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Ole E. Barndorff-Nielsen

(deceased)

Citations

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Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.

    Mentioned in:

    1. Estimating quadratic variation using realized variance (Journal of Applied Econometrics 2002) in ReplicationWiki ()

Working papers

  1. Ole E. Barndorff-Nielsen, 2016. "Assessing Gamma kernels and BSS/LSS processes," CREATES Research Papers 2016-09, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," Papers 1608.01895, arXiv.org, revised Mar 2018.
    2. Mikkel Bennedsen & Ulrich Hounyo & Asger Lunde & Mikko S. Pakkanen, 2016. "The Local Fractional Bootstrap," CREATES Research Papers 2016-15, Department of Economics and Business Economics, Aarhus University.
    3. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," CREATES Research Papers 2016-21, Department of Economics and Business Economics, Aarhus University.
    4. Mikkel Bennedsen & Ulrich Hounyo & Asger Lunde & Mikko S. Pakkanen, 2016. "The Local Fractional Bootstrap," Papers 1605.00868, arXiv.org, revised Oct 2017.

  2. Barndorff-Nielsen, Ole E. & Lunde, Asger & Shephard, Neil & Veraart, Almut E.D., 2014. "Integer-valued trawl processes: A class of stationary infinitely divisible processes," Scholarly Articles 34650304, Harvard University Department of Economics.

    Cited by:

    1. Mikkel Bennedsen & Asger Lunde & Neil Shephard & Almut E. D. Veraart, 2021. "Inference and forecasting for continuous-time integer-valued trawl processes," Papers 2107.03674, arXiv.org, revised Feb 2023.
    2. Veraart, Almut E.D., 2019. "Modeling, simulation and inference for multivariate time series of counts using trawl processes," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 110-129.
    3. Bennedsen, Mikkel & Lunde, Asger & Shephard, Neil & Veraart, Almut E.D., 2023. "Inference and forecasting for continuous-time integer-valued trawl processes," Journal of Econometrics, Elsevier, vol. 236(2).
    4. Leonte, Dan & Veraart, Almut E.D., 2024. "Simulation methods and error analysis for trawl processes and ambit fields," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 215(C), pages 518-542.
    5. Ole E. Barndorff-Nielsen & Orimar Sauri & Benedykt Szozda, 2017. "Selfdecomposable Fields," Journal of Theoretical Probability, Springer, vol. 30(1), pages 233-267, March.
    6. Doukhan, Paul & Jakubowski, Adam & Lopes, Silvia R.C. & Surgailis, Donatas, 2019. "Discrete-time trawl processes," Stochastic Processes and their Applications, Elsevier, vol. 129(4), pages 1326-1348.
    7. Valentin Courgeau & Almut E.D. Veraart, 2022. "Asymptotic theory for the inference of the latent trawl model for extreme values," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1448-1495, December.
    8. Grahovac, Danijel & Leonenko, Nikolai N. & Taqqu, Murad S., 2018. "Intermittency of trawl processes," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 235-242.
    9. Mikkel Bennedsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2021. "Inference and forecasting for continuous-time integer-valued trawl processes and their use in financial economics," CREATES Research Papers 2021-12, Department of Economics and Business Economics, Aarhus University.

  3. Ole E. Barndorff-Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2013. "Modelling energy spot prices by volatility modulated L\'{e}vy-driven Volterra processes," Papers 1307.6332, arXiv.org.

    Cited by:

    1. Brix, Anne Floor & Lunde, Asger & Wei, Wei, 2018. "A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method," Energy Economics, Elsevier, vol. 72(C), pages 560-582.
    2. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    3. Benth, Fred Espen & Koekebakker, Steen, 2015. "Pricing of forwards and other derivatives in cointegrated commodity markets," Energy Economics, Elsevier, vol. 52(PA), pages 104-117.
    4. Sauri, Orimar & Veraart, Almut E.D., 2017. "On the class of distributions of subordinated Lévy processes and bases," Stochastic Processes and their Applications, Elsevier, vol. 127(2), pages 475-496.
    5. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
    6. Ladokhin, Sergiy & Borovkova, Svetlana, 2021. "Three-factor commodity forward curve model and its joint P and Q dynamics," Energy Economics, Elsevier, vol. 101(C).
    7. Borovkova, Svetlana & Schmeck, Maren Diane, 2017. "Electricity price modeling with stochastic time change," Energy Economics, Elsevier, vol. 63(C), pages 51-65.
    8. Almut E. D. Veraart & Luitgard A. M. Veraart, 2013. "Risk premia in energy markets," CREATES Research Papers 2013-02, Department of Economics and Business Economics, Aarhus University.
    9. Andr'es C'ardenas & Sergio Pulido & Rafael Serrano, 2022. "Existence of optimal controls for stochastic Volterra equations," Papers 2207.05169, arXiv.org, revised Mar 2024.
    10. Awdesch Melzer & Wolfgang K. Härdle & Brenda López Cabrera, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers SFB649DP2017-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2016. "Decoupling the short- and long-term behavior of stochastic volatility," Papers 1610.00332, arXiv.org, revised Jan 2021.
    12. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," Papers 1608.01895, arXiv.org, revised Mar 2018.
    13. Benth, Fred Espen & Taib, Che Mohd Imran Che, 2013. "On the speed towards the mean for continuous time autoregressive moving average processes with applications to energy markets," Energy Economics, Elsevier, vol. 40(C), pages 259-268.
    14. Rowińska, Paulina A. & Veraart, Almut E.D. & Gruet, Pierre, 2021. "A multi-factor approach to modelling the impact of wind energy on electricity spot prices," Energy Economics, Elsevier, vol. 104(C).
    15. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Hybrid scheme for Brownian semistationary processes," Finance and Stochastics, Springer, vol. 21(4), pages 931-965, October.
    16. Asger Lunde & Anne Floor Brix & Wei Wei, 2015. "A Generalized Schwartz Model for Energy Spot Prices - Estimation using a Particle MCMC Method," CREATES Research Papers 2015-46, Department of Economics and Business Economics, Aarhus University.
    17. Fred Espen Benth & Hanna Zdanowicz, 2016. "Pricing And Hedging Of Energy Spread Options And Volatility Modulated Volterra Processes," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-22, February.
    18. Ole E. Barndorff-Nielsen & Mikko S. Pakkanen & Jürgen Schmiegel, 2013. "Assessing Relative Volatility/Intermittency/Energy Dissipation," CREATES Research Papers 2013-15, Department of Economics and Business Economics, Aarhus University.
    19. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2015. "Hybrid scheme for Brownian semistationary processes," CREATES Research Papers 2015-43, Department of Economics and Business Economics, Aarhus University.
    20. Jiao, Ying & Ma, Chunhua & Scotti, Simone & Sgarra, Carlo, 2019. "A branching process approach to power markets," Energy Economics, Elsevier, vol. 79(C), pages 144-156.
    21. Josselin Garnier & Knut Solna, 2015. "Correction to Black-Scholes formula due to fractional stochastic volatility," Papers 1509.01175, arXiv.org, revised Mar 2017.
    22. Andreas Basse-O'Connor & Raphaël Lachièze-Rey & Mark Podolskij, 2015. "Limit theorems for stationary increments Lévy driven moving averages," CREATES Research Papers 2015-56, Department of Economics and Business Economics, Aarhus University.
    23. Fred Espen Benth & Salvador Ortiz-Latorre, 2013. "A pricing measure to explain the risk premium in power markets," Papers 1308.3378, arXiv.org.
    24. Orcan Ogetbil & Bernhard Hientzsch, 2022. "A Flexible Commodity Skew Model with Maturity Effects," Papers 2212.07972, arXiv.org.
    25. Bender, Christian & Knobloch, Robert & Oberacker, Philip, 2015. "A generalised Itō formula for Lévy-driven Volterra processes," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2989-3022.
    26. Mark Podolskij, 2014. "Ambit fields: survey and new challenges," CREATES Research Papers 2014-51, Department of Economics and Business Economics, Aarhus University.
    27. Fred Espen Benth & Hanna Zdanowicz, 2014. "Pricing and hedging of energy spread options and volatility modulated Volterra processes," Papers 1409.5801, arXiv.org.
    28. Bennedsen, Mikkel, 2017. "A rough multi-factor model of electricity spot prices," Energy Economics, Elsevier, vol. 63(C), pages 301-313.
    29. Gudkov, Nikolay & Ignatieva, Katja, 2021. "Electricity price modelling with stochastic volatility and jumps: An empirical investigation," Energy Economics, Elsevier, vol. 98(C).
    30. Mikkel Bennedsen, 2015. "Rough electricity: a new fractal multi-factor model of electricity spot prices," CREATES Research Papers 2015-42, Department of Economics and Business Economics, Aarhus University.
    31. Li, Yuan & Pakkanen, Mikko S. & Veraart, Almut E.D., 2023. "Limit theorems for the realised semicovariances of multivariate Brownian semistationary processes," Stochastic Processes and their Applications, Elsevier, vol. 155(C), pages 202-231.
    32. Fred Espen Benth & Heidar Eyjolfsson, 2015. "Representation and approximation of ambit fields in Hilbert space," Papers 1509.08272, arXiv.org.
    33. Benth, Fred Espen & Paraschiv, Florentina, 2016. "A Structural Model for Electricity Forward Prices," Working Papers on Finance 1611, University of St. Gallen, School of Finance.
    34. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    35. Benth, Fred Espen & Paraschiv, Florentina, 2018. "A space-time random field model for electricity forward prices," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 203-216.
    36. Andrés Cárdenas & Sergio Pulido & Rafael Serrano, 2022. "Existence of optimal controls for stochastic Volterra equations," Working Papers hal-03720342, HAL.
    37. Mikkel Bennedsen & Ulrich Hounyo & Asger Lunde & Mikko S. Pakkanen, 2016. "The Local Fractional Bootstrap," CREATES Research Papers 2016-15, Department of Economics and Business Economics, Aarhus University.
    38. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," CREATES Research Papers 2016-21, Department of Economics and Business Economics, Aarhus University.
    39. Mark Podolskij & Nopporn Thamrongrat, 2015. "A weak limit theorem for numerical approximation of Brownian semi-stationary processes," CREATES Research Papers 2015-53, Department of Economics and Business Economics, Aarhus University.
    40. Fred Espen Benth & Paul Kruhner, 2014. "Representation of infinite dimensional forward price models in commodity markets," Papers 1403.4111, arXiv.org.
    41. Barndorff-Nielsen, Ole E. & Benth, Fred Espen & Pedersen, Jan & Veraart, Almut E.D., 2014. "On stochastic integration for volatility modulated Lévy-driven Volterra processes," Stochastic Processes and their Applications, Elsevier, vol. 124(1), pages 812-847.
    42. Dennis Schroers, 2024. "Robust Functional Data Analysis for Stochastic Evolution Equations in Infinite Dimensions," Papers 2401.16286, arXiv.org.
    43. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2015. "Hybrid scheme for Brownian semistationary processes," Papers 1507.03004, arXiv.org, revised May 2017.
    44. Fred Espen Benth & Asma Khedher & Mich`ele Vanmaele, 2017. "Pricing of commodity derivatives on processes with memory," Papers 1711.00307, arXiv.org.
    45. Fred Espen Benth & Heidar Eyjolfsson, 2016. "Simulation of volatility modulated Volterra processes using hyperbolic stochastic partial differential equations," Papers 1602.02907, arXiv.org.
    46. Ignatieva, Katja & Wong, Patrick, 2022. "Modelling high frequency crude oil dynamics using affine and non-affine jump–diffusion models," Energy Economics, Elsevier, vol. 108(C).
    47. Mikkel Bennedsen & Ulrich Hounyo & Asger Lunde & Mikko S. Pakkanen, 2016. "The Local Fractional Bootstrap," Papers 1605.00868, arXiv.org, revised Oct 2017.
    48. Fred Espen Benth & Asma Khedher & Michèle Vanmaele, 2020. "Pricing of Commodity Derivatives on Processes with Memory," Risks, MDPI, vol. 8(1), pages 1-32, January.
    49. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2014. "Discretization of Lévy semistationary processes with application to estimation," CREATES Research Papers 2014-21, Department of Economics and Business Economics, Aarhus University.
    50. Benth, Fred Espen & Rüdiger, Barbara & Süss, Andre, 2018. "Ornstein–Uhlenbeck processes in Hilbert space with non-Gaussian stochastic volatility," Stochastic Processes and their Applications, Elsevier, vol. 128(2), pages 461-486.

  4. Ole E. Barndorff-Nielsen & Mikko S. Pakkanen & Jürgen Schmiegel, 2013. "Assessing Relative Volatility/Intermittency/Energy Dissipation," CREATES Research Papers 2013-15, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Vicky Fasen, 2016. "Dependence Estimation for High-frequency Sampled Multivariate CARMA Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 292-320, March.
    2. Ole E. Barndorff-Nielsen, 2016. "Assessing Gamma kernels and BSS/LSS processes," CREATES Research Papers 2016-09, Department of Economics and Business Economics, Aarhus University.
    3. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2014. "Discretization of Lévy semistationary processes with application to estimation," CREATES Research Papers 2014-21, Department of Economics and Business Economics, Aarhus University.

  5. Ole E. Barndorff-Nielsen & Neil Shephard, 2012. "Basics of Levy processes," Economics Papers 2012-W06, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Pasquali, Sara, 2021. "A stage structured demographic model with “no-regression” growth: The case of constant development rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    2. Feng Guanhao & Polson Nicholas & Xu Jianeng, 2016. "The market for English Premier League (EPL) odds," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(4), pages 167-178, December.
    3. Shu, Yin & Feng, Qianmei & Liu, Hao, 2019. "Using degradation-with-jump measures to estimate life characteristics of lithium-ion battery," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    4. Gajda, Janusz & Beghin, Luisa, 2021. "Prabhakar Lévy processes," Statistics & Probability Letters, Elsevier, vol. 178(C).

  6. Ole E. Barndorff–Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2010. "Modelling electricity forward markets by ambit fields," CREATES Research Papers 2010-41, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kerstin Gärtner & Mark Podolskij, 2014. "On non-standard limits of Brownian semi-stationary," CREATES Research Papers 2014-50, Department of Economics and Business Economics, Aarhus University.
    2. Fred Espen Benth & Paul Kruhner, 2014. "Derivatives pricing in energy markets: an infinite dimensional approach," Papers 1412.7943, arXiv.org.
    3. Schnurr Alexander & Woerner Jeannette H. C., 2011. "Well-balanced Lévy driven Ornstein–Uhlenbeck processes," Statistics & Risk Modeling, De Gruyter, vol. 28(4), pages 343-357, December.
    4. Farshid Mehrdoust & Idin Noorani, 2023. "Valuation of Spark-Spread Option Written on Electricity and Gas Forward Contracts Under Two-Factor Models with Non-Gaussian Lévy Processes," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 807-853, February.
    5. Heinrich, Claudio & Pakkanen, Mikko S. & Veraart, Almut E.D., 2019. "Hybrid simulation scheme for volatility modulated moving average fields," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 166(C), pages 224-244.
    6. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, December.
    7. Ole E. Barndorff-Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2013. "Modelling energy spot prices by volatility modulated L\'{e}vy-driven Volterra processes," Papers 1307.6332, arXiv.org.
    8. Pakkanen, Mikko S., 2014. "Limit theorems for power variations of ambit fields driven by white noise," Stochastic Processes and their Applications, Elsevier, vol. 124(5), pages 1942-1973.
    9. Benth, Fred Espen & Rüdiger, Barbara & Süss, Andre, 2018. "Ornstein–Uhlenbeck processes in Hilbert space with non-Gaussian stochastic volatility," Stochastic Processes and their Applications, Elsevier, vol. 128(2), pages 461-486.

  7. Ole E. Barndorff–Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2010. "Modelling energy spot prices by Lévy semistationary processes," CREATES Research Papers 2010-18, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Pan, Zhiyuan & Liu, Li, 2018. "Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 168-180.
    2. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, December.
    3. Sanjay Sehgal & Neharika Sobti & Florent Diesting, 2021. "Who leads in intraday gold price discovery and volatility connectedness: Spot, futures, or exchange‐traded fund?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1092-1123, July.
    4. Ole E. Barndorff-Nielsen, 2016. "Assessing Gamma kernels and BSS/LSS processes," CREATES Research Papers 2016-09, Department of Economics and Business Economics, Aarhus University.
    5. Luo, Jiawen & Marfatia, Hardik A. & Ji, Qiang & Klein, Tony, 2023. "Co-volatility and asymmetric transmission of risks between the global oil and China's futures markets," Energy Economics, Elsevier, vol. 117(C).
    6. Mikko S. Pakkanen, 2011. "Brownian Semistationary Processes And Conditional Full Support," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(04), pages 579-586.
    7. Sobti, Neharika & Sehgal, Sanjay & Ilango, Balakrishnan, 2021. "How do macroeconomic news surprises affect round-the-clock price discovery of gold?," International Review of Financial Analysis, Elsevier, vol. 78(C).

  8. Ole E. Barndorff–Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2010. "Ambit processes and stochastic partial differential equations," CREATES Research Papers 2010-17, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Fred Espen Benth & Paul Kruhner, 2014. "Derivatives pricing in energy markets: an infinite dimensional approach," Papers 1412.7943, arXiv.org.
    2. Fred Espen Benth & Heidar Eyjolfsson, 2015. "Representation and approximation of ambit fields in Hilbert space," Papers 1509.08272, arXiv.org.
    3. Ole E. Barndorff-Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2013. "Modelling energy spot prices by volatility modulated L\'{e}vy-driven Volterra processes," Papers 1307.6332, arXiv.org.
    4. Ole E. Barndorff-Nielsen, 2016. "Assessing Gamma kernels and BSS/LSS processes," CREATES Research Papers 2016-09, Department of Economics and Business Economics, Aarhus University.
    5. Fred Espen Benth & Heidar Eyjolfsson, 2016. "Simulation of volatility modulated Volterra processes using hyperbolic stochastic partial differential equations," Papers 1602.02907, arXiv.org.
    6. Pakkanen, Mikko S., 2014. "Limit theorems for power variations of ambit fields driven by white noise," Stochastic Processes and their Applications, Elsevier, vol. 124(5), pages 1942-1973.

  9. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Limit theorems for functionals of higher order differences of Brownian semi-stationary processes," CREATES Research Papers 2009-60, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Mark Podolskij & Katrin Wasmuth, 2012. "Goodness-of-fit testing for fractional diffusions," CREATES Research Papers 2012-12, Department of Economics and Business Economics, Aarhus University.

  10. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Multipower Variation for Brownian Semistationary Processes," CREATES Research Papers 2009-21, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Ivan Nourdin & Giovanni Peccati & Mark Podolskij, 2010. "Quantitative Breuer-Major Theorems," CREATES Research Papers 2010-22, Department of Economics and Business Economics, Aarhus University.
    2. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Limit theorems for functionals of higher order differences of Brownian semi-stationary processes," CREATES Research Papers 2009-60, Department of Economics and Business Economics, Aarhus University.
    3. Mark Podolskij & Katrin Wasmuth, 2012. "Goodness-of-fit testing for fractional diffusions," CREATES Research Papers 2012-12, Department of Economics and Business Economics, Aarhus University.
    4. José Manuel Corcuera, 2012. "New Central Limit Theorems for Functionals of Gaussian Processes and their Applications," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 477-500, September.
    5. José Manuel Corcuera & Emil Hedevang & Mikko S. Pakkanen & Mark Podolskij, 2012. "Asymptotic theory for Brownian semi-stationary processes with application to turbulence," CREATES Research Papers 2012-52, Department of Economics and Business Economics, Aarhus University.

  11. Ole E. Barndorff-Nielsen & Almut E. D. Veraart, 2009. "Stochastic volatility of volatility in continuous time," CREATES Research Papers 2009-25, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Almut Veraart & Luitgard Veraart, 2012. "Stochastic volatility and stochastic leverage," Annals of Finance, Springer, vol. 8(2), pages 205-233, May.
    2. Imma Valentina Curato, 2012. "Asymptotics for the Fourier estimators of the volatility of volatility and the leverage," Working Papers - Mathematical Economics 2012-11, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    3. Giacomo Toscano & Maria Cristina Recchioni, 2022. "Bias-optimal vol-of-vol estimation: the role of window overlapping," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 137-185, June.
    4. Giacomo Toscano & Maria Cristina Recchioni, 2020. "Bias optimal vol-of-vol estimation: the role of window overlapping," Papers 2004.04013, arXiv.org, revised Jul 2021.
    5. Figueroa-López, José E. & Li, Cheng, 2020. "Optimal kernel estimation of spot volatility of stochastic differential equations," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 4693-4720.
    6. Li, Yingying & Liu, Guangying & Zhang, Zhiyuan, 2022. "Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps," Journal of Econometrics, Elsevier, vol. 229(2), pages 422-451.
    7. Giacomo Toscano & Giulia Livieri & Maria Elvira Mancino & Stefano Marmi, 2021. "Volatility of volatility estimation: central limit theorems for the Fourier transform estimator and empirical study of the daily time series stylized facts," Papers 2112.14529, arXiv.org, revised Sep 2022.

  12. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," CREATES Research Papers 2008-63, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    2. Yuta Koike, 2013. "Limit Theorems for the Pre-averaged Hayashi-Yoshida Estimator with Random Sampling," Global COE Hi-Stat Discussion Paper Series gd12-276, Institute of Economic Research, Hitotsubashi University.
    3. Asai Manabu & So Mike K.P., 2015. "Long Memory and Asymmetry for Matrix-Exponential Dynamic Correlation Processes," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 1-26, January.
    4. Christensen, Kim & Podolskij, Mark & Vetter, Mathias, 2013. "On covariation estimation for multivariate continuous Itô semimartingales with noise in non-synchronous observation schemes," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 59-84.
    5. Manabu Asai & Rangan Gupta & Michael McAleer, 2019. "The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures," Working Papers 201925, University of Pretoria, Department of Economics.
    6. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    7. Santos, André A.P. & Nogales, Francisco J. & Ruiz, Esther & Dijk, Dick Van, 2012. "Optimal portfolios with minimum capital requirements," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1928-1942.
    8. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," KIER Working Papers 840, Kyoto University, Institute of Economic Research.
    9. Chaker, Selma, 2019. "The signal and the noise volatilities," Research in International Business and Finance, Elsevier, vol. 50(C), pages 79-105.
    10. Silja Kinnebrock & Mark Podolskij, 2008. "An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models," CREATES Research Papers 2008-23, Department of Economics and Business Economics, Aarhus University.
    11. Koike, Yuta, 2014. "Limit theorems for the pre-averaged Hayashi–Yoshida estimator with random sampling," Stochastic Processes and their Applications, Elsevier, vol. 124(8), pages 2699-2753.
    12. Jianqing Fan & Yingying Li & Ke Yu, 2012. "Vast Volatility Matrix Estimation Using High-Frequency Data for Portfolio Selection," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 412-428, March.
    13. Manabu Asai & Michael McAleer, 2017. "The impact of jumps and leverage in forecasting covolatility," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 638-650, October.
    14. Jozef Baruník & Evžen Kocenda & Lukáš Vácha, 2015. "Asymmetric Connectedness on the U.S. Stock Market: Bad and Good Volatility Spillover," CESifo Working Paper Series 5305, CESifo.
    15. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    16. Altmeyer, Randolf & Bibinger, Markus, 2015. "Functional stable limit theorems for quasi-efficient spectral covolatility estimators," Stochastic Processes and their Applications, Elsevier, vol. 125(12), pages 4556-4600.
    17. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    18. Rasmus Tangsgaard Varneskov, 2011. "Flat-Top Realized Kernel Estimation of Quadratic Covariation with Non-Synchronous and Noisy Asset Prices," CREATES Research Papers 2011-35, Department of Economics and Business Economics, Aarhus University.
    19. Kim Christensen & Charlotte Christiansen & Anders M. Posselt, 2019. "The Economic Value of VIX ETPs," CREATES Research Papers 2019-14, Department of Economics and Business Economics, Aarhus University.
    20. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    21. Peter R. Hansen & Asger Lunde & Valeri Voev, 2010. "Realized Beta GARCH: A Multivariate GARCH Model with Realized Measures of Volatility and CoVolatility," CREATES Research Papers 2010-74, Department of Economics and Business Economics, Aarhus University.
    22. Cai, T. Tony & Hu, Jianchang & Li, Yingying & Zheng, Xinghua, 2020. "High-dimensional minimum variance portfolio estimation based on high-frequency data," Journal of Econometrics, Elsevier, vol. 214(2), pages 482-494.
    23. Maria Elvira Mancino & Simona Sanfelici, 2011. "Estimation of Quarticity with High Frequency Data," Working Papers - Mathematical Economics 2011-06, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, revised Jan 2012.
    24. Andrew Ang & Dennis Kristensen, 2011. "Testing Conditional Factor Models," NBER Working Papers 17561, National Bureau of Economic Research, Inc.
    25. Jiayuan Zhou & Feiyu Jiang & Ke Zhu & Wai Keung Li, 2019. "Time series models for realized covariance matrices based on the matrix-F distribution," Papers 1903.12077, arXiv.org, revised Jul 2020.
    26. Stanislav Anatolyev & Nikita Kobotaev, 2018. "Modeling and forecasting realized covariance matrices with accounting for leverage," Econometric Reviews, Taylor & Francis Journals, vol. 37(2), pages 114-139, February.
    27. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    28. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Tinbergen Institute Discussion Papers 14-037/III, Tinbergen Institute.
    29. Qu, Hui & Wang, Tianyang & Zhang, Yi & Sun, Pengfei, 2019. "Dynamic hedging using the realized minimum-variance hedge ratio approach – Examination of the CSI 300 index futures," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    30. Peter Reinhard Hansen & Zhuo Huang, 2012. "Exponential GARCH Modeling with Realized Measures of Volatility," CREATES Research Papers 2012-44, Department of Economics and Business Economics, Aarhus University.
    31. Andersen, Torben G. & Bollerslev, Tim & Meddahi, Nour, 2011. "Realized volatility forecasting and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 220-234, January.
    32. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
    33. Diebold, Francis X. & Strasser, Georg H., 2008. "On the correlation structure of microstructure noise in theory and practice," CFS Working Paper Series 2008/32, Center for Financial Studies (CFS).
    34. Dark, Jonathan, 2015. "Futures hedging with Markov switching vector error correction FIEGARCH and FIAPARCH," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 269-285.
    35. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    36. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    37. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    38. Tsiaras, Leonidas, 2009. "The Forecast Performance of Competing Implied Volatility Measures: The Case of Individual Stocks," Finance Research Group Working Papers F-2009-02, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    39. Vortelinos, Dimitrios I., 2013. "Portfolio analysis of intraday covariance matrix in the Greek equity market," Research in International Business and Finance, Elsevier, vol. 27(1), pages 66-79.
    40. Peter Reinhard Hansen & Guillaume Horel & Asger Lunde & Ilya Archakov, 2015. "A Markov Chain Estimator of Multivariate Volatility from High Frequency Data," CREATES Research Papers 2015-19, Department of Economics and Business Economics, Aarhus University.
    41. Audrino, Francesco & Corsi, Fulvio, 2010. "Modeling tick-by-tick realized correlations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2372-2382, November.
    42. Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    43. Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Janeway Institute Working Papers 2208, Faculty of Economics, University of Cambridge.
    44. Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    45. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    46. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    47. Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.
    48. Liu, Cheng & Tang, Cheng Yong, 2014. "A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data," Journal of Econometrics, Elsevier, vol. 180(2), pages 217-232.
    49. Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
    50. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
    51. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    52. Dinghai Xu, 2021. "A study on volatility spurious almost integration effect: A threshold realized GARCH approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4104-4126, July.
    53. Roxana Halbleib & Valeri Voev, 2012. "Forecasting Covariance Matrices: A Mixed Frequency Approach," Working Paper Series of the Department of Economics, University of Konstanz 2012-30, Department of Economics, University of Konstanz.
    54. Varneskov, Rasmus & Voev, Valeri, 2013. "The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 83-95.
    55. Xin-Bing Kong, 2013. "A direct approach to risk approximation for vast portfolios under gross-exposure constraint using high-frequency data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(4), pages 647-669, November.
    56. Ilya Archakov & Peter Reinhard Hansen & Asger Lunde, 2020. "A Multivariate Realized GARCH Model," Papers 2012.02708, arXiv.org.
    57. Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
    58. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    59. Yu‐Sheng Lai, 2019. "Flexible covariance dynamics, high‐frequency data, and optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1529-1548, December.
    60. Shen, Keren & Yao, Jianfeng & Li, Wai Keung, 2019. "On a spiked model for large volatility matrix estimation from noisy high-frequency data," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 207-221.
    61. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," Cahiers de recherche 0948, CIRPEE.
    62. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    63. Ubukata, Masato, 2018. "Dynamic hedging performance and downside risk: Evidence from Nikkei index futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 270-281.
    64. Gustavo Fruet Dias & Fotis Papailias & Cristina Scherrer, 2024. "An Econometric Analysis of Volatility Discovery," University of East Anglia School of Economics Working Paper Series 2024-01, School of Economics, University of East Anglia, Norwich, UK..
    65. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    66. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.
    67. Neil Shephard & Dacheng Xiu, 2012. "Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices," Economics Papers 2012-W04, Economics Group, Nuffield College, University of Oxford.
    68. Todorov, Viktor & Bollerslev, Tim, 2010. "Jumps and betas: A new framework for disentangling and estimating systematic risks," Journal of Econometrics, Elsevier, vol. 157(2), pages 220-235, August.
    69. Yao Axel Ehouman, 2020. "Volatility transmission between oil prices and banks’ stock prices as a new source of instability: Lessons from the United States experience," Post-Print hal-02960571, HAL.
    70. Kevin Sheppard & Wen Xu, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    71. Aït-Sahalia, Yacine & Xiu, Dacheng, 2016. "Increased correlation among asset classes: Are volatility or jumps to blame, or both?," Journal of Econometrics, Elsevier, vol. 194(2), pages 205-219.
    72. Michael C. Münnix & Rudi Schäfer & Thomas Guhr, 2011. "Statistical Causes For The Epps Effect In Microstructure Noise," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(08), pages 1231-1246.
    73. Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2013. "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns," CREATES Research Papers 2013-07, Department of Economics and Business Economics, Aarhus University.
    74. Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
    75. Clifford Lam & Phoenix Feng & Charlie Hu, 2017. "Nonlinear shrinkage estimation of large integrated covariance matrices," Biometrika, Biometrika Trust, vol. 104(2), pages 481-488.
    76. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    77. Kevin Sheppard & Wen Xu, 2019. "Factor High-Frequency-Based Volatility (HEAVY) Models," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 33-65.
    78. Francis X. Diebold & Georg H. Strasser, 2008. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," Boston College Working Papers in Economics 693, Boston College Department of Economics, revised 24 Apr 2012.
    79. Ogihara, Teppei & Yoshida, Nakahiro, 2014. "Quasi-likelihood analysis for nonsynchronously observed diffusion processes," Stochastic Processes and their Applications, Elsevier, vol. 124(9), pages 2954-3008.
    80. Dimitrios I. Vortelinos, 2015. "The Effect of Macro News on Volatility and Jumps," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 425-447, November.
    81. Jim Griffin & Jia Liu & John M. Maheu, 2021. "Bayesian Nonparametric Estimation of Ex Post Variance [Out of Sample Forecasts of Quadratic Variation]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 823-859.
    82. Jin, Xin & Maheu, John M & Yang, Qiao, 2017. "Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices," MPRA Paper 81920, University Library of Munich, Germany.
    83. Bollerslev, Tim & Meddahi, Nour & Nyawa, Serge, 2019. "High-dimensional multivariate realized volatility estimation," Journal of Econometrics, Elsevier, vol. 212(1), pages 116-136.
    84. Christensen, Kim & Kinnebrock, Silja & Podolskij, Mark, 2010. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," Journal of Econometrics, Elsevier, vol. 159(1), pages 116-133, November.
    85. Markus Bibinger & Nikolaus Hautsch & Peter Malec & Markus Reiss, 2013. "Estimating the Quadratic Covariation Matrix from Noisy Observations: Local Method of Moments and Efficiency," SFB 649 Discussion Papers SFB649DP2013-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    86. Jalshayin Bhachech & Arnab Chakrabarti & Taisei Kaizoji & Anindya S. Chakrabarti, 2022. "Instability of networks: effects of sampling frequency and extreme fluctuations in financial data," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(4), pages 1-14, April.
    87. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    88. Boffelli, Simona & Urga, Giovanni, 2015. "Macroannouncements, bond auctions and rating actions in the European government bond spreads," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 148-173.
    89. Yuta Kurose & Yasuhiro Omori, 2016. "Multiple-block Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1024, CIRJE, Faculty of Economics, University of Tokyo.
    90. Ilze Kalnina & Natalia Sizova, 2015. "Estimation of volatility measures using high frequency data (in Russian)," Quantile, Quantile, issue 13, pages 3-14, May.
    91. Nikolaus Hautsch & Stefan Voigt, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty," Papers 1709.06296, arXiv.org, revised Jun 2018.
    92. Naoto Kunitomo & Hiroumi Misaki & Seisho Sato, 2015. "The SIML Estimation of Integrated Covariance and Hedging Coefficient Under Round-off Errors, Micro-market Price Adjustments and Random Sampling," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 22(3), pages 333-368, September.
    93. Jacod, Jean & Li, Yingying & Zheng, Xinghua, 2019. "Estimating the integrated volatility with tick observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 80-100.
    94. Lidan Grossmass, 2014. "Obtaining and Predicting the Bounds of Realized Correlations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(III), pages 191-226, September.
    95. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    96. Kim, Donggyu & Kong, Xin-Bing & Li, Cui-Xia & Wang, Yazhen, 2018. "Adaptive thresholding for large volatility matrix estimation based on high-frequency financial data," Journal of Econometrics, Elsevier, vol. 203(1), pages 69-79.
    97. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    98. Marius Matei & Xari Rovira & Núria Agell, 2019. "Bivariate Volatility Modeling with High-Frequency Data," Econometrics, MDPI, vol. 7(3), pages 1-15, September.
    99. Almut E. D. Veraart, 2010. "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?," CREATES Research Papers 2010-65, Department of Economics and Business Economics, Aarhus University.
    100. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    101. Gustavo Fruet Dias & Cristina M. Scherrer & Fotis Papailias, 2016. "Volatility Discovery," CREATES Research Papers 2016-07, Department of Economics and Business Economics, Aarhus University.
    102. Jian, Zhihong & Deng, Pingjun & Zhu, Zhican, 2018. "High-dimensional covariance forecasting based on principal component analysis of high-frequency data," Economic Modelling, Elsevier, vol. 75(C), pages 422-431.
    103. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
    104. Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    105. Rui Pedro Brito & Helder Sebastião & Pedro Godinho, 2018. "On the Gains of Using High Frequency Data in Portfolio Selection," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(4), pages 365-383, December.
    106. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised Sep 2023.
    107. Fan, Jianqing & Kim, Donggyu, 2019. "Structured volatility matrix estimation for non-synchronized high-frequency financial data," Journal of Econometrics, Elsevier, vol. 209(1), pages 61-78.
    108. Ilze Kalnina, 2023. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 538-549, April.
    109. Yao Axel Ehouman, 2019. "Volatility transmission between oil prices and banks stock prices as a new source of instability: Lessons from the US Experience," EconomiX Working Papers 2019-19, University of Paris Nanterre, EconomiX.
    110. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    111. Wenjing Wang & Minjing Tao, 2020. "Forecasting Realized Volatility Matrix With Copula-Based Models," Papers 2002.08849, arXiv.org.
    112. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    113. Ehouman, Yao Axel, 2020. "Volatility transmission between oil prices and banks' stock prices as a new source of instability: Lessons from the United States experience," Economic Modelling, Elsevier, vol. 91(C), pages 198-217.
    114. Fabrizio Cipollini & Giampiero Gallo & Alessandro Palandri, 2020. "A Dynamic Conditional Approach to Portfolio Weights Forecasting," Econometrics Working Papers Archive 2020_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    115. Sanfelici Simona & Uboldi Adamo, 2014. "Assessing the quality of volatility estimators via option pricing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(2), pages 1-22, April.
    116. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2019. "Realized variance modeling: decoupling forecasting from estimation," Econometrics Working Papers Archive 2019_05, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    117. Masato Ubukata, 2022. "A time-varying jump tail risk measure using high-frequency options data," Empirical Economics, Springer, vol. 63(5), pages 2633-2653, November.
    118. Gustavo F. Dias & Marcelo Fernandes & Cristina M. Scherrer, 2021. "Price Discovery in a Continuous-Time Setting [Price Discovery and Common Factor Models]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 985-1008.
    119. Selma Chaker, 2013. "Volatility and Liquidity Costs," Staff Working Papers 13-29, Bank of Canada.
    120. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    121. Ogihara, Teppei, 2021. "Misspecified diffusion models with high-frequency observations and an application to neural networks," Stochastic Processes and their Applications, Elsevier, vol. 142(C), pages 245-292.
    122. Zhi Liu, 2017. "Jump-robust estimation of volatility with simultaneous presence of microstructure noise and multiple observations," Finance and Stochastics, Springer, vol. 21(2), pages 427-469, April.
    123. Fulvio Corsi & Stefano Peluso & Francesco Audrino, 2015. "Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 377-397, April.
    124. Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
    125. Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2012. "Jump robust daily covariance estimation by disentangling variance and correlation components," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 2993-3005.
    126. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    127. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    128. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    129. Serge Darolles & Christian Gouriéroux & Emmanuelle Jay, 2012. "Robust Portfolio Allocation with Systematic Risk Contribution Restrictions," Working Papers 2012-35, Center for Research in Economics and Statistics.
    130. Kim, Donggyu & Wang, Yazhen & Zou, Jian, 2016. "Asymptotic theory for large volatility matrix estimation based on high-frequency financial data," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3527-3577.
    131. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    132. Philip L. H. Yu & W. K. Li & F. C. Ng, 2017. "The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 513-527, October.
    133. Asger Lunde & Kasper V. Olesen, 2014. "Modeling and Forecasting the Distribution of Energy Forward Returns - Evidence from the Nordic Power Exchange," CREATES Research Papers 2013-19, Department of Economics and Business Economics, Aarhus University.
    134. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
    135. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2015. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-979, CIRJE, Faculty of Economics, University of Tokyo.
    136. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
    137. Bibinger, Markus, 2012. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," Stochastic Processes and their Applications, Elsevier, vol. 122(6), pages 2411-2453.
    138. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.
    139. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
    140. Li, Yingying & Xie, Shangyu & Zheng, Xinghua, 2016. "Efficient estimation of integrated volatility incorporating trading information," Journal of Econometrics, Elsevier, vol. 195(1), pages 33-50.
    141. Ingmar Nolte & Valeri Voev, 2011. "Least Squares Inference on Integrated Volatility and the Relationship Between Efficient Prices and Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 94-108, April.
    142. Cipollini, Fabrizio & Gallo, Giampiero M. & Palandri, Alessandro, 2021. "A dynamic conditional approach to forecasting portfolio weights," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1111-1126.
    143. Haugom, Erik & Lien, Gudbrand & Veka, Steinar & Westgaard, Sjur, 2014. "Covariance estimation using high-frequency data: Sensitivities of estimation methods," Economic Modelling, Elsevier, vol. 43(C), pages 416-425.
    144. Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.
    145. Manabu Asai & Rangan Gupta & Michael McAleer, 2019. "Forecasting Volatility and Co-volatility of Crude Oil and Gold Futures: Effects of Leverage, Jumps, Spillovers, and Geopolitical Risks," Working Papers 201951, University of Pretoria, Department of Economics.
    146. Donggyu Kim & Minseog Oh, 2023. "Dynamic Realized Minimum Variance Portfolio Models," Papers 2310.13511, arXiv.org.
    147. Dovonon, Prosper & Gonçalves, Sílvia & Meddahi, Nour, 2013. "Bootstrapping realized multivariate volatility measures," Journal of Econometrics, Elsevier, vol. 172(1), pages 49-65.
    148. Potiron, Yoann & Mykland, Per A., 2017. "Estimation of integrated quadratic covariation with endogenous sampling times," Journal of Econometrics, Elsevier, vol. 197(1), pages 20-41.
    149. Grønborg, Niels S. & Lunde, Asger & Olesen, Kasper V. & Vander Elst, Harry, 2022. "Realizing correlations across asset classes," Journal of Financial Markets, Elsevier, vol. 59(PA).
    150. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    151. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    152. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    153. Markus Bibinger & Mathias Vetter, 2015. "Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 707-743, August.
    154. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    155. Donggyu Kim & Xinyu Song & Yazhen Wang, 2020. "Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency," Papers 2006.12039, arXiv.org.
    156. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    157. Aït-Sahalia, Yacine & Xiu, Dacheng, 2017. "Using principal component analysis to estimate a high dimensional factor model with high-frequency data," Journal of Econometrics, Elsevier, vol. 201(2), pages 384-399.
    158. Bollerslev, Tim & Medeiros, Marcelo C. & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "From zero to hero: Realized partial (co)variances," Journal of Econometrics, Elsevier, vol. 231(2), pages 348-360.
    159. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    160. Štefan Lyócsa & Peter Molnár, 2016. "Volatility forecasting of strategically linked commodity ETFs: gold-silver," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1809-1822, December.
    161. Lam, Clifford & Feng, Phoenix & Hu, Charlie, 2017. "Nonlinear shrinkage estimation of large integrated covariance matrices," LSE Research Online Documents on Economics 69812, London School of Economics and Political Science, LSE Library.
    162. Bauwens, Luc & Xu, Yongdeng, 2023. "The contribution of realized covariance models to the economic value of volatility timing," LIDAM Discussion Papers CORE 2023018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    163. Wang, Kent & Liu, Junwei & Liu, Zhi, 2013. "Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1777-1786.
    164. Markus Bibinger & Per A. Mykland, 2016. "Inference for Multi-dimensional High-frequency Data with an Application to Conditional Independence Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1078-1102, December.
    165. Kirill Dragun & Kris Boudt & Orimar Sauri & Steven Vanduffel, 2021. "Beta-Adjusted Covariance Estimation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1010, Ghent University, Faculty of Economics and Business Administration.
    166. LAURENT, Sébastien & ROMBOUTS, Jeroen V. K. & VIOLANTE, Francesco, 2010. "On the forecasting accuracy of multivariate GARCH models," LIDAM Discussion Papers CORE 2010025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    167. Masato Ubukata & Toshiaki Watanabe, 2014. "Market variance risk premiums in Japan for asset predictability," Empirical Economics, Springer, vol. 47(1), pages 169-198, August.
    168. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    169. Ruijun Bu & Degui Li & Oliver Linton & Hanchao Wang, 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Working Papers 202212, University of Liverpool, Department of Economics.
    170. Giorgio Mirone, 2018. "Cross-sectional noise reduction and more efficient estimation of Integrated Variance," CREATES Research Papers 2018-18, Department of Economics and Business Economics, Aarhus University.
    171. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Aug 2018.
    172. Yaojie Zhang & Yu Wei & Li Liu, 2019. "Improving forecasting performance of realized covariance with extensions of HAR-RCOV model: statistical significance and economic value," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1425-1438, September.
    173. Torben G. Andersen & Martin Thyrsgaard & Viktor Todorov, 2021. "Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk," Quantitative Economics, Econometric Society, vol. 12(2), pages 647-682, May.
    174. BenSaïda, Ahmed, 2019. "Good and bad volatility spillovers: An asymmetric connectedness," Journal of Financial Markets, Elsevier, vol. 43(C), pages 78-95.
    175. Robert F. Engle & Martin Klint Hansen & Asger Lunde, 2012. "And Now, The Rest of the News: Volatility and Firm Specific News Arrival," CREATES Research Papers 2012-56, Department of Economics and Business Economics, Aarhus University.
    176. Liu, Cheng & Wang, Moming & Xia, Ningning, 2022. "Design-free estimation of integrated covariance matrices for high-frequency data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    177. Manabu Asai & Mike K. P. So, 2021. "Quasi‐maximum likelihood estimation of conditional autoregressive Wishart models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 271-294, May.
    178. Wang, Chengyang & Nishiyama, Yoshihiko, 2015. "Volatility forecast of stock indices by model averaging using high-frequency data," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 324-337.
    179. Michela Verardo & Andrew Patton, 2009. "Does Beta Move with News? Systematic Risk and Firm-Specific Information Flows," FMG Discussion Papers dp630, Financial Markets Group.
    180. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    181. Yacine Aït-Sahalia & Dacheng Xiu, 2015. "Principal Component Analysis of High Frequency Data," NBER Working Papers 21584, National Bureau of Economic Research, Inc.
    182. Sun, Yucheng & Xu, Wen & Zhang, Chuanhai, 2023. "Identifying latent factors based on high-frequency data," Journal of Econometrics, Elsevier, vol. 233(1), pages 251-270.
    183. Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
    184. Gu, Tiantian & Venkateswaran, Anand & Erath, Marc, 2023. "Impact of fiscal stimulus on volatility: A cross-country analysis," Research in International Business and Finance, Elsevier, vol. 65(C).
    185. Nabil Bouamara & Kris Boudt & S'ebastien Laurent & Christopher J. Neely, 2023. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Papers 2309.15705, arXiv.org.
    186. Park, Sujin & Hong, Seok Young & Linton, Oliver, 2016. "Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error," Journal of Econometrics, Elsevier, vol. 191(2), pages 325-347.
    187. Vladimír Holý & Petra Tomanová, 2023. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 463-485, June.
    188. Flavia Barsotti & Simona Sanfelici, 2012. "Microstructure effect on firm’s volatility risk," Working Papers - Mathematical Economics 2012-05, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    189. Naoto Kunitomo & Hiroumi Misaki & Seisho Sato, 2015. "The SIML Estimation of Integrated Covariance and Hedging Coefficient under Round-off Errors, Micro-market Price Adjustments and Random Sampling," CIRJE F-Series CIRJE-F-965, CIRJE, Faculty of Economics, University of Tokyo.
    190. Zhang, Lan, 2011. "Estimating covariation: Epps effect, microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 33-47, January.
    191. Shephard, Neil & Xiu, Dacheng, 2017. "Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading," Journal of Econometrics, Elsevier, vol. 201(1), pages 19-42.
    192. Markus Bibinger & Markus Reiß, 2014. "Spectral Estimation of Covolatility from Noisy Observations Using Local Weights," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 23-50, March.
    193. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    194. Enrique Sentana, 2018. "Volatility, Diversification and Contagion," Working Papers wp2018_1803, CEMFI.
    195. Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
    196. Neil Shephard & Kevin Sheppard, 2012. "Efficient and feasible inference for the components of financial variation using blocked multipower variation," Economics Series Working Papers 593, University of Oxford, Department of Economics.
    197. Cosmin Octavian Cepoi & Filip Mihai Toma, 2016. "Estimating Probability of Informed Trading on the Bucharest Stock Exchange," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(2), pages 140-160, April.
    198. Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
    199. Hwang, Eunju & Shin, Dong Wan, 2018. "Two-stage stationary bootstrapping for bivariate average realized volatility matrix under market microstructure noise and asynchronicity," Journal of Econometrics, Elsevier, vol. 202(2), pages 178-195.
    200. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    201. Selma Chaker & Nour Meddahi, 2013. "Volatility Forecasting when the Noise Variance Is Time-Varying," Staff Working Papers 13-48, Bank of Canada.
    202. Yao Axel Ehouman, 2019. "Volatility transmission between oil prices and banks stock prices as a new source of instability: Lessons from the US Experience," Working Papers hal-04141868, HAL.
    203. Yeh, Jin-Huei & Wang, Jying-Nan, 2010. "Correcting microstructure comovement biases for integrated covariance," Finance Research Letters, Elsevier, vol. 7(3), pages 184-191, September.
    204. Maria Elvira Mancino & Simona Sanfelici, 2011. "Covariance Estimation and Dynamic Asset-Allocation under Microstructure Effects via Fourier Methodology," Palgrave Macmillan Books, in: Greg N. Gregoriou & Razvan Pascalau (ed.), Financial Econometrics Modeling: Market Microstructure, Factor Models and Financial Risk Measures, chapter 1, pages 3-32, Palgrave Macmillan.
    205. Adrian Baldwin & Iffat Gheyas & Christos Ioannidis & David Pym & Julian Williams, 2017. "Contagion in cyber security attacks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 780-791, July.
    206. Greeshma Balabhadra & El Mehdi Ainasse & Pawel Polak, 2023. "High-Frequency Volatility Estimation with Fast Multiple Change Points Detection," Papers 2303.10550, arXiv.org, revised Mar 2023.
    207. Gregory Connor & Anita Suurlaht, 2012. "Dynamic Stock Market Covariances in the Eurozone," Economics Department Working Paper Series n222-12.pdf, Department of Economics, National University of Ireland - Maynooth.
    208. Kim, Donggyu & Song, Xinyu & Wang, Yazhen, 2022. "Unified discrete-time factor stochastic volatility and continuous-time Itô models for combining inference based on low-frequency and high-frequency," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    209. Stefan Lyocsa & Peter Molnar & Igor Fedorko, 2016. "Forecasting Exchange Rate Volatility: The Case of the Czech Republic, Hungary and Poland," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(5), pages 453-475, October.
    210. Matteo Bonato & Luca Taschini, 2016. "Comovement and the financialization of commodities," GRI Working Papers 215, Grantham Research Institute on Climate Change and the Environment.
    211. Markus Bibinger & Mathias Vetter, 2013. "Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps," SFB 649 Discussion Papers SFB649DP2013-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    212. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    213. Jianqing Fan & Alex Furger & Dacheng Xiu, 2016. "Incorporating Global Industrial Classification Standard Into Portfolio Allocation: A Simple Factor-Based Large Covariance Matrix Estimator With High-Frequency Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 489-503, October.
    214. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    215. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    216. Lam, Clifford & Feng, Phoenix, 2018. "A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data," LSE Research Online Documents on Economics 88375, London School of Economics and Political Science, LSE Library.
    217. Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
    218. Lam, Clifford & Feng, Phoenix, 2018. "A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data," Journal of Econometrics, Elsevier, vol. 206(1), pages 226-257.
    219. Yu-Sheng Lai, 2018. "Dynamic hedging with futures: a copula-based GARCH model with high-frequency data," Review of Derivatives Research, Springer, vol. 21(3), pages 307-329, October.
    220. Rasmus Tangsgaard Varneskov, 2011. "Generalized Flat-Top Realized Kernel Estimation of Ex-Post Variation of Asset Prices Contaminated by Noise," CREATES Research Papers 2011-31, Department of Economics and Business Economics, Aarhus University.
    221. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    222. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2013. "Conditional alphas and realized betas," Textos para discussão 341, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    223. Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    224. Münnix, Michael C. & Schäfer, Rudi & Guhr, Thomas, 2010. "Compensating asynchrony effects in the calculation of financial correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 767-779.
    225. Xinyu Song, 2019. "Large Volatility Matrix Prediction with High-Frequency Data," Papers 1907.01196, arXiv.org, revised Sep 2019.
    226. Jian Zhou, 2017. "Forecasting REIT volatility with high-frequency data: a comparison of alternative methods," Applied Economics, Taylor & Francis Journals, vol. 49(26), pages 2590-2605, June.
    227. Ikeda, Shin S., 2016. "A bias-corrected estimator of the covariation matrix of multiple security prices when both microstructure effects and sampling durations are persistent and endogenous," Journal of Econometrics, Elsevier, vol. 193(1), pages 203-214.
    228. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    229. Arnab Chakrabarti & Rituparna Sen, 2023. "Copula Estimation for Nonsynchronous Financial Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 116-149, May.
    230. Münnix, Michael C. & Schäfer, Rudi & Guhr, Thomas, 2010. "Impact of the tick-size on financial returns and correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4828-4843.
    231. Flavia Barsotti & Simona Sanfelici, 2016. "Market Microstructure Effects on Firm Default Risk Evaluation," Econometrics, MDPI, vol. 4(3), pages 1-31, July.
    232. Michael Ho & Jack Xin, 2016. "Sparse Kalman Filtering Approaches to Covariance Estimation from High Frequency Data in the Presence of Jumps," Papers 1602.02185, arXiv.org, revised Apr 2016.
    233. Kim, Donggyu & Wang, Yazhen, 2016. "Sparse PCA-based on high-dimensional Itô processes with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 172-189.
    234. Giacomo Toscano & Giulia Livieri & Maria Elvira Mancino & Stefano Marmi, 2021. "Volatility of volatility estimation: central limit theorems for the Fourier transform estimator and empirical study of the daily time series stylized facts," Papers 2112.14529, arXiv.org, revised Sep 2022.
    235. Neil Shephard, 2020. "An estimator for predictive regression: reliable inference for financial economics," Papers 2008.06130, arXiv.org.
    236. Mike Buckle & Jing Chen & Julian Williams, 2014. "How Predictable Are Equity Covariance Matrices? Evidence from High‐Frequency Data for Four Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(7), pages 542-557, November.
    237. Yu‐Sheng Lai, 2023. "Optimal futures hedging by using realized semicovariances: The information contained in signed high‐frequency returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(5), pages 677-701, May.
    238. Ole Martin & Mathias Vetter, 2019. "Laws of large numbers for Hayashi–Yoshida-type functionals," Finance and Stochastics, Springer, vol. 23(3), pages 451-500, July.

  13. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk — realised semivariance," CREATES Research Papers 2008-42, Department of Economics and Business Economics, Aarhus University.

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    2. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2015. "Volatility transmission in global financial markets," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 3-18.
    3. Haugom, Erik & Langeland, Henrik & Molnár, Peter & Westgaard, Sjur, 2014. "Forecasting volatility of the U.S. oil market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 1-14.
    4. Kislay Kumar Jha & Dirk G. Baur, 2020. "Regime-Dependent Good and Bad Volatility of Bitcoin," JRFM, MDPI, vol. 13(12), pages 1-16, December.
    5. Mei, Dexiang & Ma, Feng & Liao, Yin & Wang, Lu, 2020. "Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models," Energy Economics, Elsevier, vol. 86(C).
    6. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    7. Wang Gao & Jiajia Wei & Shixiong Yang, 2023. "The Asymmetric Effects of Extreme Climate Risk Perception on Coal Futures Return Dynamics: Evidence from Nonparametric Causality-In-Quantiles Tests," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    8. Mei, Dexiang & Liu, Jing & Ma, Feng & Chen, Wang, 2017. "Forecasting stock market volatility: Do realized skewness and kurtosis help?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 153-159.
    9. Julien Chevallier & Benoît Sévi, 2012. "On the volatility-volume relationship in energy futures markets using intraday data," Post-Print hal-00988926, HAL.
    10. Nolte, Ingmar & Xu, Qi, 2015. "The economic value of volatility timing with realized jumps," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 45-59.
    11. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    12. Jozef Baruník & Matěj Nevrla, 2023. "Quantile Spectral Beta: A Tale of Tail Risks, Investment Horizons, and Asset Prices," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1590-1646.
    13. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    14. Svetlana Borovkova & Diego Mahakena, 2015. "News, volatility and jumps: the case of natural gas futures," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1217-1242, July.
    15. Da Fonseca, José & Xu, Yahua, 2017. "Higher moment risk premiums for the crude oil market: A downside and upside conditional decomposition," Energy Economics, Elsevier, vol. 67(C), pages 410-422.
    16. Julien Chevallier & Benoît Sévi, 2011. "On the volatility-volume relationship in energy futures markets using intraday data," Working Papers hal-04140997, HAL.
    17. Lai T. Hoang & Dirk G. Baur, 2021. "Spillovers and Asset Allocation," JRFM, MDPI, vol. 14(8), pages 1-31, July.
    18. Visser, Marcel P., 2008. "Forecasting S&P 500 Daily Volatility using a Proxy for Downward Price Pressure," MPRA Paper 11100, University Library of Munich, Germany.
    19. Peter, Eckley, 2015. "Measuring economic uncertainty using news-media textual data," MPRA Paper 64874, University Library of Munich, Germany, revised 01 May 2015.
    20. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2021. "Forecasting realised volatility: Does the LASSO approach outperform HAR?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    21. Wang, Jiqian & Huang, Yisu & Ma, Feng & Chevallier, Julien, 2020. "Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? New evidence," Energy Economics, Elsevier, vol. 91(C).
    22. Zhang, Hongwei & Jin, Chen & Bouri, Elie & Gao, Wang & Xu, Yahua, 2023. "Realized higher-order moments spillovers between commodity and stock markets: Evidence from China," Journal of Commodity Markets, Elsevier, vol. 30(C).
    23. Luo, Xin & Tao, Yunqing & Zou, Kai, 2022. "A new measure of realized volatility: Inertial and reverse realized semivariance," Finance Research Letters, Elsevier, vol. 47(PA).
    24. Roh, Tai-Yong & Byun, Suk Joon & Xu, Yahua, 2020. "Downside uncertainty shocks in the oil and gold markets," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 291-307.
    25. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    26. Chao Zhang & Yihuang Zhang & Mihai Cucuringu & Zhongmin Qian, 2022. "Volatility forecasting with machine learning and intraday commonality," Papers 2202.08962, arXiv.org, revised Feb 2023.
    27. Srivastava, Pranjal & Jacob, Joshy, 2022. "Arbitrage constraints and behaviour of volatility components: Evidence from a natural experiment," IIMA Working Papers WP 2022-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    28. Fulvio Corsi & Roberto Renò, 2012. "Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 368-380, January.
    29. Si Mohammed, Kamel & Tedeschi, Marco & Mallek, Sabrine & Tarczyńska-Łuniewska, Małgorzata & Zhang, Anqi, 2023. "Realized semi variance quantile connectedness between oil prices and stock market: Spillover from Russian-Ukraine clash," Resources Policy, Elsevier, vol. 85(PA).
    30. Glenn Kit Foong Ho & Sirimon Treepongkaruna & Marvin Wee & Chaiyuth Padungsaksawasdi, 2022. "The effect of short selling on volatility and jumps," Australian Journal of Management, Australian School of Business, vol. 47(1), pages 34-52, February.
    31. Xie, Nan & Wang, Zongrun & Chen, Sicen & Gong, Xu, 2019. "Forecasting downside risk in China’s stock market based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 530-541.
    32. Apergis, Nicholas, 2023. "Realized higher-order moments spillovers across cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    33. Wang, Ziwei & Li, Youwei & He, Feng, 2020. "Asymmetric volatility spillovers between economic policy uncertainty and stock markets: Evidence from China," Research in International Business and Finance, Elsevier, vol. 53(C).
    34. Peter Reinhard Hansen & Guillaume Horel, 2009. "Quadratic Variation by Markov Chains," CREATES Research Papers 2009-13, Department of Economics and Business Economics, Aarhus University.
    35. Todorova, Neda & Clements, Adam E., 2018. "The volatility-volume relationship in the LME futures market for industrial metals," Resources Policy, Elsevier, vol. 58(C), pages 111-124.
    36. Chen, Yufeng & Li, Wenqi & Qu, Fang, 2019. "Dynamic asymmetric spillovers and volatility interdependence on China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 825-838.
    37. Lu, Botao & Ma, Feng & Wang, Jiqian & Ding, Hui & Wahab, M.I.M., 2021. "Harnessing the decomposed realized measures for volatility forecasting: Evidence from the US stock market," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 672-689.
    38. He, Feng & Ma, Feng & Wang, Ziwei & Yang, Bohan, 2021. "Asymmetric volatility spillover between oil-importing and oil-exporting countries' economic policy uncertainty and China's energy sector," International Review of Financial Analysis, Elsevier, vol. 75(C).

  14. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2007. "Power variation for Gaussian processes with stationary increments," CREATES Research Papers 2007-42, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Mikko S. Pakkanen & Anthony Réveillac, 2014. "Functional limit theorems for generalized variations of the fractional Brownian sheet," CREATES Research Papers 2014-14, Department of Economics and Business Economics, Aarhus University.
    2. Mark Podolskij & Katrin Wasmuth, 2013. "Goodness-of-fit testing for fractional diffusions," Statistical Inference for Stochastic Processes, Springer, vol. 16(2), pages 147-159, July.
    3. Kerstin Gärtner & Mark Podolskij, 2014. "On non-standard limits of Brownian semi-stationary," CREATES Research Papers 2014-50, Department of Economics and Business Economics, Aarhus University.
    4. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
    5. Ivan Nourdin & Giovanni Peccati & Mark Podolskij, 2010. "Quantitative Breuer-Major Theorems," CREATES Research Papers 2010-22, Department of Economics and Business Economics, Aarhus University.
    6. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Limit theorems for functionals of higher order differences of Brownian semi-stationary processes," CREATES Research Papers 2009-60, Department of Economics and Business Economics, Aarhus University.
    7. Gärtner, Kerstin & Podolskij, Mark, 2015. "On non-standard limits of Brownian semi-stationary processes," Stochastic Processes and their Applications, Elsevier, vol. 125(2), pages 653-677.
    8. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2016. "Decoupling the short- and long-term behavior of stochastic volatility," Papers 1610.00332, arXiv.org, revised Jan 2021.
    9. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," Papers 1608.01895, arXiv.org, revised Mar 2018.
    10. Andreas Basse-O'Connor & Mark Podolskij, 2015. "On critical cases in limit theory for stationary increments Lévy driven moving averages," CREATES Research Papers 2015-57, Department of Economics and Business Economics, Aarhus University.
    11. Mark Podolskij & Katrin Wasmuth, 2012. "Goodness-of-fit testing for fractional diffusions," CREATES Research Papers 2012-12, Department of Economics and Business Economics, Aarhus University.
    12. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Multipower Variation for Brownian Semistationary Processes," CREATES Research Papers 2009-21, Department of Economics and Business Economics, Aarhus University.
    13. Andreas Basse-O'Connor & Raphaël Lachièze-Rey & Mark Podolskij, 2015. "Limit theorems for stationary increments Lévy driven moving averages," CREATES Research Papers 2015-56, Department of Economics and Business Economics, Aarhus University.
    14. Eunjeong Choi & Soohwan Cho & Dong Keun Kim, 2020. "Power Demand Forecasting using Long Short-Term Memory (LSTM) Deep-Learning Model for Monitoring Energy Sustainability," Sustainability, MDPI, vol. 12(3), pages 1-14, February.
    15. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2007. "Power variation for Gaussian processes with stationary increments," CREATES Research Papers 2007-42, Department of Economics and Business Economics, Aarhus University.
    16. Mark Podolskij, 2014. "Ambit fields: survey and new challenges," CREATES Research Papers 2014-51, Department of Economics and Business Economics, Aarhus University.
    17. Corcuera, José Manuel & Hedevang, Emil & Pakkanen, Mikko S. & Podolskij, Mark, 2013. "Asymptotic theory for Brownian semi-stationary processes with application to turbulence," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2552-2574.
    18. José León & Carenne Ludeña, 2015. "Difference based estimators and infill statistics," Statistical Inference for Stochastic Processes, Springer, vol. 18(1), pages 1-31, April.
    19. Li, Yuan & Pakkanen, Mikko S. & Veraart, Almut E.D., 2023. "Limit theorems for the realised semicovariances of multivariate Brownian semistationary processes," Stochastic Processes and their Applications, Elsevier, vol. 155(C), pages 202-231.
    20. Robert, Christian Y., 2022. "Testing for changes in the tail behavior of Brown–Resnick Pareto processes," Stochastic Processes and their Applications, Elsevier, vol. 144(C), pages 312-368.
    21. Mikkel Bennedsen & Ulrich Hounyo & Asger Lunde & Mikko S. Pakkanen, 2016. "The Local Fractional Bootstrap," CREATES Research Papers 2016-15, Department of Economics and Business Economics, Aarhus University.
    22. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," CREATES Research Papers 2016-21, Department of Economics and Business Economics, Aarhus University.
    23. Liu, Guangying & Zhang, Xinsheng, 2011. "Power variation of fractional integral processes with jumps," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 962-972, August.
    24. Pakkanen, Mikko S., 2014. "Limit theorems for power variations of ambit fields driven by white noise," Stochastic Processes and their Applications, Elsevier, vol. 124(5), pages 1942-1973.
    25. Mikkel Bennedsen & Ulrich Hounyo & Asger Lunde & Mikko S. Pakkanen, 2016. "The Local Fractional Bootstrap," Papers 1605.00868, arXiv.org, revised Oct 2017.
    26. Bibinger, Markus & Trabs, Mathias, 2020. "Volatility estimation for stochastic PDEs using high-frequency observations," Stochastic Processes and their Applications, Elsevier, vol. 130(5), pages 3005-3052.
    27. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2014. "Discretization of Lévy semistationary processes with application to estimation," CREATES Research Papers 2014-21, Department of Economics and Business Economics, Aarhus University.
    28. Rachid Belfadli & Khalifa Es-Sebaiy & Fatima-Ezzahra Farah, 2023. "Volatility Estimation of Gaussian Ornstein–Uhlenbeck Processes of the Second Kind," Journal of Theoretical Probability, Springer, vol. 36(1), pages 1-17, March.

  15. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Subsampling realised kernels," Economics Papers 2006-W10, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
    2. Eleftheria Kafousaki & Stavros Degiannakis, 2023. "Forecasting VIX: the illusion of forecast evaluation criteria," Economics and Business Letters, Oviedo University Press, vol. 12(3), pages 231-240.
    3. Tae-Hwy Lee & Huiyu Huang, 2014. "Forecasting Value-at-Risk Using High Frequency Information," Working Papers 201409, University of California at Riverside, Department of Economics.
    4. Diebold, Francis X. & Strasser, Georg H., 2008. "On the correlation structure of microstructure noise in theory and practice," CFS Working Paper Series 2008/32, Center for Financial Studies (CFS).
    5. Tae-Hwy Lee & Huiyu Huang, 2014. "Forecasting Realized Volatility Using Subsample Averaging," Working Papers 201410, University of California at Riverside, Department of Economics.
    6. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    7. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
    8. Paolo Gorgi & Siem Jan Koopman, 2020. "Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects," Tinbergen Institute Discussion Papers 20-004/III, Tinbergen Institute.
    9. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    10. Francis X. Diebold & Georg H. Strasser, 2008. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," Boston College Working Papers in Economics 693, Boston College Department of Economics, revised 24 Apr 2012.
    11. Chaker, Selma, 2017. "On high frequency estimation of the frictionless price: The use of observed liquidity variables," Journal of Econometrics, Elsevier, vol. 201(1), pages 127-143.
    12. Linlan Xiao & Vigdis Boasson & Sergey Shishlenin & Victoria Makushina, 2018. "Volatility forecasting: combinations of realized volatility measures and forecasting models," Applied Economics, Taylor & Francis Journals, vol. 50(13), pages 1428-1441, March.
    13. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    14. Nikolaus Hautsch & Dieter Hess & David Veredas, 2011. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," ULB Institutional Repository 2013/136190, ULB -- Universite Libre de Bruxelles.
    15. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    16. Rui Da & Dacheng Xiu, 2021. "When Moving‐Average Models Meet High‐Frequency Data: Uniform Inference on Volatility," Econometrica, Econometric Society, vol. 89(6), pages 2787-2825, November.
    17. Zhang, Lan & Mykland, Per A. & Aït-Sahalia, Yacine, 2011. "Edgeworth expansions for realized volatility and related estimators," Journal of Econometrics, Elsevier, vol. 160(1), pages 190-203, January.
    18. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," Journal of Econometrics, Elsevier, vol. 193(2), pages 367-389.
    19. Vortelinos, Dimitrios I. & Thomakos, Dimitrios D., 2013. "Nonparametric realized volatility estimation in the international equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 34-45.
    20. Mihaela Craioveanu & Eric Hillebrand, 2012. "Why It Is Ok To Use The Har-Rv(1,5,21) Model," Working Papers 1201, University of Central Missouri, Department of Economics & Finance, revised Aug 2012.
    21. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    22. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
    23. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
    24. Jianfen Feng & Xiaowei Huang & Juyue Hou & Chunxia Wang & Yan Zeng, 2018. "Carbon Bond Pricing And Model Selection," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(02), pages 465-481, March.
    25. Konstantinos Gkillas & Dimitrios Vortelinos & Christos Floros & Alexandros Garefalakis & Nikolaos Sariannidis, 2020. "Greek sovereign crisis and European exchange rates: effects of news releases and their providers," Annals of Operations Research, Springer, vol. 294(1), pages 515-536, November.
    26. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
    27. Flavia Barsotti & Simona Sanfelici, 2012. "Microstructure effect on firm’s volatility risk," Working Papers - Mathematical Economics 2012-05, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    28. Zhang, Lan, 2011. "Estimating covariation: Epps effect, microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 33-47, January.
    29. Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.
    30. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    31. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Density Estimators for Daily Volatility Based on the Use of Realized Measures," Departmental Working Papers 200620, Rutgers University, Department of Economics.
    32. Dimitrios I. Vortelinos, 2015. "Out‐of‐sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini‐futures markets," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 58-67, November.
    33. Greeshma Balabhadra & El Mehdi Ainasse & Pawel Polak, 2023. "High-Frequency Volatility Estimation with Fast Multiple Change Points Detection," Papers 2303.10550, arXiv.org, revised Mar 2023.
    34. Prateek Sharma & Swati Sharma, 2015. "Forecasting gains of robust realized variance estimators: evidence from European stock markets," Economics Bulletin, AccessEcon, vol. 35(1), pages 61-69.
    35. Peter Reinhard Hansen & Guillaume Horel, 2009. "Quadratic Variation by Markov Chains," CREATES Research Papers 2009-13, Department of Economics and Business Economics, Aarhus University.
    36. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    37. Rasmus Tangsgaard Varneskov, 2011. "Generalized Flat-Top Realized Kernel Estimation of Ex-Post Variation of Asset Prices Contaminated by Noise," CREATES Research Papers 2011-31, Department of Economics and Business Economics, Aarhus University.
    38. Emilio Barucci & Davide Magno & Maria Elvira Mancino, 2012. "Fourier volatility forecasting with high-frequency data and microstructure noise," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 281-293, September.
    39. Vortelinos, Dimitrios I. & Lakshmi, Geeta, 2015. "Market risk of BRIC Eurobonds in the financial crisis period," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 295-310.
    40. Ikeda, Shin S., 2016. "A bias-corrected estimator of the covariation matrix of multiple security prices when both microstructure effects and sampling durations are persistent and endogenous," Journal of Econometrics, Elsevier, vol. 193(1), pages 203-214.
    41. Wang, Jiazhen & Jiang, Yuexiang & Zhu, Yanjian & Yu, Jing, 2020. "Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 91(C), pages 428-444.

  16. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    2. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
    3. Yuta Koike, 2013. "Limit Theorems for the Pre-averaged Hayashi-Yoshida Estimator with Random Sampling," Global COE Hi-Stat Discussion Paper Series gd12-276, Institute of Economic Research, Hitotsubashi University.
    4. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    5. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
    6. Dette, Holger & Golosnoy, Vasyl & Kellermann, Janosch, 2022. "Correcting Intraday Periodicity Bias in Realized Volatility Measures," Econometrics and Statistics, Elsevier, vol. 23(C), pages 36-52.
    7. Nagapetyan, Artur, 2019. "Precondition stock and stock indices volatility modeling based on market diversification potential: Evidence from Russian market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 56, pages 45-61.
    8. Christensen, Kim & Podolskij, Mark & Vetter, Mathias, 2013. "On covariation estimation for multivariate continuous Itô semimartingales with noise in non-synchronous observation schemes," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 59-84.
    9. Ole E. Barndorff-Nielsen & David G. Pollard & Neil Shephard, 2010. "Integer-valued Lévy processes and low latency financial econometrics," CREATES Research Papers 2010-66, Department of Economics and Business Economics, Aarhus University.
    10. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    11. Bianchi, Francesco & Gómez-Cram, Roberto & Kind, Thilo & Kung, Howard, 2023. "Threats to central bank independence: High-frequency identification with twitter," Journal of Monetary Economics, Elsevier, vol. 135(C), pages 37-54.
    12. Roberto Pascual & David Veredas, 2009. "Does the open limit order book matter in explaining informational volatility?," ULB Institutional Repository 2013/183777, ULB -- Universite Libre de Bruxelles.
    13. Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    14. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
    15. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    16. Donelli, Nicola & Peluso, Stefano & Mira, Antonietta, 2021. "A Bayesian semiparametric vector Multiplicative Error Model," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    17. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," KIER Working Papers 840, Kyoto University, Institute of Economic Research.
    18. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    19. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    20. Chaker, Selma, 2019. "The signal and the noise volatilities," Research in International Business and Finance, Elsevier, vol. 50(C), pages 79-105.
    21. Silja Kinnebrock & Mark Podolskij, 2008. "An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models," CREATES Research Papers 2008-23, Department of Economics and Business Economics, Aarhus University.
    22. Jozef Barunik & Lukas Vacha, 2015. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1347-1364, August.
    23. Heejoon Han & Myung D. Park & Shen Zhang, 2015. "A Multiplicative Error Model with Heterogeneous Components for Forecasting Realized Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 209-219, April.
    24. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
    25. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    26. Koike, Yuta, 2014. "Limit theorems for the pre-averaged Hayashi–Yoshida estimator with random sampling," Stochastic Processes and their Applications, Elsevier, vol. 124(8), pages 2699-2753.
    27. Kalnina, Ilze & Linton, Oliver, 2007. "Inference about realized volatility using infill subsampling," LSE Research Online Documents on Economics 4411, London School of Economics and Political Science, LSE Library.
    28. Massimiliano Caporin & Gabriel G. Velo, 2011. "Modeling and forecasting realized range volatility," "Marco Fanno" Working Papers 0128, Dipartimento di Scienze Economiche "Marco Fanno".
    29. Yun, Jaeho, 2014. "Out-of-sample density forecasts with affine jump diffusion models," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 74-87.
    30. Podolskij, Mark & Vetter, Mathias, 2008. "Bipower-type estimation in a noisy diffusion setting," Technical Reports 2008,24, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    31. Eleftheria Kafousaki & Stavros Degiannakis, 2023. "Forecasting VIX: the illusion of forecast evaluation criteria," Economics and Business Letters, Oviedo University Press, vol. 12(3), pages 231-240.
    32. Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    33. Virgil DAMIAN & Cosmin – Octavian CEPOI, 2016. "Volatility Estimators With High-Frequency Data From Bucharest Stock Exchange," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 247-264.
    34. Altmeyer, Randolf & Bibinger, Markus, 2015. "Functional stable limit theorems for quasi-efficient spectral covolatility estimators," Stochastic Processes and their Applications, Elsevier, vol. 125(12), pages 4556-4600.
    35. Rasmus Tangsgaard Varneskov, 2011. "Flat-Top Realized Kernel Estimation of Quadratic Covariation with Non-Synchronous and Noisy Asset Prices," CREATES Research Papers 2011-35, Department of Economics and Business Economics, Aarhus University.
    36. Markus Bibinger & Lars Winkelmann, 2013. "Econometrics of co-jumps in high-frequency data with noise," SFB 649 Discussion Papers SFB649DP2013-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    37. Dmitry Levando & Maxim Sakharov, 2018. "Natural Instability of Equilibrium Prices," Working Papers 2018:01, Department of Economics, University of Venice "Ca' Foscari".
    38. Richard Y. Chen & Per A. Mykland, 2015. "Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data," Papers 1512.06159, arXiv.org, revised Oct 2018.
    39. Christensen, Kim & Oomen, Roel & Renò, Roberto, 2022. "The drift burst hypothesis," Journal of Econometrics, Elsevier, vol. 227(2), pages 461-497.
    40. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
    41. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    42. Antonio Naimoli & Giuseppe Storti, 2021. "Forecasting Volatility and Tail Risk in Electricity Markets," JRFM, MDPI, vol. 14(7), pages 1-17, June.
    43. Peter C. B. Phillips & Jun Yu, 2009. "Information Loss in Volatility Measurement with Flat Price Trading," Global COE Hi-Stat Discussion Paper Series gd08-039, Institute of Economic Research, Hitotsubashi University.
    44. Wang, Fangfang, 2014. "Optimal design of Fourier estimator in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 708-722.
    45. Almut Veraart & Luitgard Veraart, 2012. "Stochastic volatility and stochastic leverage," Annals of Finance, Springer, vol. 8(2), pages 205-233, May.
    46. Peter R. Hansen & Asger Lunde & Valeri Voev, 2010. "Realized Beta GARCH: A Multivariate GARCH Model with Realized Measures of Volatility and CoVolatility," CREATES Research Papers 2010-74, Department of Economics and Business Economics, Aarhus University.
    47. Cecilia Mancini & Vanessa Mattiussi & Roberto Reno', 2012. "Spot Volatility Estimation Using Delta Sequences," Working Papers - Mathematical Economics 2012-10, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    48. Wang, Jiqian & Lu, Xinjie & He, Feng & Ma, Feng, 2020. "Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    49. Cai, T. Tony & Hu, Jianchang & Li, Yingying & Zheng, Xinghua, 2020. "High-dimensional minimum variance portfolio estimation based on high-frequency data," Journal of Econometrics, Elsevier, vol. 214(2), pages 482-494.
    50. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
    51. Maria Elvira Mancino & Simona Sanfelici, 2011. "Estimation of Quarticity with High Frequency Data," Working Papers - Mathematical Economics 2011-06, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, revised Jan 2012.
    52. Heejoon Han & Myung D. Park, 2013. "Comparison of Realized Measure and Implied Volatility in Forecasting Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 522-533, September.
    53. Daniel Preve, "undated". "Linear programming-based estimators in nonnegative autoregression," GRU Working Paper Series GRU_2016_001, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    54. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
    55. Fleming, Jeff & Paye, Bradley S., 2011. "High-frequency returns, jumps and the mixture of normals hypothesis," Journal of Econometrics, Elsevier, vol. 160(1), pages 119-128, January.
    56. Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
    57. Diego Amaya & Jean-François Bégin & Geneviève Gauthier, 2022. "The Informational Content of High-Frequency Option Prices," Management Science, INFORMS, vol. 68(3), pages 2166-2201, March.
    58. Ding, Hui & Huang, Yisu & Wang, Jiqian, 2023. "Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    59. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    60. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Tinbergen Institute Discussion Papers 14-037/III, Tinbergen Institute.
    61. Renault, Eric & Werker, Bas J.M., 2011. "Causality effects in return volatility measures with random times," Journal of Econometrics, Elsevier, vol. 160(1), pages 272-279, January.
    62. Marcel Aloy & Gilles de Truchis, 2015. "Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems and the Co-persistence Analysis of Stock Market Realized Volatilities," Post-Print hal-01410660, HAL.
    63. Fangfang Wang, 2016. "An Unbiased Measure of Integrated Volatility in the Frequency Domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 147-164, March.
    64. Peter Reinhard Hansen & Zhuo Huang, 2012. "Exponential GARCH Modeling with Realized Measures of Volatility," CREATES Research Papers 2012-44, Department of Economics and Business Economics, Aarhus University.
    65. Andersen, Torben G. & Bollerslev, Tim & Meddahi, Nour, 2011. "Realized volatility forecasting and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 220-234, January.
    66. Jeremy Large, 2007. "Estimating Quadratic Variation When Quoted Prices Change by a Constant Increment," Economics Series Working Papers 340, University of Oxford, Department of Economics.
    67. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
    68. Tae-Hwy Lee & Huiyu Huang, 2014. "Forecasting Value-at-Risk Using High Frequency Information," Working Papers 201409, University of California at Riverside, Department of Economics.
    69. Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    70. Corradi, Valentina & Distaso, Walter & Mele, Antonio, 2013. "Macroeconomic determinants of stock volatility and volatility premiums," Journal of Monetary Economics, Elsevier, vol. 60(2), pages 203-220.
    71. Diebold, Francis X. & Strasser, Georg H., 2008. "On the correlation structure of microstructure noise in theory and practice," CFS Working Paper Series 2008/32, Center for Financial Studies (CFS).
    72. Tae-Hwy Lee & Huiyu Huang, 2014. "Forecasting Realized Volatility Using Subsample Averaging," Working Papers 201410, University of California at Riverside, Department of Economics.
    73. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    74. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    75. He, Lidan & Liu, Qiang & Liu, Zhi, 2020. "Edgeworth corrections for spot volatility estimator," Statistics & Probability Letters, Elsevier, vol. 164(C).
    76. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    77. Markus Bibinger & Markus Reiß, 2011. "Spectral estimation of covolatility from noisy observations using local weights," SFB 649 Discussion Papers SFB649DP2011-086, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    78. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    79. Bekierman Jeremias & Gribisch Bastian, 2016. "Estimating stochastic volatility models using realized measures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 279-300, June.
    80. Ulrich Hounyo & Silvia Gonçalves & Nour Meddahi, 2016. "Bootstrapping pre-averaged realized volatility under market microstructure noise," CIRANO Working Papers 2016s-25, CIRANO.
    81. Sander Barendse & Erik Kole & Dick van Dijk, 2023. "Backtesting Value-at-Risk and Expected Shortfall in the Presence of Estimation Error," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 528-568.
    82. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
    83. Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
    84. Peter Reinhard Hansen & Guillaume Horel & Asger Lunde & Ilya Archakov, 2015. "A Markov Chain Estimator of Multivariate Volatility from High Frequency Data," CREATES Research Papers 2015-19, Department of Economics and Business Economics, Aarhus University.
    85. Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," Economics Series Working Papers 438, University of Oxford, Department of Economics.
    86. Mei, Dexiang & Zhao, Chenchen & Luo, Qin & Li, Yan, 2022. "Forecasting the Chinese low-carbon index volatility," Resources Policy, Elsevier, vol. 77(C).
    87. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    88. Xinghua Zheng & Yingying Li, 2010. "On the estimation of integrated covariance matrices of high dimensional diffusion processes," Papers 1005.1862, arXiv.org, revised Mar 2012.
    89. Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    90. Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Janeway Institute Working Papers 2208, Faculty of Economics, University of Cambridge.
    91. Qi Wang & Jos'e E. Figueroa-L'opez & Todd Kuffner, 2019. "Bayesian Inference on Volatility in the Presence of Infinite Jump Activity and Microstructure Noise," Papers 1909.04853, arXiv.org.
    92. Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    93. Mehmet Balcilar & Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "The Effect of Investor Sentiment on Gold Market Dynamics," Working Papers 201638, University of Pretoria, Department of Economics.
    94. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    95. Kim Christensen & Roel Oomen & Mark Podolskij, 2011. "Fact or friction: Jumps at ultra high frequency," CREATES Research Papers 2011-19, Department of Economics and Business Economics, Aarhus University.
    96. Jorge V. Pérez-Rodríguez, 2020. "Another look at the implied and realised volatility relation: a copula-based approach," Risk Management, Palgrave Macmillan, vol. 22(1), pages 38-64, March.
    97. Yu‐Sheng Lai, 2022. "High‐frequency data and stock–bond investing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1623-1638, December.
    98. Richard Y. Chen, 2018. "Inference for Volatility Functionals of Multivariate It\^o Semimartingales Observed with Jump and Noise," Papers 1810.04725, arXiv.org, revised Nov 2019.
    99. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    100. Misaki, Hiroumi & Kunitomo, Naoto, 2015. "On robust properties of the SIML estimation of volatility under micro-market noise and random sampling," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 265-281.
    101. Liu, Cheng & Tang, Cheng Yong, 2014. "A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data," Journal of Econometrics, Elsevier, vol. 180(2), pages 217-232.
    102. Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
    103. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
    104. Gael M. Martin & Andrew Reidy & Jill Wright, 2006. "Assessing the Impact of Market Microstructure Noise and Random Jumps on the Relative Forecasting Performance of Option-Implied and Returns-Based Volatility," Monash Econometrics and Business Statistics Working Papers 10/06, Monash University, Department of Econometrics and Business Statistics.
    105. Sattarhoff, Cristina & Lux, Thomas, 2023. "Forecasting the variability of stock index returns with the multifractal random walk model for realized volatilities," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1678-1697.
    106. Tim Bollerslev & Jia Li & Yuan Xue, 2016. "Volume, Volatility and Public News Announcements," CREATES Research Papers 2016-19, Department of Economics and Business Economics, Aarhus University.
    107. Francesco Bianchi & Thilo Kind & Howard Kung, 2019. "Threats to Central Bank Independence: High-Frequency Identification with Twitter," NBER Working Papers 26308, National Bureau of Economic Research, Inc.
    108. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    109. Dinghai Xu, 2021. "A study on volatility spurious almost integration effect: A threshold realized GARCH approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4104-4126, July.
    110. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2016. "Decoupling the short- and long-term behavior of stochastic volatility," Papers 1610.00332, arXiv.org, revised Jan 2021.
    111. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2010. "Asymmetry and Long Memory in Volatility Modelling," KIER Working Papers 726, Kyoto University, Institute of Economic Research.
    112. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," Papers 1608.01895, arXiv.org, revised Mar 2018.
    113. Wang Gao & Jiajia Wei & Shixiong Yang, 2023. "The Asymmetric Effects of Extreme Climate Risk Perception on Coal Futures Return Dynamics: Evidence from Nonparametric Causality-In-Quantiles Tests," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    114. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    115. Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
    116. Masato Ubukata & Toshiaki Watanabe, 2014. "Pricing Nikkei 225 Options Using Realized Volatility," The Japanese Economic Review, Japanese Economic Association, vol. 65(4), pages 431-467, December.
    117. Roxana Halbleib & Valeri Voev, 2012. "Forecasting Covariance Matrices: A Mixed Frequency Approach," Working Paper Series of the Department of Economics, University of Konstanz 2012-30, Department of Economics, University of Konstanz.
    118. Nolte, Ingmar & Voev, Valeri, 2007. "Estimating high-frequency based (co-) variances: A unified approach," CoFE Discussion Papers 07/07, University of Konstanz, Center of Finance and Econometrics (CoFE).
    119. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
    120. Vander Elst, Harry & Veredas, David, 2014. "Disentangled jump-robust realized covariances and correlations with non-synchronous prices," DES - Working Papers. Statistics and Econometrics. WS ws142416, Universidad Carlos III de Madrid. Departamento de Estadística.
    121. Ilze Kalnina & Oliver Linton, 2006. "Estimating Quadratic VariationConsistently in thePresence of Correlated MeasurementError," STICERD - Econometrics Paper Series 509, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    122. Varneskov, Rasmus & Voev, Valeri, 2013. "The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 83-95.
    123. Rachidi Kotchoni, 2012. "Applications of the Characteristic Function Based Continuum GMM in Finance," Post-Print hal-00867795, HAL.
    124. Neil Shephard & Ole E. Barndorff-Nielsen & Asger Lunde, 2006. "Subsampling realised kernels," Economics Series Working Papers 278, University of Oxford, Department of Economics.
    125. Mark Podolskij & Mathias Vetter, 2007. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," CREATES Research Papers 2007-27, Department of Economics and Business Economics, Aarhus University.
    126. Mei, Dexiang & Liu, Jing & Ma, Feng & Chen, Wang, 2017. "Forecasting stock market volatility: Do realized skewness and kurtosis help?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 153-159.
    127. Shen, Keren & Yao, Jianfeng & Li, Wai Keung, 2019. "On a spiked model for large volatility matrix estimation from noisy high-frequency data," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 207-221.
    128. Neil Shephard, 2013. "Martingale unobserved component models," Economics Papers 2013-W01, Economics Group, Nuffield College, University of Oxford.
    129. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2014. "Is Volatility Clustering of Asset Returns Asymmetric?," Working Papers 050, Ryerson University, Department of Economics.
    130. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.
    131. Nikolaus Hautsch & Mark Podolskij, 2013. "Preaveraging-Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 165-183, April.
    132. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," Cahiers de recherche 0948, CIRPEE.
    133. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    134. Huiling Yuan & Guodong Li & Junhui Wang, 2022. "High-Frequency-Based Volatility Model with Network Structure," Papers 2204.12933, arXiv.org.
    135. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "Long Memory and Tail dependence in Trading Volume and Volatility," CREATES Research Papers 2009-30, Department of Economics and Business Economics, Aarhus University.
    136. John M. Maheu & Thomas H. McCurdy, 2009. "Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions?," Working Paper series 19_09, Rimini Centre for Economic Analysis.
    137. Hansen, Peter R. & Lunde, Asger, 2014. "Estimating The Persistence And The Autocorrelation Function Of A Time Series That Is Measured With Error," Econometric Theory, Cambridge University Press, vol. 30(1), pages 60-93, February.
    138. Gustavo Fruet Dias & Fotis Papailias & Cristina Scherrer, 2024. "An Econometric Analysis of Volatility Discovery," University of East Anglia School of Economics Working Paper Series 2024-01, School of Economics, University of East Anglia, Norwich, UK..
    139. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk-realised semivariance," Economics Papers 2008-W02, Economics Group, Nuffield College, University of Oxford.
    140. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    141. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
    142. Federico M. Bandi & Roberto Reno, 2009. "Nonparametric Stochastic Volatility," Global COE Hi-Stat Discussion Paper Series gd08-035, Institute of Economic Research, Hitotsubashi University.
    143. Oya, Kosuke, 2011. "Bias-corrected realized variance under dependent microstructure noise," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1290-1298.
    144. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.
    145. Neil Shephard & Dacheng Xiu, 2012. "Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices," Economics Papers 2012-W04, Economics Group, Nuffield College, University of Oxford.
    146. Marine Carrasco & Rachidi Kotchoni, 2015. "Adaptive Realized Kernels," Journal of Financial Econometrics, Oxford University Press, vol. 13(4), pages 757-797.
    147. Dohyun Chun & Donggyu Kim, 2021. "State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data," Papers 2102.13404, arXiv.org.
    148. Taesuk Lee & Mico Loretan & Werner Ploberger, 2013. "Rate-optimal tests for jumps in diffusion processes," Statistical Papers, Springer, vol. 54(4), pages 1009-1041, November.
    149. Yaojie Zhang & Mengxi He & Danyan Wen & Yudong Wang, 2022. "Forecasting Bitcoin volatility: A new insight from the threshold regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 633-652, April.
    150. A. Goubar & A. E. Ades & D. De Angelis & C. A. McGarrigle & C. H. Mercer & P. A. Tookey & K. Fenton & O. N. Gill, 2008. "Estimates of human immunodeficiency virus prevalence and proportion diagnosed based on Bayesian multiparameter synthesis of surveillance data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(3), pages 541-580, June.
    151. Celso Brunetti, Bahattin Buyuksahin, and Jeffrey H. Harris, 2013. "Herding and Speculation in the Crude Oil Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    152. Todorov, Viktor & Bollerslev, Tim, 2010. "Jumps and betas: A new framework for disentangling and estimating systematic risks," Journal of Econometrics, Elsevier, vol. 157(2), pages 220-235, August.
    153. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2007. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," CREATES Research Papers 2007-22, Department of Economics and Business Economics, Aarhus University.
    154. Yao Axel Ehouman, 2020. "Volatility transmission between oil prices and banks’ stock prices as a new source of instability: Lessons from the United States experience," Post-Print hal-02960571, HAL.
    155. Kevin Sheppard & Wen Xu, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    156. Tong, Chen & Huang, Zhuo & Wang, Tianyi & Zhang, Cong, 2023. "The effects of economic uncertainty on financial volatility: A comprehensive investigation," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 369-389.
    157. Alexander Aue & Lajos Horváth & Clifford M. Hurvich & Philippe Soulier, 2014. "Limit Laws in Transaction-Level Asset Price Models," Post-Print hal-00583372, HAL.
    158. Luke De Clerk & Sergey Savel'ev, 2021. "Non-stationary GARCH modelling for fitting higher order moments of financial series within moving time windows," Papers 2102.11627, arXiv.org, revised Mar 2021.
    159. Aït-Sahalia, Yacine & Xiu, Dacheng, 2016. "Increased correlation among asset classes: Are volatility or jumps to blame, or both?," Journal of Econometrics, Elsevier, vol. 194(2), pages 205-219.
    160. Tim Bollerslev & Hao Zhou, 2007. "Expected Stock Returns and Variance Risk Premia," CREATES Research Papers 2007-17, Department of Economics and Business Economics, Aarhus University.
    161. Diep Duong & Norman Swanson, 2013. "Empirical Evidence on the Importance of Aggregation, Asymmetry, and Jumps for Volatility Prediction," Departmental Working Papers 201321, Rutgers University, Department of Economics.
    162. Masato Ubukata & Toshiaki Watanabe, 2011. "Market Variance Risk Premiums in Japan as Predictor Variables and Indicators of Risk Aversion," Global COE Hi-Stat Discussion Paper Series gd11-214, Institute of Economic Research, Hitotsubashi University.
    163. Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2013. "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns," CREATES Research Papers 2013-07, Department of Economics and Business Economics, Aarhus University.
    164. Feng Ma & Chao Liang & Yuanhui Ma & M.I.M. Wahab, 2020. "Cryptocurrency volatility forecasting: A Markov regime‐switching MIDAS approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1277-1290, December.
    165. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Economics Papers 2008-W10, Economics Group, Nuffield College, University of Oxford.
    166. Chao Liang & Yongan Xu & Zhonglu Chen & Xiafei Li, 2023. "Forecasting China's stock market volatility with shrinkage method: Can Adaptive Lasso select stronger predictors from numerous predictors?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3689-3699, October.
    167. Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
    168. Li, M. Z. & Linton, O., 2021. "Robust Estimation of Integrated and Spot Volatility," Cambridge Working Papers in Economics 2115, Faculty of Economics, University of Cambridge.
    169. P Gorgi & P R Hansen & P Janus & S J Koopman, 2019. "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 1-32.
    170. Sergii Pypko, 2015. "Volatility Forecast in Crises and Expansions," JRFM, MDPI, vol. 8(3), pages 1-26, August.
    171. Manh Cuong Dong & Cathy W. S. Chen & Manabu Asai, 2023. "Bayesian non‐linear quantile effects on modelling realized kernels," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 981-995, January.
    172. Kim Christensen & Mark Podolskij & Mathias Vetter, 2009. "Bias-correcting the realized range-based variance in the presence of market microstructure noise," Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
    173. Manabu Asai & Chia-Lin Chang & Michael McAleer, 2016. "Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers," Documentos de Trabajo del ICAE 2016-15, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    174. L. Scaffidi Domianello & G.M. Gallo & E. Otranto, 2022. "Smooth and Abrupt Dynamics in Financial Volatility: the MS-MEM-MIDAS," Working Paper CRENoS 202205, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    175. Wu, Xinyu & Xie, Haibin, 2021. "A realized EGARCH-MIDAS model with higher moments," Finance Research Letters, Elsevier, vol. 38(C).
    176. Dong, Yingjie & Tse, Yiu-Kuen, 2017. "On estimating market microstructure noise variance," Economics Letters, Elsevier, vol. 150(C), pages 59-62.
    177. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
    178. Kevin Sheppard & Wen Xu, 2019. "Factor High-Frequency-Based Volatility (HEAVY) Models," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 33-65.
    179. Francis X. Diebold & Georg H. Strasser, 2008. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," Boston College Working Papers in Economics 693, Boston College Department of Economics, revised 24 Apr 2012.
    180. Chaker, Selma, 2017. "On high frequency estimation of the frictionless price: The use of observed liquidity variables," Journal of Econometrics, Elsevier, vol. 201(1), pages 127-143.
    181. Joshua C C Chan & Yong Song, 2017. "Measuring inflation expectations uncertainty using high-frequency data," CAMA Working Papers 2017-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    182. Dimitrios I. Vortelinos, 2015. "The Effect of Macro News on Volatility and Jumps," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 425-447, November.
    183. Jim Griffin & Jia Liu & John M. Maheu, 2021. "Bayesian Nonparametric Estimation of Ex Post Variance [Out of Sample Forecasts of Quadratic Variation]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 823-859.
    184. Hanousek, Jan & Novotný, Jan, 2012. "Price jumps in Visegrad-country stock markets: An empirical analysis," Emerging Markets Review, Elsevier, vol. 13(2), pages 184-201.
    185. Xin Zhang & Donggyu Kim & Yazhen Wang, 2016. "Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets," Econometrics, MDPI, vol. 4(3), pages 1-26, August.
    186. Ding, Y., 2021. "Augmented Real-Time GARCH: A Joint Model for Returns, Volatility and Volatility of Volatility," Cambridge Working Papers in Economics 2112, Faculty of Economics, University of Cambridge.
    187. Bollerslev, Tim & Meddahi, Nour & Nyawa, Serge, 2019. "High-dimensional multivariate realized volatility estimation," Journal of Econometrics, Elsevier, vol. 212(1), pages 116-136.
    188. Christensen, Kim & Kinnebrock, Silja & Podolskij, Mark, 2010. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," Journal of Econometrics, Elsevier, vol. 159(1), pages 116-133, November.
    189. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    190. Chen Tong & Zhuo Huang, 2021. "Pricing VIX options with realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(8), pages 1180-1200, August.
    191. Liao, Yin & Anderson, Heather M., 2019. "Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
    192. Manabu Asai & Shelton Peiris & Michael McAleer, 2017. "Realized Stochastic Volatility Models with Generalized Gegenbauer Long Memory," Documentos de Trabajo del ICAE 2017-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    193. Balcilar, Mehmet & Bonato, Matteo & Demirer, Riza & Gupta, Rangan, 2017. "The effect of investor sentiment on gold market return dynamics: Evidence from a nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 51(C), pages 77-84.
    194. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    195. Massimiliano Caporin & Michael McAleer, 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," Working Papers in Economics 10/58, University of Canterbury, Department of Economics and Finance.
    196. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2017. "Realized stochastic volatility with general asymmetry and long memory," Journal of Econometrics, Elsevier, vol. 199(2), pages 202-212.
    197. Zhuo Huang & Chen Tong & Tianyi Wang, 2019. "VIX term structure and VIX futures pricing with realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 72-93, January.
    198. Johanna F. Ziegel & Fabian Kruger & Alexander Jordan & Fernando Fasciati, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Papers 1705.04537, arXiv.org.
    199. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    200. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    201. Demetrio Lacava & Giampiero M. Gallo & Edoardo Otranto, 2020. "Unconventional Policies Effects on Stock Market Volatility: A MAP Approach," Papers 2010.08259, arXiv.org, revised Mar 2021.
    202. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    203. Matthieu Garcin & Clément Goulet, 2015. "Non-parameteric news impact curve: a variational approach," Documents de travail du Centre d'Economie de la Sorbonne 15086r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jul 2016.
    204. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2012. "International market links and volatility transmission," Journal of Econometrics, Elsevier, vol. 170(1), pages 117-141.
    205. Kim, Donggyu & Wang, Yazhen, 2016. "Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financial data," Journal of Econometrics, Elsevier, vol. 194(2), pages 220-230.
    206. Lars Stentoft, 2008. "Option Pricing using Realized Volatility," CREATES Research Papers 2008-13, Department of Economics and Business Economics, Aarhus University.
    207. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
    208. Per Mykland, 2012. "A Gaussian calculus for inference from high frequency data," Annals of Finance, Springer, vol. 8(2), pages 235-258, May.
    209. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.
    210. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2014. "A Robust Neighborhood Truncation Approach To Estimation Of Integrated Quarticity," Econometric Theory, Cambridge University Press, vol. 30(1), pages 3-59, February.
    211. Naoto Kunitomo & Hiroumi Misaki, 2013. "The SIML Estimation of Integrated Covariance and Hedging Coefficient under Micro-market noise and Random Sampling," CIRJE F-Series CIRJE-F-893, CIRJE, Faculty of Economics, University of Tokyo.
    212. Cedric Okou & Eric Jacquier, 2014. "Horizon Effect in the Term Structure of Long-Run Risk-Return Trade-Offs," CIRANO Working Papers 2014s-36, CIRANO.
    213. Corsi, Fulvio & Kretschmer, Uta & Mittnik, Stefan & Pigorsch, Christian, 2005. "The volatility of realized volatility," CFS Working Paper Series 2005/33, Center for Financial Studies (CFS).
    214. Ilze Kalnina & Natalia Sizova, 2015. "Estimation of volatility measures using high frequency data (in Russian)," Quantile, Quantile, issue 13, pages 3-14, May.
    215. Bonato, Matteo & Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian, 2018. "Gold futures returns and realized moments: A forecasting experiment using a quantile-boosting approach," Resources Policy, Elsevier, vol. 57(C), pages 196-212.
    216. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    217. Nikolaus Hautsch & Stefan Voigt, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty," Papers 1709.06296, arXiv.org, revised Jun 2018.
    218. Naoto Kunitomo & Hiroumi Misaki & Seisho Sato, 2015. "The SIML Estimation of Integrated Covariance and Hedging Coefficient Under Round-off Errors, Micro-market Price Adjustments and Random Sampling," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 22(3), pages 333-368, September.
    219. Demetrio Lacava & Luca Scaffidi Domianello, 2021. "The Incidence of Spillover Effects during the Unconventional Monetary Policies Era," JRFM, MDPI, vol. 14(6), pages 1-18, May.
    220. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    221. Tim Bollerslev & Natalia Sizova & George Tauchen, 2009. "Volatility in Equilibrium: Asymmetries and Dynamic Dependencies," Working Papers 10-73, Duke University, Department of Economics.
    222. Naoto Kunitomo & Seisho Sato, 2010. "Robustness of the Separating Information Maximum Likelihood Estimation of Realized Volatility with Micro-Market Noise," CIRJE F-Series CIRJE-F-733, CIRJE, Faculty of Economics, University of Tokyo.
    223. Adam E Clements & Christopher A Coleman-Fenn & Daniel R Smith, 2011. "Forecasting Equicorrelation," NCER Working Paper Series 72, National Centre for Econometric Research, revised 29 Aug 2011.
    224. Jacod, Jean & Li, Yingying & Zheng, Xinghua, 2019. "Estimating the integrated volatility with tick observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 80-100.
    225. Michael McAleer & Marcelo C. Medeiros, 2009. "Forecasting Realized Volatility with Linear and Nonlinear Models," CARF F-Series CARF-F-189, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    226. Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Indirect inference with time series observed with error," CREATES Research Papers 2014-57, Department of Economics and Business Economics, Aarhus University.
    227. Lidan Grossmass, 2014. "Obtaining and Predicting the Bounds of Realized Correlations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(III), pages 191-226, September.
    228. Tommaso Mariotti & Fabrizio Lillo & Giacomo Toscano, 2022. "From Zero-Intelligence to Queue-Reactive: Limit Order Book modeling for high-frequency volatility estimation and optimal execution," Papers 2202.12137, arXiv.org, revised Sep 2022.
    229. Jacod, Jean & Li, Yingying & Mykland, Per A. & Podolskij, Mark & Vetter, Mathias, 2007. "Microstructure noise in the continuous case: the pre-averaging approach," Technical Reports 2007,41, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    230. LAURENT, Sébastien & VIOLANTE, Francesco, 2012. "Volatility forecasts evaluation and comparison," LIDAM Reprints CORE 2414, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    231. Jim Gatheral & Roel Oomen, 2010. "Zero-intelligence realized variance estimation," Finance and Stochastics, Springer, vol. 14(2), pages 249-283, April.
    232. Kim, Donggyu & Kong, Xin-Bing & Li, Cui-Xia & Wang, Yazhen, 2018. "Adaptive thresholding for large volatility matrix estimation based on high-frequency financial data," Journal of Econometrics, Elsevier, vol. 203(1), pages 69-79.
    233. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    234. Chen Tong & Peter Reinhard Hansen & Zhuo Huang, 2021. "Option Pricing with State-dependent Pricing Kernel," Papers 2112.05308, arXiv.org, revised Apr 2022.
    235. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting," MPRA Paper 35252, University Library of Munich, Germany.
    236. Madalina-Gabriela Anghel & Constantin Anghelache & Stefan Virgil Iacob, 2022. "Theoretical Elements Regarding The Management Of A Dynamic Portfolio," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 91-96, February.
    237. Selma Chaker & Nour Meddahi, 2013. "A Distributional Approach to Realized Volatility," Staff Working Papers 13-49, Bank of Canada.
    238. E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2011. "Modeling microstructure noise with mutually exciting point processes," Papers 1101.3422, arXiv.org.
    239. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    240. Fu, Jin-Yu & Lin, Jin-Guan & Hao, Hong-Xia, 2023. "Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1698-1712.
    241. Jia Li & Dacheng Xiu, 2016. "Generalized Method of Integrated Moments for High‐Frequency Data," Econometrica, Econometric Society, vol. 84, pages 1613-1633, July.
    242. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    243. Yingying Li & Zhiyuan Zhang & Xinghua Zheng, 2013. "Volatility Inference in the Presence of Both Endogenous Time and Microstructure Noise," Papers 1303.5809, arXiv.org.
    244. Hanousek Jan & Kočenda Evžen & Novotný Jan, 2012. "The identification of price jumps," Monte Carlo Methods and Applications, De Gruyter, vol. 18(1), pages 53-77, January.
    245. Kunitomo, Naoto & Sato, Seisho, 2011. "The SIML estimation of realized volatility of the Nikkei-225 Futures and hedging coefficient with micro-market noise," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1272-1289.
    246. Adam D. Bull, 2013. "Estimating time-changes in noisy L\'evy models," Papers 1312.5911, arXiv.org, revised Nov 2014.
    247. Hao Liu & Shihan Shen & Tianyi Wang & Zhuo Huang, 2016. "Revisiting the risk-return relation in the Chinese stock market: Decomposition of risk premium and volatility feedback effect," China Economic Journal, Taylor & Francis Journals, vol. 9(2), pages 140-153, May.
    248. Chao Liang & Yan Li & Feng Ma & Yaojie Zhang, 2022. "Forecasting international equity market volatility: A new approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1433-1457, November.
    249. Barunik, Jozef & Barunikova, Michaela, 2015. "Revisiting the long memory dynamics of implied-realized volatility relation: A new evidence from wavelet band spectrum regression," FinMaP-Working Papers 43, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    250. Venter, J.H. & de Jongh, P.J., 2014. "Extended stochastic volatility models incorporating realised measures," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 687-707.
    251. Almut E. D. Veraart, 2010. "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?," CREATES Research Papers 2010-65, Department of Economics and Business Economics, Aarhus University.
    252. Cathy W.S. Chen & Toshiaki Watanabe, 2019. "Bayesian modeling and forecasting of Value‐at‐Risk via threshold realized volatility," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(3), pages 747-765, May.
    253. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    254. Becker, Janis & Leschinski, Christian, 2018. "The Bias of Realized Volatility," Hannover Economic Papers (HEP) dp-642, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    255. Mark Podolskij & Bezirgen Veliyev & Nakahiro Yoshida, 2015. "Edgeworth expansion for the pre-averaging estimator," CREATES Research Papers 2015-60, Department of Economics and Business Economics, Aarhus University.
    256. Gustavo Fruet Dias & Cristina M. Scherrer & Fotis Papailias, 2016. "Volatility Discovery," CREATES Research Papers 2016-07, Department of Economics and Business Economics, Aarhus University.
    257. Okou, Cédric & Jacquier, Éric, 2016. "Horizon effect in the term structure of long-run risk-return trade-offs," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 445-466.
    258. Markus Reiss, 2010. "Asymptotic equivalence and sufficiency for volatility estimation under microstructure noise," Papers 1001.3006, arXiv.org.
    259. Ngo Hoang-Long & Ogawa Shigeyoshi, 2009. "A central limit theorem for the functional estimation of the spot volatility," Monte Carlo Methods and Applications, De Gruyter, vol. 15(4), pages 353-380, January.
    260. Bee, Marco & Dupuis, Debbie J. & Trapin, Luca, 2016. "Realizing the extremes: Estimation of tail-risk measures from a high-frequency perspective," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 86-99.
    261. Masazumi Hattori & Andreas Schrimpf & Vladyslav Sushko, 2016. "The Response of Tail Risk Perceptions to Unconventional Monetary Policy," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(2), pages 111-136, April.
    262. Hiroumi Misaki & Naoto Kunitomo, 2013. "On Robust Properties of the SIML Estimation of Volatility under Micro-market noise and Random Sampling," CIRJE F-Series CIRJE-F-892, CIRJE, Faculty of Economics, University of Tokyo.
    263. Bekierman, Jeremias & Manner, Hans, 2018. "Forecasting realized variance measures using time-varying coefficient models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 276-287.
    264. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    265. Manabu Asai, 2013. "Heterogeneous Asymmetric Dynamic Conditional Correlation Model with Stock Return and Range," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 469-480, August.
    266. Ostap Okhrin & Anastasija Tetereva, 2017. "The Realized Hierarchical Archimedean Copula in Risk Modelling," Econometrics, MDPI, vol. 5(2), pages 1-31, June.
    267. Wilson Ye Chen & Richard H. Gerlach, 2017. "Semiparametric GARCH via Bayesian model averaging," Papers 1708.07587, arXiv.org.
    268. Yves Dominicy & Harry-Paul Vander Elst, 2015. "Macro-Driven VaR Forecasts: From Very High to Very Low Frequency Data," Working Papers ECARES ECARES 2015-41, ULB -- Universite Libre de Bruxelles.
    269. Torben G. Andersen & Oleg Bondarenko, 2007. "Construction and Interpretation of Model-Free Implied Volatility," NBER Working Papers 13449, National Bureau of Economic Research, Inc.
    270. Donggyu Kim & Minseog Oh & Yazhen Wang, 2022. "Conditional quantile analysis for realized GARCH models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 640-665, July.
    271. Naoto Kunitomo & Seisho Sato, 2008. "Separating Information Maximum Likelihood Estimation of Realized Volatility and Covariance with Micro-Market Noise," CIRJE F-Series CIRJE-F-581, CIRJE, Faculty of Economics, University of Tokyo.
    272. Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 94289, University Library of Munich, Germany.
    273. Shirota, Shinichiro & Hizu, Takayuki & Omori, Yasuhiro, 2014. "Realized stochastic volatility with leverage and long memory," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 618-641.
    274. Silja Kinnebrock & Mark Podolskij, 2007. "A Note on the Central Limit Theorem for Bipower Variation of General Functions," OFRC Working Papers Series 2007fe03, Oxford Financial Research Centre.
    275. Allen, David E. & McAleer, Michael & Scharth, Marcel, 2011. "Monte Carlo option pricing with asymmetric realized volatility dynamics," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1247-1256.
    276. G.M. Gallo & D. Lacava & E. Otranto, 2020. "Measuring the Effects of Unconventional Policies on Stock Market Volatility," Working Paper CRENoS 202006, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    277. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised Sep 2023.
    278. Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).
    279. Fan, Jianqing & Kim, Donggyu, 2019. "Structured volatility matrix estimation for non-synchronized high-frequency financial data," Journal of Econometrics, Elsevier, vol. 209(1), pages 61-78.
    280. Patton, Andrew J. & Sheppard, Kevin, 2009. "Optimal combinations of realised volatility estimators," International Journal of Forecasting, Elsevier, vol. 25(2), pages 218-238.
    281. Xu, Dinghai, 2022. "Canadian stock market volatility under COVID-19," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 159-169.
    282. Ilze Kalnina, 2023. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 538-549, April.
    283. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    284. Yao Axel Ehouman, 2019. "Volatility transmission between oil prices and banks stock prices as a new source of instability: Lessons from the US Experience," EconomiX Working Papers 2019-19, University of Paris Nanterre, EconomiX.
    285. Vica Tendenan & Richard Gerlach & Chao Wang, 2020. "Tail risk forecasting using Bayesian realized EGARCH models," Papers 2008.05147, arXiv.org, revised Aug 2020.
    286. Mihaela Craioveanu & Eric Hillebrand, 2012. "Level changes in volatility models," Annals of Finance, Springer, vol. 8(2), pages 277-308, May.
    287. Hiroyuki Kawakatsu, 2021. "Information in daily data volatility measurements," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1642-1656, April.
    288. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    289. Masato Ubukata, 2010. "Large-scale portfolios using realized covariance matrix: evidence from the Japanese stock market," Economics Bulletin, AccessEcon, vol. 30(4), pages 2906-2919.
    290. Anine E. Bolko & Kim Christensen & Mikko S. Pakkanen & Bezirgen Veliyev, 2020. "A GMM approach to estimate the roughness of stochastic volatility," Papers 2010.04610, arXiv.org, revised Apr 2022.
    291. Wenjing Wang & Minjing Tao, 2020. "Forecasting Realized Volatility Matrix With Copula-Based Models," Papers 2002.08849, arXiv.org.
    292. Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024. "Doubly multiplicative error models with long- and short-run components," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    293. Shin S. Ikeda, 2013. "A Note on the Mixingale Limit Theorem by McLeish (1977)," GRIPS Discussion Papers 13-11, National Graduate Institute for Policy Studies.
    294. Guido Russi, 2012. "Estimating the Leverage Effect Using High Frequency Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 1-24, February.
    295. Zu, Yang & Boswijk, H. Peter, 2017. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 53-75.
    296. Ehouman, Yao Axel, 2020. "Volatility transmission between oil prices and banks' stock prices as a new source of instability: Lessons from the United States experience," Economic Modelling, Elsevier, vol. 91(C), pages 198-217.
    297. Rui Da & Dacheng Xiu, 2021. "When Moving‐Average Models Meet High‐Frequency Data: Uniform Inference on Volatility," Econometrica, Econometric Society, vol. 89(6), pages 2787-2825, November.
    298. Yacine Aït-Sahalia & Jean Jacod, 2010. "Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data," NBER Working Papers 15808, National Bureau of Economic Research, Inc.
    299. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2019. "Realized variance modeling: decoupling forecasting from estimation," Econometrics Working Papers Archive 2019_05, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    300. Manabu Asai, 2023. "Estimation of Realized Asymmetric Stochastic Volatility Models Using Kalman Filter," Econometrics, MDPI, vol. 11(3), pages 1-14, July.
    301. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    302. Gustavo F. Dias & Marcelo Fernandes & Cristina M. Scherrer, 2021. "Price Discovery in a Continuous-Time Setting [Price Discovery and Common Factor Models]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 985-1008.
    303. Selma Chaker, 2013. "Volatility and Liquidity Costs," Staff Working Papers 13-29, Bank of Canada.
    304. Zu, Y., 2015. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Working Papers 15/02, Department of Economics, City University London.
    305. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    306. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    307. Pedersen, Lasse Heje & Bollerslev, Tim & Hood, Benjamin & Huss, John, 2018. "Risk Everywhere: Modeling and Managing Volatility," CEPR Discussion Papers 12687, C.E.P.R. Discussion Papers.
    308. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    309. Liang-Ching Lin & Sangyeol Lee & Meihui Guo, 2014. "The Bickel–Rosenblatt test for continuous time stochastic volatility models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 195-218, March.
    310. Donggyu Kim, 2016. "Statistical Inference for Unified Garch–Itô Models with High-Frequency Financial Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 513-532, July.
    311. Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.
    312. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
    313. Chao Liang & Yi Zhang & Yaojie Zhang, 2022. "Forecasting the volatility of the German stock market: New evidence," Applied Economics, Taylor & Francis Journals, vol. 54(9), pages 1055-1070, February.
    314. Zhang, Lan & Mykland, Per A. & Aït-Sahalia, Yacine, 2011. "Edgeworth expansions for realized volatility and related estimators," Journal of Econometrics, Elsevier, vol. 160(1), pages 190-203, January.
    315. Mădălina-Gabriela ANGHEL & Ștefan Virgil IACOB & Gabriel-Ștefan DUMBRAVĂ & Marius POPOVICI, 2019. "Dynamic models used in analysis capital and population," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(621), W), pages 149-162, Winter.
    316. Dimpfl, Thomas & Schweikert, Karsten, 2023. "Information shares for markets with partially overlapping trading hours," Journal of Banking & Finance, Elsevier, vol. 154(C).
    317. Simon Clinet & Yoann Potiron, 2021. "Estimation for high-frequency data under parametric market microstructure noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
    318. Tim Bollerslev & Viktor Todorov, 2011. "Estimation of Jump Tails," Econometrica, Econometric Society, vol. 79(6), pages 1727-1783, November.
    319. Bollerslev, Tim & Osterrieder, Daniela & Sizova, Natalia & Tauchen, George, 2013. "Risk and return: Long-run relations, fractional cointegration, and return predictability," Journal of Financial Economics, Elsevier, vol. 108(2), pages 409-424.
    320. Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
    321. Huang, Zhuo & Liu, Hao & Wang, Tianyi, 2016. "Modeling long memory volatility using realized measures of volatility: A realized HAR GARCH model," Economic Modelling, Elsevier, vol. 52(PB), pages 812-821.
    322. Vetter, Mathias, 2014. "Inference on the Lévy measure in case of noisy observations," Statistics & Probability Letters, Elsevier, vol. 87(C), pages 125-133.
    323. Li, Z. Merrick & Laeven, Roger J.A. & Vellekoop, Michel H., 2020. "Dependent microstructure noise and integrated volatility estimation from high-frequency data," Journal of Econometrics, Elsevier, vol. 215(2), pages 536-558.
    324. Zhi Liu, 2017. "Jump-robust estimation of volatility with simultaneous presence of microstructure noise and multiple observations," Finance and Stochastics, Springer, vol. 21(2), pages 427-469, April.
    325. Kalnina, Ilze & Linton, Oliver, 2006. "Estimating quadratic variation consistently in the presence of correlated measurement error," LSE Research Online Documents on Economics 4413, London School of Economics and Political Science, LSE Library.
    326. Deniz Erdemlioglu & Sebastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    327. E. Otranto, 2012. "Spillover Effects in the Volatility of Financial Markets," Working Paper CRENoS 201217, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    328. Xie, Haibin & Yu, Chengtan, 2020. "Realized GARCH models: Simpler is better," Finance Research Letters, Elsevier, vol. 33(C).
    329. Taro Kanatani, 2007. "Finite Sample Analysis of Weighted Realized Covariance with Noisy Asynchronous Observations," KIER Working Papers 634, Kyoto University, Institute of Economic Research.
    330. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    331. Rosenbaum, Mathieu & Tankov, Peter, 2011. "Asymptotic results for time-changed Lévy processes sampled at hitting times," Stochastic Processes and their Applications, Elsevier, vol. 121(7), pages 1607-1632, July.
    332. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    333. Ghysels, Eric, 2014. "Factor Analysis with Large Panels of Volatility Proxies," CEPR Discussion Papers 10034, C.E.P.R. Discussion Papers.
    334. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.
    335. Asuka Takeuchi-Nogimori, 2012. "An Empirical Analysis of the Nikkei 225 Put Options Using Realized GARCH Models," Global COE Hi-Stat Discussion Paper Series gd12-241, Institute of Economic Research, Hitotsubashi University.
    336. Seisho Sato & Naoto Kunitomo, 2015. "A Robust Estimation of Integrated Volatility under Round-off Errors, Micro-market Price Adjustments and Noises," CIRJE F-Series CIRJE-F-964, CIRJE, Faculty of Economics, University of Tokyo.
    337. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.
    338. Hautsch, Nikolaus & Okhrin, Ostap & Ristig, Alexander, 2014. "Efficient iterative maximum likelihood estimation of high-parameterized time series models," CFS Working Paper Series 450, Center for Financial Studies (CFS).
    339. Jiawen Luo & Qun Zhang, 2024. "Air pollution, weather factors, and realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 151-217, February.
    340. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, Department of Economics and Business Economics, Aarhus University.
    341. Jihyun Kim & Nour Meddahi, 2020. "Volatility Regressions with Fat Tails," Post-Print hal-03142647, HAL.
    342. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    343. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018.
    344. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
    345. Julien Chevallier, 2020. "COVID-19 Pandemic and Financial Contagion," JRFM, MDPI, vol. 13(12), pages 1-25, December.
    346. Todorova, Neda & Souček, Michael, 2014. "Overnight information flow and realized volatility forecasting," Finance Research Letters, Elsevier, vol. 11(4), pages 420-428.
    347. Christensen, Kim & Thyrsgaard, Martin & Veliyev, Bezirgen, 2019. "The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing," Journal of Econometrics, Elsevier, vol. 212(2), pages 556-583.
    348. Wei Wei & Denis Pelletier, 2015. "A Jump-Diffusion Model with Stochastic Volatility and Durations," CREATES Research Papers 2015-34, Department of Economics and Business Economics, Aarhus University.
    349. Liu, Min & Lee, Chien-Chiang, 2021. "Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting," Energy Economics, Elsevier, vol. 103(C).
    350. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2011. "The Merit of High-Frequency Data in Portfolio Allocation," SFB 649 Discussion Papers SFB649DP2011-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    351. Naoto Kunitomo & Seisho Sato, 2010. "On Properties of Separating Information Maximum Likelihood Estimation of Realized Volatility and Covariance with Micro-Market Noise," CIRJE F-Series CIRJE-F-758, CIRJE, Faculty of Economics, University of Tokyo.
    352. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    353. Kim, Donggyu & Wang, Yazhen & Zou, Jian, 2016. "Asymptotic theory for large volatility matrix estimation based on high-frequency financial data," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3527-3577.
    354. Vít Bubák & Filip Žikeš, 2009. "Distribution and Dynamics of Central-European Exchange Rates: Evidence from Intraday Data," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(4), pages 334-359, Oktober.
    355. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    356. Ole E. Barndorff-Nielsen & David G. Pollard & Neil Shephard, 2010. "Discrete-valued Levy processes and low latency financial econometrics," Economics Papers 2010-W04, Economics Group, Nuffield College, University of Oxford.
    357. Peter Christensen, 2024. "Roughness Signature Functions," Papers 2401.02819, arXiv.org.
    358. Schmidt, Anatoly B., 2009. "Detrending the realized volatility in the global FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(9), pages 1887-1892.
    359. Ysusi Carla, 2007. "Multipower Variation Under Market Microstructure Effects," Working Papers 2007-13, Banco de México.
    360. Tao, Minjing & Wang, Yahzen & Yao, Qiwei & Zou, Jian, 2011. "Large volatility matrix inference via combining low-frequency and high-frequency approaches," LSE Research Online Documents on Economics 39321, London School of Economics and Political Science, LSE Library.
    361. Hansen, Peter Reinhard & Dumitrescu, Elena-Ivona, 2022. "How should parameter estimation be tailored to the objective?," Journal of Econometrics, Elsevier, vol. 230(2), pages 535-558.
    362. Cartea, Álvaro & Karyampas, Dimitrios, 2009. "The relationship between the volatility of returns and the number of jumps in financial markets," DEE - Working Papers. Business Economics. WB wb097508, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    363. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
    364. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
    365. Malec, Peter & Schienle, Melanie, 2014. "Nonparametric kernel density estimation near the boundary," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 57-76.
    366. Vortelinos, Dimitrios I. & Thomakos, Dimitrios D., 2013. "Nonparametric realized volatility estimation in the international equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 34-45.
    367. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2015. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-979, CIRJE, Faculty of Economics, University of Tokyo.
    368. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
    369. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
    370. Bibinger, Markus, 2012. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," Stochastic Processes and their Applications, Elsevier, vol. 122(6), pages 2411-2453.
    371. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.
    372. Yacine Ait-Sahalia & Jianqing Fan & Yingying Li, 2011. "The Leverage Effect Puzzle: Disentangling Sources of Bias at High Frequency," NBER Working Papers 17592, National Bureau of Economic Research, Inc.
    373. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
    374. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
    375. Dohyun Chun & Donggyu Kim, 2022. "State Heterogeneity Analysis of Financial Volatility using high‐frequency Financial Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 105-124, January.
    376. Donggyu Kim, 2021. "Exponential GARCH-Ito Volatility Models," Papers 2111.04267, arXiv.org.
    377. Li, Yingying & Xie, Shangyu & Zheng, Xinghua, 2016. "Efficient estimation of integrated volatility incorporating trading information," Journal of Econometrics, Elsevier, vol. 195(1), pages 33-50.
    378. Yacine Ait-Sahalia & Per A. Mykland & Lan Zhang, 2005. "Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise," NBER Working Papers 11380, National Bureau of Economic Research, Inc.
    379. Haugom, Erik & Lien, Gudbrand & Veka, Steinar & Westgaard, Sjur, 2014. "Covariance estimation using high-frequency data: Sensitivities of estimation methods," Economic Modelling, Elsevier, vol. 43(C), pages 416-425.
    380. Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.
    381. Donggyu Kim & Minseog Oh, 2023. "Dynamic Realized Minimum Variance Portfolio Models," Papers 2310.13511, arXiv.org.
    382. Dovonon, Prosper & Gonçalves, Sílvia & Meddahi, Nour, 2013. "Bootstrapping realized multivariate volatility measures," Journal of Econometrics, Elsevier, vol. 172(1), pages 49-65.
    383. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    384. Jean Jacod & Mark Podolskij & Mathias Vetter, 2008. "Intertemporal Asset Allocation with Habit Formation in Preferences: An Approximate Analytical Solution," CREATES Research Papers 2008-61, Department of Economics and Business Economics, Aarhus University.
    385. Avouyi-Dovi, S. & Idier, J., 2010. "Central bank liquidity and market liquidity: the role of collateral provision on the French government debt securities market," Working papers 278, Banque de France.
    386. Anine E. Bolko & Kim Christensen & Mikko S. Pakkanen & Bezirgen Veliyev, 2020. "Roughness in spot variance? A GMM approach for estimation of fractional log-normal stochastic volatility models using realized measures," CREATES Research Papers 2020-12, Department of Economics and Business Economics, Aarhus University.
    387. Constantin Anghelache & Madalina-Gabriela Anghel & Stefan Virgil Iacob, 2021. "Statistical-Econometric Methods For Risk Diversification," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 5, pages 157-163, October.
    388. Julien Chevallier, 2020. "COVID-19 Outbreak and CO 2 Emissions: Macro-Financial Linkages," JRFM, MDPI, vol. 14(1), pages 1-18, December.
    389. Baltussen, Guido & Da, Zhi & Lammers, Sten & Martens, Martin, 2021. "Hedging demand and market intraday momentum," Journal of Financial Economics, Elsevier, vol. 142(1), pages 377-403.
    390. Kalnina, Ilze, 2011. "Subsampling high frequency data," Journal of Econometrics, Elsevier, vol. 161(2), pages 262-283, April.
    391. Silvia Goncalves & Nour Meddahi, 2008. "Edgeworth Corrections for Realized Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 139-162.
    392. Kunitomo, Naoto & Sato, Seisho, 2013. "Separating Information Maximum Likelihood estimation of the integrated volatility and covariance with micro-market noise," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 282-309.
    393. Maria Elvira Mancino & Tommaso Mariotti & Giacomo Toscano, 2022. "Asymptotic Normality for the Fourier spot volatility estimator in the presence of microstructure noise," Papers 2209.08967, arXiv.org.
    394. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    395. Bacry, E. & Delattre, S. & Hoffmann, M. & Muzy, J.F., 2013. "Some limit theorems for Hawkes processes and application to financial statistics," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2475-2499.
    396. Chen, Richard Y. & Mykland, Per A., 2017. "Model-free approaches to discern non-stationary microstructure noise and time-varying liquidity in high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 79-103.
    397. Großmaß Lidan, 2014. "Liquidity and the Value at Risk," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(5), pages 572-602, October.
    398. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    399. Markus Bibinger & Mathias Vetter, 2015. "Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 707-743, August.
    400. Song, Xinyu & Kim, Donggyu & Yuan, Huiling & Cui, Xiangyu & Lu, Zhiping & Zhou, Yong & Wang, Yazhen, 2021. "Volatility analysis with realized GARCH-Itô models," Journal of Econometrics, Elsevier, vol. 222(1), pages 393-410.
    401. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    402. Donggyu Kim & Xinyu Song & Yazhen Wang, 2020. "Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency," Papers 2006.12039, arXiv.org.
    403. Damien Challet & Vincent Ragel, 2023. "Recurrent Neural Networks with more flexible memory: better predictions than rough volatility," Papers 2308.08550, arXiv.org.
    404. Duan, Yinying & Chen, Wang & Zeng, Qing & Liu, Zhicao, 2018. "Leverage effect, economic policy uncertainty and realized volatility with regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 148-154.
    405. Martin, Vance L. & Tang, Chrismin & Yao, Wenying, 2021. "Forecasting the volatility of asset returns: The informational gains from option prices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 862-880.
    406. M. Podolskij & D. Ziggel, 2010. "New tests for jumps in semimartingale models," Statistical Inference for Stochastic Processes, Springer, vol. 13(1), pages 15-41, April.
    407. Chen, Cathy W.S. & Hsu, Hsiao-Yun & Watanabe, Toshiaki, 2023. "Tail risk forecasting of realized volatility CAViaR models," Finance Research Letters, Elsevier, vol. 51(C).
    408. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    409. Minseog Oh & Donggyu Kim, 2021. "Effect of the U.S.--China Trade War on Stock Markets: A Financial Contagion Perspective," Papers 2111.09655, arXiv.org.
    410. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    411. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Wang, Jianqiong, 2020. "Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models," Energy, Elsevier, vol. 212(C).
    412. Shuichi Nagata, 2012. "Consistent Estimation of Integrated Volatility Using Intraday Absolute Returns for SV Jump Diffusion Processes," Economics Bulletin, AccessEcon, vol. 32(1), pages 306-314.
    413. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2021. "Bayesian estimation for a semiparametric nonlinear volatility model," Economic Modelling, Elsevier, vol. 98(C), pages 361-370.
    414. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    415. Li, Yingying & Zhang, Zhiyuan & Zheng, Xinghua, 2013. "Volatility inference in the presence of both endogenous time and microstructure noise," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2696-2727.
    416. Z. Merrick Li & Oliver Linton, 2022. "A ReMeDI for Microstructure Noise," Econometrica, Econometric Society, vol. 90(1), pages 367-389, January.
    417. Li, Yingying & Zhang, Zhiyuan & Li, Yichu, 2018. "A unified approach to volatility estimation in the presence of both rounding and random market microstructure noise," Journal of Econometrics, Elsevier, vol. 203(2), pages 187-222.
    418. Pérez-Rodríguez, Jorge V. & Andrada-Félix, Julián & Rachinger, Heiko, 2021. "Testing the forward volatility unbiasedness hypothesis in exchange rates under long-range dependence," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    419. Chow, Ying-Foon & Lam, James T.K. & Yeung, Hinson S., 2009. "Realized volatility of index constituent stocks in Hong Kong," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2809-2818.
    420. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
    421. Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
    422. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
    423. Markus Bibinger & Per A. Mykland, 2016. "Inference for Multi-dimensional High-frequency Data with an Application to Conditional Independence Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1078-1102, December.
    424. Sutton, Maxwell & Vasnev, Andrey L. & Gerlach, Richard, 2019. "Mixed interval realized variance: A robust estimator of stock price volatility," Econometrics and Statistics, Elsevier, vol. 11(C), pages 43-62.
    425. LAURENT, Sébastien & ROMBOUTS, Jeroen V. K. & VIOLANTE, Francesco, 2010. "On the forecasting accuracy of multivariate GARCH models," LIDAM Discussion Papers CORE 2010025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    426. Bolko, Anine E. & Christensen, Kim & Pakkanen, Mikko S. & Veliyev, Bezirgen, 2023. "A GMM approach to estimate the roughness of stochastic volatility," Journal of Econometrics, Elsevier, vol. 235(2), pages 745-778.
    427. Masato Ubukata & Toshiaki Watanabe, 2014. "Market variance risk premiums in Japan for asset predictability," Empirical Economics, Springer, vol. 47(1), pages 169-198, August.
    428. Almut E. D. Veraart, 2008. "Impact of time–inhomogeneous jumps and leverage type effects on returns and realised variances," CREATES Research Papers 2008-57, Department of Economics and Business Economics, Aarhus University.
    429. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    430. Ying Chen & Wolfgang Härdle & Uta Pigorsch, 2009. "Localized Realized Volatility Modelling," SFB 649 Discussion Papers SFB649DP2009-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    431. Ahoniemi, Katja & Lanne, Markku, 2010. "Realized volatility and overnight returns," Bank of Finland Research Discussion Papers 19/2010, Bank of Finland.
    432. Tong, Yuan & Wan, Ning & Dai, Xingyu & Bi, Xiaoyi & Wang, Qunwei, 2022. "China's energy stock market jumps: To what extent does the COVID-19 pandemic play a part?," Energy Economics, Elsevier, vol. 109(C).
    433. Ruijun Bu & Degui Li & Oliver Linton & Hanchao Wang, 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Working Papers 202212, University of Liverpool, Department of Economics.
    434. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    435. Giorgio Mirone, 2017. "Inference from the futures: ranking the noise cancelling accuracy of realized measures," CREATES Research Papers 2017-24, Department of Economics and Business Economics, Aarhus University.
    436. Giorgio Mirone, 2018. "Cross-sectional noise reduction and more efficient estimation of Integrated Variance," CREATES Research Papers 2018-18, Department of Economics and Business Economics, Aarhus University.
    437. Sattarhoff, Cristina & Lux, Thomas, 2021. "Forecasting the Variability of Stock Index Returns with the Multifractal Random Walk Model for Realized Volatilities," Economics Working Papers 2021-02, Christian-Albrechts-University of Kiel, Department of Economics.
    438. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    439. Chao YU & Xujie ZHAO, 2021. "Measuring the Jump Risk Contribution under Market Microstructure Noise – Evidence from Chinese Stock Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 32-47, December.
    440. Ulrich Hounyo, 2013. "Bootstrapping realized volatility and realized beta under a local Gaussianity assumption," CREATES Research Papers 2013-30, Department of Economics and Business Economics, Aarhus University.
    441. Habib Hasnaoui, 2014. "Alternative Beta Risk Estimators in Emerging Markets: The Case of Tunisia," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 2(2), pages 96-105.
    442. Xie, Haibin & Qi, Nan & Wang, Shouyang, 2019. "A new variant of RealGARCH for volatility modeling," Finance Research Letters, Elsevier, vol. 28(C), pages 438-443.
    443. Wu, Fan & Wang, Guan-jun & Kong, Xin-bing, 2022. "Inference on common intraday periodicity at high frequencies," Statistics & Probability Letters, Elsevier, vol. 191(C).
    444. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2011. "A Functional Filtering and Neighborhood Truncation Approach to Integrated Quarticity Estimation," NBER Working Papers 17152, National Bureau of Economic Research, Inc.
    445. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    446. Giampiero M. Gallo & Edoardo Otranto, 2016. "Combining Markov Switching and Smooth Transition in Modeling Volatility: A Fuzzy Regime MEM," Econometrics Working Papers Archive 2016_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    447. Liu, Cheng & Wang, Moming & Xia, Ningning, 2022. "Design-free estimation of integrated covariance matrices for high-frequency data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    448. Behrendt, Simon & Schweikert, Karsten, 2021. "A Note on Adaptive Group Lasso for Structural Break Time Series," Econometrics and Statistics, Elsevier, vol. 17(C), pages 156-172.
    449. Wang, Chengyang & Nishiyama, Yoshihiko, 2015. "Volatility forecast of stock indices by model averaging using high-frequency data," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 324-337.
    450. Markus Bibinger & Lars Winkelmann, 2014. "Common price and volatility jumps in noisy high-frequency data," SFB 649 Discussion Papers SFB649DP2014-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    451. Heejoon Han & Shen Zhang, 2012. "Non‐stationary non‐parametric volatility model," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 204-225, June.
    452. Likun Lei & Yaojie Zhang & Yu Wei & Yi Zhang, 2021. "Forecasting the volatility of Chinese stock market: An international volatility index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1336-1350, January.
    453. Neil Shephard & Torben G. Andersen, 2008. "Stochastic Volatility: Origins and Overview," OFRC Working Papers Series 2008fe23, Oxford Financial Research Centre.
    454. Su, Fei & Wang, Xinyi & Yuan, Yulin, 2022. "The intraday dynamics and intraday price discovery of bitcoin," Research in International Business and Finance, Elsevier, vol. 60(C).
    455. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    456. Bent Jesper Christensen & Mads Markvart Kjær & Bezirgen Veliyev, 2021. "The incremental information in the yield curve about future interest rate risk," CREATES Research Papers 2021-11, Department of Economics and Business Economics, Aarhus University.
    457. Yu, Honghai & Fang, Libing & Sun, Wencong, 2018. "Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 931-940.
    458. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2021. "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Discussion paper series HIAS-E-104, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    459. Mykland, Per A. & Zhang, Lan & Chen, Dachuan, 2019. "The algebra of two scales estimation, and the S-TSRV: High frequency estimation that is robust to sampling times," Journal of Econometrics, Elsevier, vol. 208(1), pages 101-119.
    460. Bandi, Federico M. & Russell, Jeffrey R., 2011. "Market microstructure noise, integrated variance estimators, and the accuracy of asymptotic approximations," Journal of Econometrics, Elsevier, vol. 160(1), pages 145-159, January.
    461. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
    462. Taylor, Nick, 2017. "Realised variance forecasting under Box-Cox transformations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 770-785.
    463. Siem Jan Koopman & Marcel Scharth, 2011. "The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures," Tinbergen Institute Discussion Papers 11-132/4, Tinbergen Institute.
    464. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
    465. Todorova, Neda & Worthington, Andrew & Souček, Michael, 2014. "Realized volatility spillovers in the non-ferrous metal futures market," Resources Policy, Elsevier, vol. 39(C), pages 21-31.
    466. Christophe Boucher & Gilles de Truchis & Elena Ivona Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," Working Papers hal-04141651, HAL.
    467. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    468. Li, Shaoyu & Zheng, Tingguo, 2017. "Modeling spot rate using a realized stochastic volatility model with level effect and dynamic drift☆," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 200-221.
    469. Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
    470. Liu, Min, 2022. "The driving forces of green bond market volatility and the response of the market to the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 288-309.
    471. Zu, Yang & Peter Boswijk, H., 2014. "Estimating spot volatility with high-frequency financial data," Journal of Econometrics, Elsevier, vol. 181(2), pages 117-135.
    472. Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
    473. Cathy W. S. Chen & Edward M. H. Lin & Tara F. J. Huang, 2022. "Bayesian quantile forecasting via the realized hysteretic GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1317-1337, November.
    474. Chai, Edwina F.L. & Lee, Adrian D. & Wang, Jianxin, 2015. "Global information distribution in the gold OTC markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 206-217.
    475. Park, Sujin & Hong, Seok Young & Linton, Oliver, 2016. "Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error," Journal of Econometrics, Elsevier, vol. 191(2), pages 325-347.
    476. PASCUAL, Roberto & VEREDAS, David, 2006. "Does the open limit order book matter in explaining long run volatility ?," LIDAM Discussion Papers CORE 2006110, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    477. Vladimír Holý & Petra Tomanová, 2023. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 463-485, June.
    478. Flavia Barsotti & Simona Sanfelici, 2012. "Microstructure effect on firm’s volatility risk," Working Papers - Mathematical Economics 2012-05, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    479. Mikkel Bennedsen & Ulrich Hounyo & Asger Lunde & Mikko S. Pakkanen, 2016. "The Local Fractional Bootstrap," CREATES Research Papers 2016-15, Department of Economics and Business Economics, Aarhus University.
    480. Shcherba, Alexandr, 2014. "Comparing «Realized volatility» models in the VaR calculation for the Russian equity market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 34(2), pages 120-136.
    481. Naoto Kunitomo & Hiroumi Misaki & Seisho Sato, 2015. "The SIML Estimation of Integrated Covariance and Hedging Coefficient under Round-off Errors, Micro-market Price Adjustments and Random Sampling," CIRJE F-Series CIRJE-F-965, CIRJE, Faculty of Economics, University of Tokyo.
    482. Zhang, Lan, 2011. "Estimating covariation: Epps effect, microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 33-47, January.
    483. T. -N. Nguyen & M. -N. Tran & R. Kohn, 2020. "Recurrent Conditional Heteroskedasticity," Papers 2010.13061, arXiv.org, revised Jan 2022.
    484. Shephard, Neil & Xiu, Dacheng, 2017. "Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading," Journal of Econometrics, Elsevier, vol. 201(1), pages 19-42.
    485. Markus Bibinger & Markus Reiß, 2014. "Spectral Estimation of Covolatility from Noisy Observations Using Local Weights," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 23-50, March.
    486. Donggyu Kim & Minseok Shin, 2023. "Volatility models for stylized facts of high‐frequency financial data," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(3), pages 262-279, May.
    487. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    488. Jean Jacod & Yingying Li & Per A. Mykland & Mark Podolskij & Mathias Vetter, 2007. "Microstructure Noise in the Continuous Case: The Pre-Averaging Approach - JLMPV-9," CREATES Research Papers 2007-43, Department of Economics and Business Economics, Aarhus University.
    489. Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.
    490. Christophe Boucher & Gilles de Truchis & Elena Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," EconomiX Working Papers 2017-20, University of Paris Nanterre, EconomiX.
    491. M. Karanasos & S. Yfanti & J. Hunter, 2022. "Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises," Annals of Operations Research, Springer, vol. 313(2), pages 1077-1116, June.
    492. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," CREATES Research Papers 2016-21, Department of Economics and Business Economics, Aarhus University.
    493. Enrique Sentana, 2018. "Volatility, Diversification and Contagion," Working Papers wp2018_1803, CEMFI.
    494. Giampiero M. Gallo & Edoardo Otranto, 2012. "Volatility Swings in the US Financial Markets," Econometrics Working Papers Archive 2012_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    495. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    496. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    497. Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
    498. Neil Shephard & Kevin Sheppard, 2012. "Efficient and feasible inference for the components of financial variation using blocked multipower variation," Economics Series Working Papers 593, University of Oxford, Department of Economics.
    499. Victor Bello Accioly & Beatriz Vaz de Melo Mendes, 2016. "Assessing the Impact of the Realized Range on the (E)GARCH Volatility: Evidence from Brazil," Brazilian Business Review, Fucape Business School, vol. 13(2), pages 1-26, March.
    500. Ji, Qiang & Bouri, Elie & Kristoufek, Ladislav & Lucey, Brian, 2021. "Realised volatility connectedness among Bitcoin exchange markets," Finance Research Letters, Elsevier, vol. 38(C).
    501. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 29-56, Winter.
    502. Wu, Xinyu & Wang, Xiaona, 2020. "Forecasting volatility using realized stochastic volatility model with time-varying leverage effect," Finance Research Letters, Elsevier, vol. 34(C).
    503. Andersen, Torben G. & Archakov, Ilya & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2022. "Local mispricing and microstructural noise: A parametric perspective," Journal of Econometrics, Elsevier, vol. 230(2), pages 510-534.
    504. Yuan, Ying & Zhang, Tonghui, 2020. "Forecasting stock market in high and low volatility periods: a modified multifractal volatility approach," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    505. Thomakos, Dimitrios D. & Wang, Tao, 2010. "'Optimal' probabilistic and directional predictions of financial returns," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 102-119, January.
    506. Tobias Fissler & Mark Podolskij, 2014. "Testing the maximal rank of the volatility process for continuous diffusions observed with noise," CREATES Research Papers 2014-52, Department of Economics and Business Economics, Aarhus University.
    507. Pellatt , Daniel & Sun, Yixiao, 2020. "Asymptotic F test in Regressions with Observations Collected at High Frequency over Long Span," University of California at San Diego, Economics Working Paper Series qt19f0d9wz, Department of Economics, UC San Diego.
    508. Qiang Liu & Zhi Liu & Chuanhai Zhang, 2020. "Heteroscedasticity test of high-frequency data with jumps and microstructure noise," Papers 2010.07659, arXiv.org.
    509. Selma Chaker & Nour Meddahi, 2013. "Volatility Forecasting when the Noise Variance Is Time-Varying," Staff Working Papers 13-48, Bank of Canada.
    510. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Density Estimators for Daily Volatility Based on the Use of Realized Measures," Departmental Working Papers 200620, Rutgers University, Department of Economics.
    511. Jin-Huei Yeh & Jying-Nan Wang & Chung-Ming Kuan, 2014. "A noise-robust estimator of volatility based on interquantile ranges," Review of Quantitative Finance and Accounting, Springer, vol. 43(4), pages 751-779, November.
    512. Jos'e E. Figueroa-L'opez & Bei Wu, 2020. "Kernel Estimation of Spot Volatility with Microstructure Noise Using Pre-Averaging," Papers 2004.01865, arXiv.org, revised Feb 2022.
    513. Cathy W. S. Chen & Takaaki Koike & Wei-Hsuan Shau, 2024. "Tail risk forecasting with semi-parametric regression models by incorporating overnight information," Papers 2402.07134, arXiv.org.
    514. Kosuke Oya, 2009. "Bias-Corrected Realized Variance under Dependent Microstructure Noise," Discussion Papers in Economics and Business 09-39, Osaka University, Graduate School of Economics.
    515. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    516. Yu, Chao & Fang, Yue & Zhao, Xujie & Zhang, Bo, 2013. "Kernel filtering of spot volatility in presence of Lévy jumps and market microstructure noise," MPRA Paper 63293, University Library of Munich, Germany, revised 10 Mar 2014.
    517. Luwen Zhang & Li Wang, 2023. "Generalized Method of Moments Estimation of Realized Stochastic Volatility Model," JRFM, MDPI, vol. 16(8), pages 1-12, August.
    518. Yao Axel Ehouman, 2019. "Volatility transmission between oil prices and banks stock prices as a new source of instability: Lessons from the US Experience," Working Papers hal-04141868, HAL.
    519. Lyócsa, Štefan & Todorova, Neda, 2021. "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, vol. 100(C).
    520. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    521. Dimitrios I. Vortelinos, 2015. "Out‐of‐sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini‐futures markets," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 58-67, November.
    522. Greeshma Balabhadra & El Mehdi Ainasse & Pawel Polak, 2023. "High-Frequency Volatility Estimation with Fast Multiple Change Points Detection," Papers 2303.10550, arXiv.org, revised Mar 2023.
    523. Matthieu Garcin, 2019. "Fractal analysis of the multifractality of foreign exchange rates [Analyse fractale de la multifractalité des taux de change]," Working Papers hal-02283915, HAL.
    524. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    525. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    526. Halbleib, Roxana & Dimitriadis, Timo, 2019. "How informative is high-frequency data for tail risk estimation and forecasting? An intrinsic time perspectice," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203669, Verein für Socialpolitik / German Economic Association.
    527. Pierre Chausse & Dinghai Xu, 2012. "GMM Estimation of a Stochastic Volatility Model with Realized Volatility: A Monte Carlo Study," Working Papers 1203, University of Waterloo, Department of Economics, revised May 2012.
    528. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    529. Prateek Sharma & Swati Sharma, 2015. "Forecasting gains of robust realized variance estimators: evidence from European stock markets," Economics Bulletin, AccessEcon, vol. 35(1), pages 61-69.
    530. Jean Jacod, 2019. "Estimation of volatility in a high-frequency setting: a short review," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 351-385, December.
    531. E. Otranto, 2024. "A Vector Multiplicative Error Model with Spillover Effects and Co-movements," Working Paper CRENoS 202404, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    532. Wu, Liuren, 2011. "Variance dynamics: Joint evidence from options and high-frequency returns," Journal of Econometrics, Elsevier, vol. 160(1), pages 280-287, January.
    533. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2014. "Realized volatility models and alternative Value-at-Risk prediction strategies," Economic Modelling, Elsevier, vol. 40(C), pages 101-116.
    534. CHEN, Cathy W.S. & WENG, Monica M.C. & WATANABE, Toshiaki & 渡部, 渡部, 2015. "Employing Bayesian Forecasting of Value-at-Risk to Determine an Appropriate Model for Risk Management," Discussion paper series HIAS-E-16, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    535. Masato Ubukata & Toshiaki Watanabe, 2011. "Pricing Nikkei 225 Options Using Realized Volatility," IMES Discussion Paper Series 11-E-18, Institute for Monetary and Economic Studies, Bank of Japan.
    536. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    537. Zhang, Hongwei & Demirer, Riza & Huang, Jianbai & Huang, Wanjun & Tahir Suleman, Muhammad, 2021. "Economic policy uncertainty and gold return dynamics: Evidence from high-frequency data," Resources Policy, Elsevier, vol. 72(C).
    538. Peter Reinhard Hansen & Zhuo Huang & Chen Tong & Tianyi Wang, 2021. "Realized GARCH, CBOE VIX, and the Volatility Risk Premium," Papers 2112.05302, arXiv.org.
    539. Wang Pu & Yixiang Chen & Feng Ma, 2016. "Forecasting the realized volatility in the Chinese stock market: further evidence," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3116-3130, July.
    540. Li, Yingying & Liu, Guangying & Zhang, Zhiyuan, 2022. "Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps," Journal of Econometrics, Elsevier, vol. 229(2), pages 422-451.
    541. Caporin, Massimiliano & Velo, Gabriel G., 2015. "Realized range volatility forecasting: Dynamic features and predictive variables," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 98-112.
    542. Kim, Donggyu & Song, Xinyu & Wang, Yazhen, 2022. "Unified discrete-time factor stochastic volatility and continuous-time Itô models for combining inference based on low-frequency and high-frequency," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    543. Jiang, Wei & Ruan, Qingsong & Li, Jianfeng & Li, Ye, 2018. "Modeling returns volatility: Realized GARCH incorporating realized risk measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 249-258.
    544. Markus Bibinger & Mathias Vetter, 2013. "Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps," SFB 649 Discussion Papers SFB649DP2013-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    545. Neil Shephard & Silja Kinnebrock & Ole E. Barndorff-Neilsen, 2008. "Measuring downside risk - realised semivariance," Economics Series Working Papers 382, University of Oxford, Department of Economics.
    546. Adamantios Ntakaris & Giorgio Mirone & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Feature Engineering for Mid-Price Prediction with Deep Learning," Papers 1904.05384, arXiv.org, revised Jun 2019.
    547. Naoto Kunitomo & Seisho Sato, 2008. "Realized Volatility, Covariance and Hedging Coefficient of the Nikkei-225 Futures with Micro-Market Noise," CIRJE F-Series CIRJE-F-601, CIRJE, Faculty of Economics, University of Tokyo.
    548. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    549. Chen, Cathy W.S. & Watanabe, Toshiaki & Lin, Edward M.H., 2023. "Bayesian estimation of realized GARCH-type models with application to financial tail risk management," Econometrics and Statistics, Elsevier, vol. 28(C), pages 30-46.
    550. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
    551. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    552. Jacod, Jean & Mykland, Per A., 2015. "Microstructure noise in the continuous case: Approximate efficiency of the adaptive pre-averaging method," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2910-2936.
    553. Donggyu Kim & Minseok Shin & Yazhen Wang, 2021. "Overnight GARCH-It\^o Volatility Models," Papers 2102.13467, arXiv.org, revised Jun 2022.
    554. Yinfen Tang & Tao Su & Zhiyuan Zhang, 2022. "Distribution-free specification test for volatility function based on high-frequency data with microstructure noise," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(8), pages 977-1022, November.
    555. Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
    556. Jozef Barunik & Michaela Barunikova, 2012. "Revisiting the fractional cointegrating dynamics of implied-realized volatility relation with wavelet band spectrum regression," Papers 1208.4831, arXiv.org, revised Feb 2013.
    557. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    558. Markus Bibinger & Per A. Mykland, 2013. "Inference for Multi-Dimensional High-Frequency Data: Equivalence of Methods, Central Limit Theorems, and an Application to Conditional Independence Testing," SFB 649 Discussion Papers SFB649DP2013-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    559. Ping, Yuan & Li, Rui, 2018. "Forecasting realized volatility based on the truncated two-scales realized volatility estimator (TTSRV): Evidence from China's stock market," Finance Research Letters, Elsevier, vol. 25(C), pages 222-229.
    560. Zhang, Congshan & Li, Jia & Bollerslev, Tim, 2022. "Occupation density estimation for noisy high-frequency data," Journal of Econometrics, Elsevier, vol. 227(1), pages 189-211.
    561. Tian, Shuairu & Hamori, Shigeyuki, 2015. "Modeling interest rate volatility: A Realized GARCH approach," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 158-171.
    562. Ciciretti, Vito & Bucci, Andrea, 2023. "Building optimal regime-switching portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    563. Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
    564. Martin, Vance L. & Tang, Chrismin & Yao, Wenying, 2018. "News and expected returns in East Asian equity markets: The RV-GARCHM model," Journal of Asian Economics, Elsevier, vol. 57(C), pages 36-52.
    565. Kim Christensen & Roel Oomen & Roberto Renò, 2018. "The drift burst hypothesis," CREATES Research Papers 2018-21, Department of Economics and Business Economics, Aarhus University.
    566. Maria Elvira Mancino & Maria Cristina Recchioni, 2015. "Fourier Spot Volatility Estimator: Asymptotic Normality and Efficiency with Liquid and Illiquid High-Frequency Data," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-33, September.
    567. Chao Liang & Yu Wei & Yaojie Zhang, 2020. "Is implied volatility more informative for forecasting realized volatility: An international perspective," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1253-1276, December.
    568. Kim Christensen & Roel Oomen & Roberto Renò, 2016. "The Drift Burst Hypothesis," CREATES Research Papers 2016-28, Department of Economics and Business Economics, Aarhus University.
    569. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility Regressions with Fat Tails," TSE Working Papers 20-1097, Toulouse School of Economics (TSE).
    570. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
    571. Giampiero M. Gallo & Edoardo Otranto, 2012. "Realized Volatility and Change of Regimes," Econometrics Working Papers Archive 2012_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    572. Ting Ting Chen & Tetsuya Takaishi, 2013. "Empirical Study of the GARCH model with Rational Errors," Papers 1312.7057, arXiv.org.
    573. Aït-Sahalia, Yacine & Jacod, Jean & Li, Jia, 2012. "Testing for jumps in noisy high frequency data," Journal of Econometrics, Elsevier, vol. 168(2), pages 207-222.
    574. Matthieu Garcin & Clément Goulet, 2015. "Non-parameteric news impact curve: a variational approach," Documents de travail du Centre d'Economie de la Sorbonne 15086rr, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Feb 2017.
    575. Tong Fang & Deyu Miao & Zhi Su & Libo Yin, 2023. "Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 872-904, July.
    576. Naoto Kunitomo & Seisho Sato, 2010. "On Properties of Separating Information Maximum Likelihood Estimation of Realized Volatility and Covariance with Micro-Market Noise," CARF F-Series CARF-F-228, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    577. Sujin Park & Oliver Linton, 2012. "Estimating the Quadratic Covariation Matrix for an Asynchronously Observed Continuous Time Signal Masked by Additive Noise," FMG Discussion Papers dp703, Financial Markets Group.
    578. Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    579. E. Otranto, 2015. "Adding Flexibility to Markov Switching Models," Working Paper CRENoS 201509, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    580. Qiang Liu & Zhi Liu, 2022. "Estimating spot volatility under infinite variation jumps with dependent market microstructure noise," Papers 2205.15738, arXiv.org, revised Feb 2023.
    581. Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020. "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 1-12.
    582. Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
    583. Kong, Xin-Bing & Liu, Cheng, 2018. "Testing against constant factor loading matrix with large panel high-frequency data," Journal of Econometrics, Elsevier, vol. 204(2), pages 301-319.
    584. Ikeda, Shin S., 2016. "A bias-corrected estimator of the covariation matrix of multiple security prices when both microstructure effects and sampling durations are persistent and endogenous," Journal of Econometrics, Elsevier, vol. 193(1), pages 203-214.
    585. Curato, Imma Valentina & Mancino, Maria Elvira & Recchioni, Maria Cristina, 2018. "Spot volatility estimation using the Laplace transform," Econometrics and Statistics, Elsevier, vol. 6(C), pages 22-43.
    586. Xin-Bing Kong, 2017. "On the number of common factors with high-frequency data," Biometrika, Biometrika Trust, vol. 104(2), pages 397-410.
    587. Curato, Imma Valentina, 2019. "Estimation of the stochastic leverage effect using the Fourier transform method," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3207-3238.
    588. Liang, Chao & Li, Yan & Ma, Feng & Wei, Yu, 2021. "Global equity market volatilities forecasting: A comparison of leverage effects, jumps, and overnight information," International Review of Financial Analysis, Elsevier, vol. 75(C).
    589. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    590. Markus Bibinger & Moritz Jirak & Markus Reiss, 2014. "Improved Volatility Estimation Based On Limit Order Books," SFB 649 Discussion Papers SFB649DP2014-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    591. E. Otranto, 2011. "Classification of Volatility in Presence of Changes in Model Parameters," Working Paper CRENoS 201113, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    592. Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
    593. Qiao, Gaoxiu & Jiang, Gongyue & Yang, Jiyu, 2022. "VIX term structure forecasting: New evidence based on the realized semi-variances," International Review of Financial Analysis, Elsevier, vol. 82(C).
    594. Masato Ubukata & Kosuke Oya, 2008. "A Test for Dependence and Covariance Estimator of Market Microstructure Noise," Discussion Papers in Economics and Business 07-03-Rev.2, Osaka University, Graduate School of Economics.
    595. Chen Liu & Chao Wang & Minh-Ngoc Tran & Robert Kohn, 2023. "Deep Learning Enhanced Realized GARCH," Papers 2302.08002, arXiv.org, revised Oct 2023.
    596. Roland Füss & Ferdinand Mager & Michael Stein & Lu Zhao, 2018. "Financial crises, price discovery, and information transmission: a high-frequency perspective," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(4), pages 333-365, November.
    597. Jan Novotn?? & Jan Hanousek & Ev??en Ko??enda, 2013. "Price Jump Indicators: Stock Market Empirics During the Crisis," William Davidson Institute Working Papers Series wp1050, William Davidson Institute at the University of Michigan.
    598. Qu, Hui & Li, Guo, 2023. "Multi-perspective investor attention and oil futures volatility forecasting," Energy Economics, Elsevier, vol. 119(C).
    599. Didit Budi Nugroho & Takayuki Morimoto, 2019. "Incorporating Realized Quarticity into a Realized Stochastic Volatility Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(4), pages 495-528, December.
    600. Wu, Xinyu & Zhao, An & Liu, Li, 2023. "Forecasting VIX using two-component realized EGARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    601. Chao Liang & Yu Wei & Likun Lei & Feng Ma, 2022. "Global equity market volatility forecasting: New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 594-609, January.
    602. Flavia Barsotti & Simona Sanfelici, 2016. "Market Microstructure Effects on Firm Default Risk Evaluation," Econometrics, MDPI, vol. 4(3), pages 1-31, July.
    603. Mikkel Bennedsen & Ulrich Hounyo & Asger Lunde & Mikko S. Pakkanen, 2016. "The Local Fractional Bootstrap," Papers 1605.00868, arXiv.org, revised Oct 2017.
    604. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    605. Su, Fei & Zhang, Jingjing, 2018. "Global price discovery in the Australian dollar market and its determinants," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 35-55.
    606. Bachmair, K., 2023. "The Effects of the LIBOR Scandal on Volatility and Liquidity in LIBOR Futures Markets," Cambridge Working Papers in Economics 2303, Faculty of Economics, University of Cambridge.
    607. Wang, Jiazhen & Jiang, Yuexiang & Zhu, Yanjian & Yu, Jing, 2020. "Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 91(C), pages 428-444.
    608. Yingjie Dong & Yiu-Kuen Tse, 2017. "Business Time Sampling Scheme with Applications to Testing Semi-Martingale Hypothesis and Estimating Integrated Volatility," Econometrics, MDPI, vol. 5(4), pages 1-19, November.
    609. Giulia Livieri & Maria Elvira Mancino & Stefano Marmi, 2019. "Asymptotic results for the Fourier estimator of the integrated quarticity," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 471-502, December.
    610. Antoine Bouveret & Martin Haferkorn & Gaetano Marseglia & Onofrio Panzarino, 2022. "Flash crashes on sovereign bond markets – EU evidence," Mercati, infrastrutture, sistemi di pagamento (Markets, Infrastructures, Payment Systems) 20, Bank of Italy, Directorate General for Markets and Payment System.
    611. Randolf Altmeyer & Markus Bibinger, 2014. "Functional stable limit theorems for efficient spectral covolatility estimators," SFB 649 Discussion Papers SFB649DP2014-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    612. Wang, Lu & Zhao, Chenchen & Liang, Chao & Jiu, Song, 2022. "Predicting the volatility of China's new energy stock market: Deep insight from the realized EGARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 48(C).
    613. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
    614. Minxian Yang, 2014. "The Risk Return Relationship: Evidence from Index Return and Realised Variance Series," Discussion Papers 2014-16, School of Economics, The University of New South Wales.
    615. Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017. "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, vol. 67(C), pages 136-145.
    616. Eric Hillebrand & Marcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
    617. Jos'e E. Figueroa-L'opez & Cheng Li, 2016. "Optimal Kernel Estimation of Spot Volatility of Stochastic Differential Equations," Papers 1612.04507, arXiv.org.
    618. Vladim'ir Hol'y & Petra Tomanov'a, 2018. "Estimation of Ornstein-Uhlenbeck Process Using Ultra-High-Frequency Data with Application to Intraday Pairs Trading Strategy," Papers 1811.09312, arXiv.org, revised Jul 2022.
    619. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
    620. Jonathan Haynes & Daniel Schmitt & Lukas Grimm, 2019. "Estimating stochastic volatility: the rough side to equity returns," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 449-469, December.
    621. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.
    622. Yang, Minxian, 2019. "The risk return relationship: Evidence from index returns and realised variances," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.

  17. Ole E. Barndorff-Nielsen & Neil Shephard & Matthias Winkel, 2005. "Limit theorems for multipower variation in the presence of jumps," Economics Papers 2005-W07, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    2. Kolokolov, Aleksey & Livieri, Giulia & Pirino, Davide, 2020. "Statistical inferences for price staleness," Journal of Econometrics, Elsevier, vol. 218(1), pages 32-81.
    3. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    4. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    5. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    6. Mancini, Cecilia, 2008. "Large deviation principle for an estimator of the diffusion coefficient in a jump-diffusion process," Statistics & Probability Letters, Elsevier, vol. 78(7), pages 869-879, May.
    7. Vetter, Mathias, 2010. "Limit theorems for bipower variation of semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 120(1), pages 22-38, January.
    8. George Tauchen & Viktor Todorov, 2010. "Activity Signature Functions for High-Frequency Data Analysis," Working Papers 10-08, Duke University, Department of Economics.
    9. Lorenzo Camponovo & Yukitoshi Matsushita & Taisuke Otsu, 2017. "Empirical likelihood for high frequency data," STICERD - Econometrics Paper Series 591, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    10. Dovonon, Prosper & Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping high-frequency jump tests," IDEI Working Papers 870, Institut d'Économie Industrielle (IDEI), Toulouse.
    11. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Limit theorems for functionals of higher order differences of Brownian semi-stationary processes," CREATES Research Papers 2009-60, Department of Economics and Business Economics, Aarhus University.
    12. Kim Christensen & Roel Oomen & Mark Podolskij, 2011. "Fact or friction: Jumps at ultra high frequency," CREATES Research Papers 2011-19, Department of Economics and Business Economics, Aarhus University.
    13. Yuta Koike, 2014. "An estimator for the cumulative co-volatility of asynchronously observed semimartingales with jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 460-481, June.
    14. Phillips, Peter C.B. & Yu, Jun, 2009. "A two-stage realized volatility approach to estimation of diffusion processes with discrete data," Journal of Econometrics, Elsevier, vol. 150(2), pages 139-150, June.
    15. Mark Podolskij & Mathias Vetter, 2009. "Understanding limit theorems for semimartingales: a short survey," CREATES Research Papers 2009-47, Department of Economics and Business Economics, Aarhus University.
    16. Gabriel P. Mathy, 2014. "Uncertainty Shocks and Equity Return Jumps and Volatility During the Great Depression," Working Papers 2014-02, American University, Department of Economics.
    17. Mark Podolskij & Mathias Vetter, 2007. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," CREATES Research Papers 2007-27, Department of Economics and Business Economics, Aarhus University.
    18. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    19. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    20. Lee, Suzanne S. & Hannig, Jan, 2010. "Detecting jumps from Lévy jump diffusion processes," Journal of Financial Economics, Elsevier, vol. 96(2), pages 271-290, May.
    21. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    22. Federico M. Bandi & Roberto Reno, 2009. "Nonparametric Stochastic Volatility," Global COE Hi-Stat Discussion Paper Series gd08-035, Institute of Economic Research, Hitotsubashi University.
    23. Kolokolov, Aleksey & Livieri, Giulia & Pirino, Davide, 2018. "Statistical inferences for price staleness," SAFE Working Paper Series 236, Leibniz Institute for Financial Research SAFE.
    24. Todorov, Viktor & Bollerslev, Tim, 2010. "Jumps and betas: A new framework for disentangling and estimating systematic risks," Journal of Econometrics, Elsevier, vol. 157(2), pages 220-235, August.
    25. Diep Duong & Norman Swanson, 2013. "Empirical Evidence on the Importance of Aggregation, Asymmetry, and Jumps for Volatility Prediction," Departmental Working Papers 201321, Rutgers University, Department of Economics.
    26. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2014. "A Robust Neighborhood Truncation Approach To Estimation Of Integrated Quarticity," Econometric Theory, Cambridge University Press, vol. 30(1), pages 3-59, February.
    27. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    28. Clément, Emmanuelle & Gloter, Arnaud, 2011. "Limit theorems in the Fourier transform method for the estimation of multivariate volatility," Stochastic Processes and their Applications, Elsevier, vol. 121(5), pages 1097-1124, May.
    29. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    30. Hacène Djellout & Hui Jiang, 2018. "Large Deviations Of The Threshold Estimator Of Integrated (Co-)Volatility Vector In The Presence Of Jumps," Post-Print hal-01147189, HAL.
    31. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Multipower Variation for Brownian Semistationary Processes," CREATES Research Papers 2009-21, Department of Economics and Business Economics, Aarhus University.
    32. Almut E. D. Veraart, 2010. "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?," CREATES Research Papers 2010-65, Department of Economics and Business Economics, Aarhus University.
    33. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    34. Figueroa-López, José E. & Nisen, Jeffrey, 2013. "Optimally thresholded realized power variations for Lévy jump diffusion models," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2648-2677.
    35. Omura, Akihiro & Li, Bin & Chung, Richard & Todorova, Neda, 2018. "Convenience yield, realised volatility and jumps: Evidence from non-ferrous metals," Economic Modelling, Elsevier, vol. 70(C), pages 496-510.
    36. Charles S. Bos & Pawel Janus, 2013. "A Quantile-based Realized Measure of Variation: New Tests for Outlying Observations in Financial Data," Tinbergen Institute Discussion Papers 13-155/III, Tinbergen Institute.
    37. Fulvio Corsi & Davide Pirino & Roberto Reno', 2010. "Threshold Bipower Variation and the Impact of Jumps on Volatility Forecasting," LEM Papers Series 2010/11, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    38. Ewald, Christian & Zou, Yihan, 2021. "Stochastic volatility: A tale of co-jumps, non-normality, GMM and high frequency data," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 37-52.
    39. Jiang, George J. & Oomen, Roel C.A., 2008. "Testing for jumps when asset prices are observed with noise-a "swap variance" approach," Journal of Econometrics, Elsevier, vol. 144(2), pages 352-370, June.
    40. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
    41. Beatriz Vaz de Melo Mendes & Victor Bello Accioly, 2017. "Improving (E)GARCH forecasts with robust realized range measures: Evidence from international markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 631-658, October.
    42. Ahmed, Walid M.A., 2020. "Is there a risk-return trade-off in cryptocurrency markets? The case of Bitcoin," Journal of Economics and Business, Elsevier, vol. 108(C).
    43. Deniz Erdemlioglu & Sebastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    44. Rosenbaum, Mathieu & Tankov, Peter, 2011. "Asymptotic results for time-changed Lévy processes sampled at hitting times," Stochastic Processes and their Applications, Elsevier, vol. 121(7), pages 1607-1632, July.
    45. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.
    46. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, Department of Economics and Business Economics, Aarhus University.
    47. Jihyun Kim & Nour Meddahi, 2020. "Volatility Regressions with Fat Tails," Post-Print hal-03142647, HAL.
    48. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2007. "Power variation for Gaussian processes with stationary increments," CREATES Research Papers 2007-42, Department of Economics and Business Economics, Aarhus University.
    49. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Duration-Based Volatility Estimation," Global COE Hi-Stat Discussion Paper Series gd08-034, Institute of Economic Research, Hitotsubashi University.
    50. Djellout, Hacène & Guillin, Arnaud & Samoura, Yacouba, 2017. "Estimation of the realized (co-)volatility vector: Large deviations approach," Stochastic Processes and their Applications, Elsevier, vol. 127(9), pages 2926-2960.
    51. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
    52. Vasile George MARICA & Lucian Claudiu ANGHEL, 2015. "Sovereign Default Analysis through Extreme Events Identification," Management Dynamics in the Knowledge Economy, College of Management, National University of Political Studies and Public Administration, vol. 3(2), pages 339-353, June.
    53. Kalnina, Ilze, 2011. "Subsampling high frequency data," Journal of Econometrics, Elsevier, vol. 161(2), pages 262-283, April.
    54. Peter C. B. Phillips & Jun Yu, 2006. "A Two-Stage Realized Volatility Approach to Estimation of Diffusion Processes with Discrete," Macroeconomics Working Papers 22472, East Asian Bureau of Economic Research.
    55. Aleksey Kolokolov & Giulia Livieri & Davide Pirino, 2022. "Testing for Endogeneity of Irregular Sampling Schemes," CEIS Research Paper 547, Tor Vergata University, CEIS, revised 19 Dec 2022.
    56. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    57. Amorino, Chiara & Gloter, Arnaud, 2020. "Unbiased truncated quadratic variation for volatility estimation in jump diffusion processes," Stochastic Processes and their Applications, Elsevier, vol. 130(10), pages 5888-5939.
    58. Mancini, Cecilia & Renò, Roberto, 2011. "Threshold estimation of Markov models with jumps and interest rate modeling," Journal of Econometrics, Elsevier, vol. 160(1), pages 77-92, January.
    59. José E. Figueroa-López & Jeffrey Nisen, 2019. "Second-order properties of thresholded realized power variations of FJA additive processes," Statistical Inference for Stochastic Processes, Springer, vol. 22(3), pages 431-474, October.
    60. Chao YU & Xujie ZHAO, 2021. "Measuring the Jump Risk Contribution under Market Microstructure Noise – Evidence from Chinese Stock Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 32-47, December.
    61. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2011. "A Functional Filtering and Neighborhood Truncation Approach to Integrated Quarticity Estimation," NBER Working Papers 17152, National Bureau of Economic Research, Inc.
    62. Diep Duong & Norman R. Swanson, 2011. "Empirical Evidence on Jumps and Large Fluctuations in Individual Stocks," Departmental Working Papers 201116, Rutgers University, Department of Economics.
    63. I. Gaia Becheri & Feike C. Drost & Bas J.M. Werker, 2016. "Asymptotic Inference for Jump Diffusions with State-Dependent Intensity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 520-542, June.
    64. Park, Joon Y. & Wang, Bin, 2021. "Nonparametric estimation of jump diffusion models," Journal of Econometrics, Elsevier, vol. 222(1), pages 688-715.
    65. Dobrislav Dobrev & Pawel J. Szerszen, 2010. "The information content of high-frequency data for estimating equity return models and forecasting risk," Finance and Economics Discussion Series 2010-45, Board of Governors of the Federal Reserve System (U.S.).
    66. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena.
    67. Dong, Yingjie & Huang, Wenxin & Tse, Yiu-Kuen, 2023. "Price comovement and market segmentation of Chinese A- and H-shares: Evidence from a panel latent-factor model," Journal of International Money and Finance, Elsevier, vol. 131(C).
    68. Patrick Chang, 2020. "Fourier instantaneous estimators and the Epps effect," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-24, September.
    69. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    70. Neil Shephard & Kevin Sheppard, 2012. "Efficient and feasible inference for the components of financial variation using blocked multipower variation," Economics Series Working Papers 593, University of Oxford, Department of Economics.
    71. Dobrislav Dobrev & Pawel J. Szerszen, 2010. "The information content of high-frequency data for estimating equity return models and forecasting risk," International Finance Discussion Papers 1005, Board of Governors of the Federal Reserve System (U.S.).
    72. Cuchiero, Christa & Teichmann, Josef, 2015. "Fourier transform methods for pathwise covariance estimation in the presence of jumps," Stochastic Processes and their Applications, Elsevier, vol. 125(1), pages 116-160.
    73. Figueroa-López, José E. & Mancini, Cecilia, 2019. "Optimum thresholding using mean and conditional mean squared error," Journal of Econometrics, Elsevier, vol. 208(1), pages 179-210.
    74. Jean Jacod, 2019. "Estimation of volatility in a high-frequency setting: a short review," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 351-385, December.
    75. Liu, Guangying & Zhang, Xinsheng, 2011. "Power variation of fractional integral processes with jumps," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 962-972, August.
    76. Palandri, Alessandro, 2015. "Do negative and positive equity returns share the same volatility dynamics?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 486-505.
    77. Cecilia Mancini, 2009. "Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 270-296, June.
    78. Kim, Jihyun & Park, Joon & Wang, Bin, 2020. "Estimation of Volatility Functions in Jump Diffusions Using Truncated Bipower Increments," TSE Working Papers 20-1096, Toulouse School of Economics (TSE).
    79. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
    80. Corradi, Valentina & Silvapulle, Mervyn J. & Swanson, Norman R., 2018. "Testing for jumps and jump intensity path dependence," Journal of Econometrics, Elsevier, vol. 204(2), pages 248-267.
    81. Rama Cont & Cecilia Mancini, 2010. "Nonparametric tests for pathwise properties of semimartingales," Working Papers - Mathematical Economics 2010-02, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    82. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility Regressions with Fat Tails," TSE Working Papers 20-1097, Toulouse School of Economics (TSE).
    83. Todorov, Viktor, 2009. "Estimation of continuous-time stochastic volatility models with jumps using high-frequency data," Journal of Econometrics, Elsevier, vol. 148(2), pages 131-148, February.
    84. Jacod, Jean, 2008. "Asymptotic properties of realized power variations and related functionals of semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 118(4), pages 517-559, April.
    85. Yingjie Dong & Yiu-Kuen Tse, 2017. "Business Time Sampling Scheme with Applications to Testing Semi-Martingale Hypothesis and Estimating Integrated Volatility," Econometrics, MDPI, vol. 5(4), pages 1-19, November.
    86. Hacène Djellout & Arnaud Guillin & Yacouba Samoura, 2017. "Large Deviations Of The Realized (Co-)Volatility Vector," Post-Print hal-01082903, HAL.
    87. Diep Duong & Norman R. Swanson, 2011. "Volatility in Discrete and Continuous Time Models: A Survey with New Evidence on Large and Small Jumps," Departmental Working Papers 201117, Rutgers University, Department of Economics.

  18. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Papers 2005-W16, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    2. Bence Toth & Janos Kertesz, 2009. "The Epps effect revisited," Quantitative Finance, Taylor & Francis Journals, vol. 9(7), pages 793-802.
    3. Peter C. B. Phillips & Jun Yu, 2009. "Information Loss in Volatility Measurement with Flat Price Trading," Global COE Hi-Stat Discussion Paper Series gd08-039, Institute of Economic Research, Hitotsubashi University.
    4. Xinhong Lu & Ken-Ichi Kawai & Koichi Maekawa, 2010. "Estimating Bivariate Garch-Jump Model Based On High Frequency Data: The Case Of Revaluation Of The Chinese Yuan In July 2005," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 27(02), pages 287-300.
    5. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
    6. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
    7. Gael M. Martin & Andrew Reidy & Jill Wright, 2006. "Assessing the Impact of Market Microstructure Noise and Random Jumps on the Relative Forecasting Performance of Option-Implied and Returns-Based Volatility," Monash Econometrics and Business Statistics Working Papers 10/06, Monash University, Department of Econometrics and Business Statistics.
    8. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    9. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford.
    10. Neil Shephard, 2005. "Stochastic Volatility," Economics Papers 2005-W17, Economics Group, Nuffield College, University of Oxford.
    11. Irving Fisher Committee, 2005. "Proceedings of the Bank of Canada/IFC Workshop on "Data requirements for analysing the stability and vulnerability of mature financial systems", Ottawa, June 2005," IFC Bulletins, Bank for International Settlements, number 23.
    12. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    13. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    14. Yi, Chae-Deug, 2020. "Jump probability using volatility periodicity filters in US Dollar/Euro exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    15. Aktham Maghyereh & Hussein Abdoh, 2022. "COVID-19 and the volatility interlinkage between bitcoin and financial assets," Empirical Economics, Springer, vol. 63(6), pages 2875-2901, December.
    16. Vortelinos, Dimitrios I., 2010. "The properties of realized correlation: Evidence from the French, German and Greek equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 273-290, August.
    17. Christensen, Kim & Podolski, Mark, 2005. "Asymptotic theory for range-based estimation of integrated variance of a continuous semi-martingale," Technical Reports 2005,18, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    18. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    19. Elezovic, Suad, 2009. "Functional modelling of volatility in the Swedish limit order book," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2107-2118, April.
    20. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    21. Anatoliy Swishchuk, 2013. "Modeling and Pricing of Swaps for Financial and Energy Markets with Stochastic Volatilities," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8660, December.

  19. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," Economics Papers 2005-W06, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Réveillac, Anthony, 2009. "Estimation of quadratic variation for two-parameter diffusions," Stochastic Processes and their Applications, Elsevier, vol. 119(5), pages 1652-1672, May.
    2. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    3. Peter C. B. Phillips & Jun Yu, 2009. "Information Loss in Volatility Measurement with Flat Price Trading," Global COE Hi-Stat Discussion Paper Series gd08-039, Institute of Economic Research, Hitotsubashi University.
    4. Fleming, Jeff & Paye, Bradley S., 2011. "High-frequency returns, jumps and the mixture of normals hypothesis," Journal of Econometrics, Elsevier, vol. 160(1), pages 119-128, January.
    5. Fangfang Wang, 2016. "An Unbiased Measure of Integrated Volatility in the Frequency Domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 147-164, March.
    6. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2012. "Parametric Inference and Dynamic State Recovery from Option Panels," Global COE Hi-Stat Discussion Paper Series gd12-266, Institute of Economic Research, Hitotsubashi University.
    7. Isao Ishida & Michael McAleer & Kosuke Oya, 2011. "Estimating the Leverage Parameter of Continuous-time Stochastic Volatility Models Using High Frequency S&P 500 and VIX," Working Papers in Economics 11/11, University of Canterbury, Department of Economics and Finance.
    8. Almut Veraart, 2008. "Inference for the jump part of quadratic variation of Itô semimartingales," CREATES Research Papers 2008-17, Department of Economics and Business Economics, Aarhus University.
    9. Phillips, Peter C.B. & Yu, Jun, 2009. "A two-stage realized volatility approach to estimation of diffusion processes with discrete data," Journal of Econometrics, Elsevier, vol. 150(2), pages 139-150, June.
    10. Neil Shephard & Ole E. Barndorff-Nielsen & Asger Lunde, 2006. "Subsampling realised kernels," Economics Series Working Papers 278, University of Oxford, Department of Economics.
    11. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    12. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    13. Jerome L Kreuser & Didier Sornette, 2017. "Super-Exponential RE Bubble Model with Efficient Crashes," Swiss Finance Institute Research Paper Series 17-33, Swiss Finance Institute.
    14. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    15. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk-realised semivariance," Economics Papers 2008-W02, Economics Group, Nuffield College, University of Oxford.
    16. Liao, Yin & Anderson, Heather M., 2019. "Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
    17. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    18. Bo Yu & Bruce Mizrach & Norman R. Swanson, 2020. "New Evidence of the Marginal Predictive Content of Small and Large Jumps in the Cross-Section," Econometrics, MDPI, vol. 8(2), pages 1-52, May.
    19. Clément, Emmanuelle & Gloter, Arnaud, 2011. "Limit theorems in the Fourier transform method for the estimation of multivariate volatility," Stochastic Processes and their Applications, Elsevier, vol. 121(5), pages 1097-1124, May.
    20. Hacène Djellout & Hui Jiang, 2018. "Large Deviations Of The Threshold Estimator Of Integrated (Co-)Volatility Vector In The Presence Of Jumps," Post-Print hal-01147189, HAL.
    21. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Multipower Variation for Brownian Semistationary Processes," CREATES Research Papers 2009-21, Department of Economics and Business Economics, Aarhus University.
    22. Hounyo, Ulrich & Varneskov, Rasmus T., 2017. "A local stable bootstrap for power variations of pure-jump semimartingales and activity index estimation," Journal of Econometrics, Elsevier, vol. 198(1), pages 10-28.
    23. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    24. Silja Kinnebrock & Mark Podolskij, 2007. "A Note on the Central Limit Theorem for Bipower Variation of General Functions," OFRC Working Papers Series 2007fe03, Oxford Financial Research Centre.
    25. Adam D. Bull, 2014. "Near-optimal estimation of jump activity in semimartingales," Papers 1409.8150, arXiv.org, revised Jan 2016.
    26. Charles S. Bos & Paweł Janus & Siem Jan Koopman, 2012. "Spot Variance Path Estimation and Its Application to High-Frequency Jump Testing," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 354-389, 2012 06.
    27. Fulvio Corsi & Davide Pirino & Roberto Reno', 2010. "Threshold Bipower Variation and the Impact of Jumps on Volatility Forecasting," LEM Papers Series 2010/11, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    28. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    29. Ishida, I. & McAleer, M.J. & Oya, K., 2011. "Estimating the Leverage Parameter of Continuous-time Stochastic Volatility Models Using High Frequency S&P 500 VIX," Econometric Institute Research Papers EI 2011-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    30. Simon Clinet & Yoann Potiron, 2021. "Estimation for high-frequency data under parametric market microstructure noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
    31. Ulrich Hounyo & Bezirgen Veliyev, 2015. "Validity of Edgeworth expansions for realized volatility estimators," CREATES Research Papers 2015-21, Department of Economics and Business Economics, Aarhus University.
    32. He, Xin-Jiang & Lin, Sha, 2023. "Analytically pricing variance and volatility swaps under a Markov-modulated model with liquidity risks," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    33. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.
    34. Nirei, Makoto & Sushko, Vladyslav, 2011. "Jumps in foreign exchange rates and stochastic unwinding of carry trades," International Review of Economics & Finance, Elsevier, vol. 20(1), pages 110-127, January.
    35. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2007. "Power variation for Gaussian processes with stationary increments," CREATES Research Papers 2007-42, Department of Economics and Business Economics, Aarhus University.
    36. Kristensen, Dennis, 2010. "Nonparametric Filtering Of The Realized Spot Volatility: A Kernel-Based Approach," Econometric Theory, Cambridge University Press, vol. 26(1), pages 60-93, February.
    37. Xu, De-xuan & Yang, Ben-zhang & Kang, Jian-hao & Huang, Nan-jing, 2021. "Variance and volatility swaps valuations with the stochastic liquidity risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    38. Bandi, Federico M. & Renò, Roberto, 2012. "Time-varying leverage effects," Journal of Econometrics, Elsevier, vol. 169(1), pages 94-113.
    39. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Duration-Based Volatility Estimation," Global COE Hi-Stat Discussion Paper Series gd08-034, Institute of Economic Research, Hitotsubashi University.
    40. Djellout, Hacène & Guillin, Arnaud & Samoura, Yacouba, 2017. "Estimation of the realized (co-)volatility vector: Large deviations approach," Stochastic Processes and their Applications, Elsevier, vol. 127(9), pages 2926-2960.
    41. Ysusi Carla, 2007. "Multipower Variation Under Market Microstructure Effects," Working Papers 2007-13, Banco de México.
    42. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
    43. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
    44. Li, Yingying & Xie, Shangyu & Zheng, Xinghua, 2016. "Efficient estimation of integrated volatility incorporating trading information," Journal of Econometrics, Elsevier, vol. 195(1), pages 33-50.
    45. Hwang, Eunju & Shin, Dong Wan, 2013. "Stationary bootstrapping realized volatility," Statistics & Probability Letters, Elsevier, vol. 83(9), pages 2045-2051.
    46. Dovonon, Prosper & Gonçalves, Sílvia & Meddahi, Nour, 2013. "Bootstrapping realized multivariate volatility measures," Journal of Econometrics, Elsevier, vol. 172(1), pages 49-65.
    47. Kalnina, Ilze, 2011. "Subsampling high frequency data," Journal of Econometrics, Elsevier, vol. 161(2), pages 262-283, April.
    48. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2011. "A Functional Filtering and Neighborhood Truncation Approach to Integrated Quarticity Estimation," NBER Working Papers 17152, National Bureau of Economic Research, Inc.
    49. Konstantinos Gkillas & Dimitrios Vortelinos & Christos Floros & Alexandros Garefalakis & Nikolaos Sariannidis, 2020. "Greek sovereign crisis and European exchange rates: effects of news releases and their providers," Annals of Operations Research, Springer, vol. 294(1), pages 515-536, November.
    50. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena.
    51. Ceylan, Ozcan, 2012. "Time-Varying Volatility Asymmetry: A Conditioned HAR-RV(CJ) EGARCH-M Model," GIAM Working Papers 12-4, Galatasaray University Economic Research Center.
    52. Ghysels, Eric & Sohn, Bumjean, 2009. "Which power variation predicts volatility well?," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 686-700, September.
    53. Gonçalves, Sílvia & Meddahi, Nour, 2011. "Box-Cox transforms for realized volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 129-144, January.
    54. Neil Shephard & Kevin Sheppard, 2012. "Efficient and feasible inference for the components of financial variation using blocked multipower variation," Economics Series Working Papers 593, University of Oxford, Department of Economics.
    55. Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021. "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 46-61.
    56. Lorenzo Camponovo & Yukitoshi Matsushita & Taisuke Otsu, 2015. "Nonparametric likelihood for volatility under high frequency data," STICERD - Econometrics Paper Series /2015/581, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    57. Pierre Bajgrowicz & Olivier Scaillet & Adrien Treccani, 2016. "Jumps in High-Frequency Data: Spurious Detections, Dynamics, and News," Management Science, INFORMS, vol. 62(8), pages 2198-2217, August.
    58. Dimitrios I. Vortelinos, 2015. "Out‐of‐sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini‐futures markets," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 58-67, November.
    59. Cem Cakmakli & Verda Ozturk, 2021. "Economic Value of Modeling the Joint Distribution of Returns and Volatility: Leverage Timing," Koç University-TUSIAD Economic Research Forum Working Papers 2110, Koc University-TUSIAD Economic Research Forum.
    60. Li, Meiyu & Gençay, Ramazan & Xue, Yi, 2016. "Is it Brownian or fractional Brownian motion?," Economics Letters, Elsevier, vol. 145(C), pages 52-55.
    61. Neil Shephard & Silja Kinnebrock & Ole E. Barndorff-Neilsen, 2008. "Measuring downside risk - realised semivariance," Economics Series Working Papers 382, University of Oxford, Department of Economics.
    62. Rasmus Tangsgaard Varneskov, 2011. "Generalized Flat-Top Realized Kernel Estimation of Ex-Post Variation of Asset Prices Contaminated by Noise," CREATES Research Papers 2011-31, Department of Economics and Business Economics, Aarhus University.
    63. Dumitru, Ana-Maria & Hizmeri, Rodrigo & Izzeldin, Marwan, 2019. "Forecasting the Realized Variance in the Presence of Intraday Periodicity," EconStor Preprints 193631, ZBW - Leibniz Information Centre for Economics.
    64. Wang, Jiazhen & Jiang, Yuexiang & Zhu, Yanjian & Yu, Jing, 2020. "Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 91(C), pages 428-444.
    65. Hacène Djellout & Arnaud Guillin & Yacouba Samoura, 2017. "Large Deviations Of The Realized (Co-)Volatility Vector," Post-Print hal-01082903, HAL.
    66. Ysusi Carla, 2006. "Estimating Integrated Volatility Using Absolute High-Frequency Returns," Working Papers 2006-13, Banco de México.

  20. Ole Barndorff-Nielsen & Svend Erik Graversen & Jean Jacod & Mark Podolskij & Neil Shephard, 2004. "A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales," Economics Papers 2004-W29, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    2. Silja Kinnebrock & Mark Podolskij, 2008. "An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models," CREATES Research Papers 2008-23, Department of Economics and Business Economics, Aarhus University.
    3. Dufour, Jean-Marie & García, René & Taamouti, Abderrahim, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Podolskij, Mark & Vetter, Mathias, 2008. "Bipower-type estimation in a noisy diffusion setting," Technical Reports 2008,24, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    5. Almut Veraart & Luitgard Veraart, 2012. "Stochastic volatility and stochastic leverage," Annals of Finance, Springer, vol. 8(2), pages 205-233, May.
    6. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Limit theorems for functionals of higher order differences of Brownian semi-stationary processes," CREATES Research Papers 2009-60, Department of Economics and Business Economics, Aarhus University.
    7. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," Global COE Hi-Stat Discussion Paper Series gd08-032, Institute of Economic Research, Hitotsubashi University.
    8. Almut Veraart, 2008. "Inference for the jump part of quadratic variation of Itô semimartingales," CREATES Research Papers 2008-17, Department of Economics and Business Economics, Aarhus University.
    9. Kim Christensen & Roel Oomen & Mark Podolskij, 2011. "Fact or friction: Jumps at ultra high frequency," CREATES Research Papers 2011-19, Department of Economics and Business Economics, Aarhus University.
    10. Mark Podolskij & Mathias Vetter, 2009. "Understanding limit theorems for semimartingales: a short survey," CREATES Research Papers 2009-47, Department of Economics and Business Economics, Aarhus University.
    11. Mark Podolskij & Mathias Vetter, 2007. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," CREATES Research Papers 2007-27, Department of Economics and Business Economics, Aarhus University.
    12. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    13. Nikolaus Hautsch & Mark Podolskij, 2013. "Preaveraging-Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 165-183, April.
    14. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    15. Cecilia Mancini & Fabio Gobbi, 2010. "Identifying the Brownian Covariation from the Co-Jumps Given Discrete Observations," Working Papers - Mathematical Economics 2010-05, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    16. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk-realised semivariance," Economics Papers 2008-W02, Economics Group, Nuffield College, University of Oxford.
    17. Todorov, Viktor & Bollerslev, Tim, 2010. "Jumps and betas: A new framework for disentangling and estimating systematic risks," Journal of Econometrics, Elsevier, vol. 157(2), pages 220-235, August.
    18. Diep Duong & Norman Swanson, 2013. "Empirical Evidence on the Importance of Aggregation, Asymmetry, and Jumps for Volatility Prediction," Departmental Working Papers 201321, Rutgers University, Department of Economics.
    19. Kim Christensen & Mark Podolskij & Mathias Vetter, 2009. "Bias-correcting the realized range-based variance in the presence of market microstructure noise," Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
    20. Christensen, Kim & Kinnebrock, Silja & Podolskij, Mark, 2010. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," Journal of Econometrics, Elsevier, vol. 159(1), pages 116-133, November.
    21. Dette, Holger & Podolskij, Mark, 2005. "Testing the parametric form of the volatility in continuous time diffusion models: an empirical process approach," Technical Reports 2005,50, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    22. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    23. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    24. Alexander Alvarez & Fabien Panloup & Monique Pontier & Nicolas Savy, 2012. "Estimation of the instantaneous volatility," Statistical Inference for Stochastic Processes, Springer, vol. 15(1), pages 27-59, April.
    25. Hanousek Jan & Kočenda Evžen & Novotný Jan, 2012. "The identification of price jumps," Monte Carlo Methods and Applications, De Gruyter, vol. 18(1), pages 53-77, January.
    26. Mark Podolskij & Daniel Ziggel, 2007. "A Range-Based Test for the Parametric Form of the Volatility in Diffusion Models," CREATES Research Papers 2007-26, Department of Economics and Business Economics, Aarhus University.
    27. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Multipower Variation for Brownian Semistationary Processes," CREATES Research Papers 2009-21, Department of Economics and Business Economics, Aarhus University.
    28. Mark Podolskij & Mathieu Rosenbaum, 2012. "Testing the local volatility assumption: a statistical approach," Annals of Finance, Springer, vol. 8(1), pages 31-48, February.
    29. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.
    30. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2007. "Power variation for Gaussian processes with stationary increments," CREATES Research Papers 2007-42, Department of Economics and Business Economics, Aarhus University.
    31. Ole E. Barndorff-Nielsen & Almut E. D. Veraart, 2009. "Stochastic volatility of volatility in continuous time," CREATES Research Papers 2009-25, Department of Economics and Business Economics, Aarhus University.
    32. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
    33. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2005. "Roughing it Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," NBER Working Papers 11775, National Bureau of Economic Research, Inc.
    34. Ysusi Carla, 2007. "Multipower Variation Under Market Microstructure Effects," Working Papers 2007-13, Banco de México.
    35. Jean Jacod & Mark Podolskij & Mathias Vetter, 2008. "Intertemporal Asset Allocation with Habit Formation in Preferences: An Approximate Analytical Solution," CREATES Research Papers 2008-61, Department of Economics and Business Economics, Aarhus University.
    36. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    37. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    38. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2011. "A Functional Filtering and Neighborhood Truncation Approach to Integrated Quarticity Estimation," NBER Working Papers 17152, National Bureau of Economic Research, Inc.
    39. Diep Duong & Norman R. Swanson, 2011. "Empirical Evidence on Jumps and Large Fluctuations in Individual Stocks," Departmental Working Papers 201116, Rutgers University, Department of Economics.
    40. Mark Podolskij & Daniel Ziggel, 2008. "New tests for jumps: a threshold-based approach," CREATES Research Papers 2008-34, Department of Economics and Business Economics, Aarhus University.
    41. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena.
    42. Christensen, Kim & Podolski, Mark, 2005. "Asymptotic theory for range-based estimation of integrated variance of a continuous semi-martingale," Technical Reports 2005,18, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    43. Holger Dette & Mark Podolskij & Mathias Vetter, 2006. "Estimation of Integrated Volatility in Continuous‐Time Financial Models with Applications to Goodness‐of‐Fit Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 259-278, June.
    44. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Density Estimators for Daily Volatility Based on the Use of Realized Measures," Departmental Working Papers 200620, Rutgers University, Department of Economics.
    45. Neil Shephard & Silja Kinnebrock & Ole E. Barndorff-Neilsen, 2008. "Measuring downside risk - realised semivariance," Economics Series Working Papers 382, University of Oxford, Department of Economics.
    46. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
    47. Bekiros, Stelios & Jlassi, Mouna & Naoui, Kamel & Uddin, Gazi Salah, 2017. "The asymmetric relationship between returns and implied volatility: Evidence from global stock markets," Journal of Financial Stability, Elsevier, vol. 30(C), pages 156-174.
    48. Rasmus Tangsgaard Varneskov, 2011. "Generalized Flat-Top Realized Kernel Estimation of Ex-Post Variation of Asset Prices Contaminated by Noise," CREATES Research Papers 2011-31, Department of Economics and Business Economics, Aarhus University.
    49. Jan Novotn?? & Jan Hanousek & Ev??en Ko??enda, 2013. "Price Jump Indicators: Stock Market Empirics During the Crisis," William Davidson Institute Working Papers Series wp1050, William Davidson Institute at the University of Michigan.
    50. Fabio Gobbi & Cecilia Mancini, 2006. "Identifying the covariation between the diffusion parts and the co-jumps given discrete observations," Papers math/0610621, arXiv.org, revised Jul 2008.
    51. Diep Duong & Norman R. Swanson, 2011. "Volatility in Discrete and Continuous Time Models: A Survey with New Evidence on Large and Small Jumps," Departmental Working Papers 201117, Rutgers University, Department of Economics.
    52. Ysusi Carla, 2006. "Estimating Integrated Volatility Using Absolute High-Frequency Returns," Working Papers 2006-13, Banco de México.

  21. Ole Barndorff-Nielsen & Neil Shephard, 2004. "Multipower Variation and Stochastic Volatility," Economics Papers 2004-W30, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    2. de Vilder, Robin G. & Visser, Marcel P., 2007. "Volatility Proxies for Discrete Time Models," MPRA Paper 4917, University Library of Munich, Germany.
    3. Walter Distaso & Basel Awartani & Valentina Corradi, 2004. "Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average," Econometric Society 2004 Australasian Meetings 273, Econometric Society.
    4. Inekwe John Nkwoma, 2014. "Business Cycle Variability and Growth Linkage," Monash Economics Working Papers 38-14, Monash University, Department of Economics.

  22. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2004. "Regular and Modified Kernel-Based Estimators of Integrated Variance: The Case with Independent Noise," Economics Papers 2004-W28, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    2. Peter Reinhard Hansen & Asger Lunde, 2005. "A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 525-554.
    3. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    4. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    5. John M. Maheu & Thomas H. McCurdy, 2009. "Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions?," Working Paper series 19_09, Rimini Centre for Economic Analysis.
    6. Torben G. Andersen & Luca Benzoni, 2010. "Do Bonds Span Volatility Risk in the U.S. Treasury Market? A Specification Test for Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 65(2), pages 603-653, April.
    7. Ole E. Barndorff-Nielsen & Neil Shephard & Matthias Winkel, 2005. "Limit theorems for multipower variation in the presence of jumps," OFRC Working Papers Series 2005fe06, Oxford Financial Research Centre.
    8. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    9. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    10. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford.
    11. Michiel de Pooter & Martin Martens & Dick van Dijk, 2005. "Predicting the Daily Covariance Matrix for S&P 100 Stocks using Intraday Data - But which Frequency to use?," Tinbergen Institute Discussion Papers 05-089/4, Tinbergen Institute, revised 03 Jan 2006.
    12. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    13. Ostap Okhrin & Anastasija Tetereva, 2017. "The Realized Hierarchical Archimedean Copula in Risk Modelling," Econometrics, MDPI, vol. 5(2), pages 1-31, June.
    14. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    15. Zhang, Lan & Mykland, Per A. & Aït-Sahalia, Yacine, 2011. "Edgeworth expansions for realized volatility and related estimators," Journal of Econometrics, Elsevier, vol. 160(1), pages 190-203, January.
    16. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," Journal of Econometrics, Elsevier, vol. 193(2), pages 367-389.
    17. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2005. "Roughing it Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," NBER Working Papers 11775, National Bureau of Economic Research, Inc.
    18. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
    19. Yacine Ait-Sahalia & Per A. Mykland & Lan Zhang, 2005. "Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise," NBER Working Papers 11380, National Bureau of Economic Research, Inc.
    20. Richard Gerlach & Declan Walpole & Chao Wang, 2017. "Semi-parametric Bayesian tail risk forecasting incorporating realized measures of volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 199-215, February.
    21. Giuseppe Curci & Fulvio Corsi, 2012. "Discrete sine transform for multi-scale realized volatility measures§," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 263-279, April.
    22. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    23. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    24. Christensen, Kim & Podolski, Mark, 2005. "Asymptotic theory for range-based estimation of integrated variance of a continuous semi-martingale," Technical Reports 2005,18, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    25. Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.
    26. Masato Ubukata & Toshiaki Watanabe, 2011. "Pricing Nikkei 225 Options Using Realized Volatility," IMES Discussion Paper Series 11-E-18, Institute for Monetary and Economic Studies, Bank of Japan.
    27. B. Jungbacker & S.J. Koopman, 2005. "Model-based Measurement of Actual Volatility in High-Frequency Data," Tinbergen Institute Discussion Papers 05-002/4, Tinbergen Institute.
    28. Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
    29. Benlagha, Noureddine & Chargui, Sana, 2017. "Range-based and GARCH volatility estimation: Evidence from the French asset market," Global Finance Journal, Elsevier, vol. 32(C), pages 149-165.

  23. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "A Feasible Central Limit Theory for Realised Volatility Under Leverage," Economics Papers 2004-W03, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    2. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    3. Bollerslev, Tim & Zhou, Hao, 2006. "Volatility puzzles: a simple framework for gauging return-volatility regressions," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 123-150.
    4. Walter Distaso & Basel Awartani & Valentina Corradi, 2004. "Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average," Econometric Society 2004 Australasian Meetings 273, Econometric Society.
    5. Tao, Minjing & Wang, Yahzen & Yao, Qiwei & Zou, Jian, 2011. "Large volatility matrix inference via combining low-frequency and high-frequency approaches," LSE Research Online Documents on Economics 39321, London School of Economics and Political Science, LSE Library.
    6. Elezovic, Suad, 2009. "Functional modelling of volatility in the Swedish limit order book," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2107-2118, April.

  24. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Econometrics of testing for jumps in financial economics using bipower variation," Economics Papers 2003-W21, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Yu-Min Yen, 2013. "Testing Jumps via False Discovery Rate Control," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    2. Mancini, Cecilia, 2011. "The speed of convergence of the Threshold estimator of integrated variance," Stochastic Processes and their Applications, Elsevier, vol. 121(4), pages 845-855, April.
    3. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    4. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    5. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    6. Matteo Bonato & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Investor Happiness and Predictability of the Realized Volatility of Oil Price," Working Papers 202009, University of Pretoria, Department of Economics.
    7. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    8. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
    9. Anisha Ghosh & Oliver Linton, 2019. "Estimation with Mixed Data Frequencies: A Bias-Correction Approach," CeMMAP working papers CWP65/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    11. Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    12. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    13. Megaritis, Anastasios & Vlastakis, Nikolaos & Triantafyllou, Athanasios, 2021. "Stock market volatility and jumps in times of uncertainty," Journal of International Money and Finance, Elsevier, vol. 113(C).
    14. Feng, Yun & Hou, Weijie & Song, Yuping, 2023. "Asymmetric contagion of jump risk in the Chinese financial sector: Monetary policy transmission matters," Economic Modelling, Elsevier, vol. 119(C).
    15. Da Fonseca, José & Ignatieva, Katja, 2019. "Jump activity analysis for affine jump-diffusion models: Evidence from the commodity market," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 45-62.
    16. Jozef Barunik & Lukas Vacha, 2015. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1347-1364, August.
    17. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    18. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    19. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    20. Peter Christoffersen & Bruno Feunou & Yoontae Jeon, 2014. "Option Valuation with Observable Volatility and Jump Dynamics," CREATES Research Papers 2015-07, Department of Economics and Business Economics, Aarhus University.
    21. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    22. Basel M. A. Awartani, 2008. "Forecasting volatility with noisy jumps: an application to the Dow Jones Industrial Average stocks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 267-278.
    23. Kalnina, Ilze & Linton, Oliver, 2007. "Inference about realized volatility using infill subsampling," LSE Research Online Documents on Economics 4411, London School of Economics and Political Science, LSE Library.
    24. Ourania Theodosiadou & Sotiris Skaperas & George Tsaklidis, 2017. "Change Point Detection and Estimation of the Two-Sided Jumps of Asset Returns Using a Modified Kalman Filter," Risks, MDPI, vol. 5(1), pages 1-14, March.
    25. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    26. Arif, Muhammad & Naeem, Muhammad Abubakr & Farid, Saqib & Nepal, Rabindra & Jamasb, Tooraj, 2022. "Diversifier or more? Hedge and safe haven properties of green bonds during COVID-19," Energy Policy, Elsevier, vol. 168(C).
    27. Doureige J. Jurdi, 2020. "Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    28. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    29. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    30. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01411808, HAL.
    31. Lee, Hwang Hee & Hyun, Jung-Soon, 2019. "The asymmetric effect of equity volatility on credit default swap spreads," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 125-136.
    32. Sevcan Uzun & Ahmet Sensoy & Duc Khuong Nguyen, 2023. "Jump forecasting in foreign exchange markets: A high‐frequency analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 578-624, April.
    33. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and state-level stock market realized volatility," Journal of Financial Markets, Elsevier, vol. 66(C).
    34. Jose E. Figueroa-Lopez & Martin Forde, 2011. "The small-maturity smile for exponential Levy models," Papers 1105.3180, arXiv.org, revised Dec 2011.
    35. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2011. "The Japanese economy in crises: A time series segmentation study," Economics Discussion Papers 2011-24, Kiel Institute for the World Economy (IfW Kiel).
    36. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "High-Frequency Jump Tests: Which Test Should We Use?," Papers 1708.09520, arXiv.org, revised Jan 2020.
    37. Giot, Pierre & Laurent, Sébastien & Petitjean, Mikael, 2010. "Trading activity, realized volatility and jumps," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 168-175, January.
    38. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2015. "Volatility transmission in global financial markets," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 3-18.
    39. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    40. Huang, Jianbai & Tang, Jing & Zhang, Hongwei, 2020. "The effect of investors’ information search behaviors on rebar market return dynamics using high frequency data," Resources Policy, Elsevier, vol. 66(C).
    41. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
    42. Almut Veraart & Luitgard Veraart, 2012. "Stochastic volatility and stochastic leverage," Annals of Finance, Springer, vol. 8(2), pages 205-233, May.
    43. Márcio Poletti Laurini & Roberto Baltieri Mauad & Fernando Antonio Lucena Aiube, 2016. "Multivariate Stochastic Volatility-Double Jump Model: an application for oil assets," Working Papers Series 415, Central Bank of Brazil, Research Department.
    44. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
    45. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    46. Geon Ho Choe & Kyungsub Lee, 2013. "High moment variations and their application," Papers 1311.4973, arXiv.org.
    47. Maria Elvira Mancino & Simona Sanfelici, 2011. "Estimation of Quarticity with High Frequency Data," Working Papers - Mathematical Economics 2011-06, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, revised Jan 2012.
    48. Lee, Suzanne S. & Wang, Minho, 2019. "The impact of jumps on carry trade returns," Journal of Financial Economics, Elsevier, vol. 131(2), pages 433-455.
    49. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    50. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
    51. Li, Xiafei & Liao, Yin & Lu, Xinjie & Ma, Feng, 2022. "An oil futures volatility forecast perspective on the selection of high-frequency jump tests," Energy Economics, Elsevier, vol. 116(C).
    52. Fleming, Jeff & Paye, Bradley S., 2011. "High-frequency returns, jumps and the mixture of normals hypothesis," Journal of Econometrics, Elsevier, vol. 160(1), pages 119-128, January.
    53. Todorov, Viktor & Zhang, Yang, 2023. "Bias reduction in spot volatility estimation from options," Journal of Econometrics, Elsevier, vol. 234(1), pages 53-81.
    54. Diego Amaya & Jean-François Bégin & Geneviève Gauthier, 2022. "The Informational Content of High-Frequency Option Prices," Management Science, INFORMS, vol. 68(3), pages 2166-2201, March.
    55. Serdengeçti, Süleyman & Sensoy, Ahmet & Nguyen, Duc Khuong, 2021. "Dynamics of return and liquidity (co) jumps in emerging foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    56. Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2017. "Jumps in Commodity Markets," Hannover Economic Papers (HEP) dp-615, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    57. Jeremy Large, 2007. "Estimating Quadratic Variation When Quoted Prices Change by a Constant Increment," Economics Series Working Papers 340, University of Oxford, Department of Economics.
    58. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
    59. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2012. "Parametric Inference and Dynamic State Recovery from Option Panels," Global COE Hi-Stat Discussion Paper Series gd12-266, Institute of Economic Research, Hitotsubashi University.
    60. Liu, Wenwen & Zhang, Chang & Qiao, Gaoxiu & Xu, Lei, 2022. "Impact of network investor sentiment and news arrival on jumps," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    61. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2017. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Working Papers 2017-10, University of Tasmania, Tasmanian School of Business and Economics.
    62. Lorenzo Camponovo & Yukitoshi Matsushita & Taisuke Otsu, 2017. "Empirical likelihood for high frequency data," STICERD - Econometrics Paper Series 591, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    63. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
    64. Ai-ru (Meg) Cheng & Kuntal Das & Takeshi Shimatani, 2013. "Central Bank Intervention and Exchange Rate Volatility: Evidence from Japan Using Realized Volatility," Working Papers in Economics 13/19, University of Canterbury, Department of Economics and Finance.
    65. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    66. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích [Cluster Analysis of Jumps on Capital Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2016(2), pages 127-144.
    67. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    68. Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
    69. Eom, Cheoljun & Kaizoji, Taisei & Kang, Sang Hoon & Pichl, Lukas, 2019. "Bitcoin and investor sentiment: Statistical characteristics and predictability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 511-521.
    70. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    71. Krauss, Christopher & Herrmann, Klaus & Teis, Stefan, 2015. "On the power and size properties of cointegration tests in the light of high-frequency stylized facts," FAU Discussion Papers in Economics 11/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    72. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    73. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2013. "A nonparametric test of a strong leverage hypothesis," CeMMAP working papers 28/13, Institute for Fiscal Studies.
    74. Torben G. Andersen & Nicola Fusari & Viktor Todorov & Rasmus T. Varneskov, 2018. "Unified Inference for Nonlinear Factor Models from Panels with Fixed and Large Time Span," CREATES Research Papers 2018-03, Department of Economics and Business Economics, Aarhus University.
    75. Ulrich Hounyo & Silvia Gonçalves & Nour Meddahi, 2016. "Bootstrapping pre-averaged realized volatility under market microstructure noise," CIRANO Working Papers 2016s-25, CIRANO.
    76. Dovonon, Prosper & Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping high-frequency jump tests," IDEI Working Papers 870, Institut d'Économie Industrielle (IDEI), Toulouse.
    77. Dario Alitab & Giacomo Bormetti & Fulvio Corsi & Adam A. Majewski, 2019. "A realized volatility approach to option pricing with continuous and jump variance components," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 639-664, December.
    78. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Limit theorems for functionals of higher order differences of Brownian semi-stationary processes," CREATES Research Papers 2009-60, Department of Economics and Business Economics, Aarhus University.
    79. Riza Demirer & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2022. "Risk aversion and the predictability of crude oil market volatility: A forecasting experiment with random forests," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(8), pages 1755-1767, August.
    80. Andor, György & Bohák, András, 2017. "Identifying events in financial time series – A new approach with bipower variation," Finance Research Letters, Elsevier, vol. 22(C), pages 42-48.
    81. Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," Economics Series Working Papers 438, University of Oxford, Department of Economics.
    82. Liling Deng & Haifang Xiong & Zhiqiang Wang, 2023. "Research on cojumps of electronic commerce overnight factors in volatility prediction based on joint BW test," Electronic Commerce Research, Springer, vol. 23(1), pages 115-135, March.
    83. Mei, Dexiang & Ma, Feng & Liao, Yin & Wang, Lu, 2020. "Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models," Energy Economics, Elsevier, vol. 86(C).
    84. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," Global COE Hi-Stat Discussion Paper Series gd08-032, Institute of Economic Research, Hitotsubashi University.
    85. Mehmet Balcilar & Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "The Effect of Investor Sentiment on Gold Market Dynamics," Working Papers 201638, University of Pretoria, Department of Economics.
    86. Kim Christensen & Roel Oomen & Mark Podolskij, 2011. "Fact or friction: Jumps at ultra high frequency," CREATES Research Papers 2011-19, Department of Economics and Business Economics, Aarhus University.
    87. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    88. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    89. Pan, Ging-Ginq & Shiu, Yung-Ming & Wu, Tu-Cheng, 2022. "Can risk-neutral skewness and kurtosis subsume the information content of historical jumps?," Journal of Financial Markets, Elsevier, vol. 57(C).
    90. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market Instability and Technical Trading at High Frequency: Evidence from NASDAQ Stocks," LIDAM Reprints LFIN 2021016, Université catholique de Louvain, Louvain Finance (LFIN).
    91. Arnerić, Josip & Matković, Mario & Sorić, Petar, 2019. "Comparison of range-based volatility estimators against integrated volatility in European emerging markets," Finance Research Letters, Elsevier, vol. 28(C), pages 118-124.
    92. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    93. Chan, Kam Fong & Gray, Philip & van Campen, Bart, 2008. "A new approach to characterizing and forecasting electricity price volatility," International Journal of Forecasting, Elsevier, vol. 24(4), pages 728-743.
    94. Mark Podolskij & Mathias Vetter, 2009. "Understanding limit theorems for semimartingales: a short survey," CREATES Research Papers 2009-47, Department of Economics and Business Economics, Aarhus University.
    95. Yi-Ting Chen & Wan-Ni Lai & Edward W. Sun, 2019. "Jump Detection and Noise Separation by a Singular Wavelet Method for Predictive Analytics of High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 809-844, August.
    96. Gabriel P. Mathy, 2014. "Uncertainty Shocks and Equity Return Jumps and Volatility During the Great Depression," Working Papers 2014-02, American University, Department of Economics.
    97. Mark Podolskij & Mathias Vetter, 2007. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," CREATES Research Papers 2007-27, Department of Economics and Business Economics, Aarhus University.
    98. Eric Jondeau & Jérôme Lahaye & Michael Rockinger, 2013. "Estimating the Price Impact of Trades in an High-Frequency Microstructure Model with Jumps," Swiss Finance Institute Research Paper Series 13-47, Swiss Finance Institute, revised Feb 2016.
    99. Jacod, Jean & Klüppelberg, Claudia & Müller, Gernot, 2017. "Testing for non-correlation between price and volatility jumps," Journal of Econometrics, Elsevier, vol. 197(2), pages 284-297.
    100. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    101. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.
    102. Charles S. Bos & Phillip Gould, 2007. "Dynamic Correlations and Optimal Hedge Ratios," Tinbergen Institute Discussion Papers 07-025/4, Tinbergen Institute.
    103. Ole Barndorff-Nielsen & Svend Erik Graversen & Jean Jacod & Mark Podolskij & Neil Shephard, 2004. "A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales," Economics Papers 2004-W29, Economics Group, Nuffield College, University of Oxford.
    104. Benjamin Yibin Zhang & Hao Zhou & Haibin Zhu, 2009. "Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5099-5131, December.
    105. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    106. Adam Canopius, 2006. "Practitioners' Corner," Journal of Financial Econometrics, Oxford University Press, vol. 4(2), pages 346-351.
    107. Marcelo Fernandes & Ms. Deniz O Igan & Marcelo Pinheiro, 2015. "March Madness in Wall Street: (What) Does the Market Learn from Stress Tests?," IMF Working Papers 2015/271, International Monetary Fund.
    108. Arouri, Mohamed El Hedi & M’saddek, Oussama & Nguyen, Duc Khuong & Pukthuanthong, Kuntara, 2017. "Cojumps and Asset Allocation in International Equity Markets," MPRA Paper 89938, University Library of Munich, Germany, revised May 2018.
    109. Mohammad Al-Shboul & Aktham Maghyereh, 2023. "Did real economic uncertainty drive risk connectedness in the oil–stock nexus during the COVID-19 outbreak? A partial wavelet coherence analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-23, December.
    110. Julien Chevallier & Benoît Sévi, 2012. "On the Stochastic Properties of Carbon Futures Prices," Working Papers halshs-00720166, HAL.
    111. Zhou, Haigang & Zhu, John Qi, 2019. "Firm characteristics and jump dynamics in stock prices around earnings announcements," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    112. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk-realised semivariance," Economics Papers 2008-W02, Economics Group, Nuffield College, University of Oxford.
    113. Fan, Yingying & Fan, Jianqing, 2011. "Testing and detecting jumps based on a discretely observed process," Journal of Econometrics, Elsevier, vol. 164(2), pages 331-344, October.
    114. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model," CREATES Research Papers 2013-03, Department of Economics and Business Economics, Aarhus University.
    115. Jiang, George J. & Zhu, Kevin X., 2017. "Information Shocks and Short-Term Market Underreaction," Journal of Financial Economics, Elsevier, vol. 124(1), pages 43-64.
    116. Tang, Yusui & Ma, Feng, 2023. "The volatility of natural resources implications for sustainable development: Crude oil volatility prediction based on the multivariate structural regime switching," Resources Policy, Elsevier, vol. 83(C).
    117. Federico M. Bandi & Roberto Reno, 2009. "Nonparametric Stochastic Volatility," Global COE Hi-Stat Discussion Paper Series gd08-035, Institute of Economic Research, Hitotsubashi University.
    118. Jérôme Lahaye & Christopher Neely, 2020. "The Role of Jumps in Volatility Spillovers in Foreign Exchange Markets: Meteor Shower and Heat Waves Revisited," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 410-427, April.
    119. Yusaku Nishimura & Xuyi Dong & Bianxia Sun, 2021. "Trump's tweets: Sentiment, stock market volatility, and jumps," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 44(3), pages 497-512, September.
    120. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.
    121. Julien Chevallier & Benoît Sévi, 2012. "On the volatility-volume relationship in energy futures markets using intraday data," Post-Print hal-00988926, HAL.
    122. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
    123. Audrino, Francesco & Hu, Yujia, 2011. "Volatility Forecasting: Downside Risk, Jumps and Leverage Effect," Economics Working Paper Series 1138, University of St. Gallen, School of Economics and Political Science.
    124. Jui‐Cheng Hung & Hung‐Chun Liu & J. Jimmy Yang, 2023. "Does the tail risk index matter in forecasting downside risk?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3451-3466, July.
    125. Nicholas Bloom, 2007. "The Impact of Uncertainty Shocks," NBER Working Papers 13385, National Bureau of Economic Research, Inc.
    126. Taesuk Lee & Mico Loretan & Werner Ploberger, 2013. "Rate-optimal tests for jumps in diffusion processes," Statistical Papers, Springer, vol. 54(4), pages 1009-1041, November.
    127. Souček, Michael & Todorova, Neda, 2014. "Realized volatility transmission: The role of jumps and leverage effects," Economics Letters, Elsevier, vol. 122(2), pages 111-115.
    128. Yao, Wenying & Tian, Jing, 2015. "The role of intra-day volatility pattern in jump detection: empirical evidence on how financial markets respond to macroeconomic news announcements," Working Papers 2015-05, University of Tasmania, Tasmanian School of Business and Economics.
    129. Jeong, Daehee & Kim, Hwagyun & Park, Joon Y., 2015. "Does ambiguity matter? Estimating asset pricing models with a multiple-priors recursive utility," Journal of Financial Economics, Elsevier, vol. 115(2), pages 361-382.
    130. Todorov, Viktor & Bollerslev, Tim, 2010. "Jumps and betas: A new framework for disentangling and estimating systematic risks," Journal of Econometrics, Elsevier, vol. 157(2), pages 220-235, August.
    131. Cui, Jinxin & Maghyereh, Aktham & Goh, Mark & Zou, Huiwen, 2022. "Risk spillovers and time-varying links between international oil and China’s commodity futures markets: Fresh evidence from the higher-order moments," Energy, Elsevier, vol. 238(PB).
    132. Chen, Wang & Lu, Xinjie & Wang, Jiqian, 2022. "Modeling and managing stock market volatility using MRS-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 625-635.
    133. Aït-Sahalia, Yacine & Xiu, Dacheng, 2016. "Increased correlation among asset classes: Are volatility or jumps to blame, or both?," Journal of Econometrics, Elsevier, vol. 194(2), pages 205-219.
    134. Diep Duong & Norman Swanson, 2013. "Empirical Evidence on the Importance of Aggregation, Asymmetry, and Jumps for Volatility Prediction," Departmental Working Papers 201321, Rutgers University, Department of Economics.
    135. Ole E. Barndorff-Nielsen & Neil Shephard & Matthias Winkel, 2005. "Limit theorems for multipower variation in the presence of jumps," OFRC Working Papers Series 2005fe06, Oxford Financial Research Centre.
    136. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, Center for Economic and Financial Research (CEFIR).
    137. Filip Zikes & Jozef Barunik, 2013. "Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility," Papers 1308.4276, arXiv.org.
    138. Kim Christensen & Mark Podolskij & Mathias Vetter, 2009. "Bias-correcting the realized range-based variance in the presence of market microstructure noise," Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
    139. Yuewen Xiao & Xiangkang Yin & Jing Zhao, 2020. "Jumps, News, And Subsequent Return Dynamics: An Intraday Study," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 705-731, August.
    140. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    141. Bilel Sanhaji & Julien Chevallier, 2023. "Tracking ‘Pure’ Systematic Risk with Realized Betas for Bitcoin and Ethereum," Post-Print hal-04218488, HAL.
    142. Ralf Becker & Adam Clements & Robert O'Neill, 2010. "A Cholesky-MIDAS model for predicting stock portfolio volatility," Centre for Growth and Business Cycle Research Discussion Paper Series 149, Economics, The University of Manchester.
    143. Wen, Zhuzhu & Bouri, Elie & Xu, Yahua & Zhao, Yang, 2022. "Intraday return predictability in the cryptocurrency markets: Momentum, reversal, or both," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    144. Shaliastovich, Ivan, 2015. "Learning, confidence, and option prices," Journal of Econometrics, Elsevier, vol. 187(1), pages 18-42.
    145. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
    146. Dimitrios I. Vortelinos, 2015. "The Effect of Macro News on Volatility and Jumps," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 425-447, November.
    147. Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2019. "Asset prices and “the devil(s) you know”," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 20-35.
    148. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight momentum, informational shocks, and late informed trading in China," International Review of Financial Analysis, Elsevier, vol. 66(C).
    149. Jim Griffin & Jia Liu & John M. Maheu, 2021. "Bayesian Nonparametric Estimation of Ex Post Variance [Out of Sample Forecasts of Quadratic Variation]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 823-859.
    150. Hanousek, Jan & Novotný, Jan, 2012. "Price jumps in Visegrad-country stock markets: An empirical analysis," Emerging Markets Review, Elsevier, vol. 13(2), pages 184-201.
    151. Xin Zhang & Donggyu Kim & Yazhen Wang, 2016. "Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets," Econometrics, MDPI, vol. 4(3), pages 1-26, August.
    152. Ding, Y., 2021. "Augmented Real-Time GARCH: A Joint Model for Returns, Volatility and Volatility of Volatility," Cambridge Working Papers in Economics 2112, Faculty of Economics, University of Cambridge.
    153. Maciej Kostrzewski, 2014. "Bayesian DEJD model and detection of asymmetric jumps," Papers 1404.2050, arXiv.org.
    154. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    155. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford.
    156. Lin, Tiantian & Liu, Dehong & Zhang, Lili & Lung, Peter, 2019. "The information content of realized volatility of sector indices in China’s stock market," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 625-640.
    157. Federico A. Bugni & Jia Li & Qiyuan Li, 2023. "Permutation‐based tests for discontinuities in event studies," Quantitative Economics, Econometric Society, vol. 14(1), pages 37-70, January.
    158. Youcong Chao & Xiaoqun Liu & Shijun Guo, 2017. "Sign realized jump risk and the cross-section of stock returns: Evidence from China's stock market," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-14, August.
    159. Liao, Yin & Anderson, Heather M., 2019. "Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
    160. Jos'e E. Figueroa-L'opez & Yankeng Luo & Cheng Ouyang, 2011. "Small-time expansions for local jump-diffusion models with infinite jump activity," Papers 1108.3386, arXiv.org, revised Jul 2014.
    161. Balcilar, Mehmet & Bonato, Matteo & Demirer, Riza & Gupta, Rangan, 2017. "The effect of investor sentiment on gold market return dynamics: Evidence from a nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 51(C), pages 77-84.
    162. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2013. "Modelling systemic price cojumps with Hawkes factor models," Papers 1301.6141, arXiv.org, revised Mar 2013.
    163. Égert, Balázs & Kočenda, Evžen, 2014. "The impact of macro news and central bank communication on emerging European forex markets," Economic Systems, Elsevier, vol. 38(1), pages 73-88.
    164. Jean Jacod & Viktor Todorov, 2010. "Do price and volatility jump together?," Papers 1010.4990, arXiv.org.
    165. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2021. "Exploring volatility of crude oil intra-day return curves: a functional GARCH-X Model," MPRA Paper 109231, University Library of Munich, Germany.
    166. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    167. Michael S. Johannes & Nicholas G. Polson & Jonathan R. Stroud, 2009. "Optimal Filtering of Jump Diffusions: Extracting Latent States from Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2559-2599, July.
    168. Arnerić Josip, 2020. "Realized density estimation using intraday prices," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 1-9, May.
    169. Nekhili, Ramzi & Bouri, Elie, 2023. "Higher-order moments and co-moments' contribution to spillover analysis and portfolio risk management," Energy Economics, Elsevier, vol. 119(C).
    170. Dumitru, Ana-Maria & Urga, Giovanni, 2016. "Jumps and Information Asymmetry in the US Treasury Market," EconStor Preprints 130148, ZBW - Leibniz Information Centre for Economics.
    171. Zhihong Jian & Zhican Zhu & Jie Zhou & Shuai Wu, 2018. "The Magnet Effect of Circuit Breakers: A role of price jumps and market liquidity," Departmental Working Papers 2018-01, The University of Winnipeg, Department of Economics.
    172. Zhang, Chuanhai & Ma, Huan & Arkorful, Gideon Bruce & Peng, Zhe, 2023. "The impacts of futures trading on volatility and volatility asymmetry of Bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 86(C).
    173. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2014. "A Robust Neighborhood Truncation Approach To Estimation Of Integrated Quarticity," Econometric Theory, Cambridge University Press, vol. 30(1), pages 3-59, February.
    174. Yin Liao & Heather M. Anderson & Farshid Vahid, 2010. "Do Jumps Matter? Forecasting Multivariate Realized Volatility allowing for Common Jumps," Monash Econometrics and Business Statistics Working Papers 11/10, Monash University, Department of Econometrics and Business Statistics.
    175. Tai‐Yong Roh & Alireza Tourani‐Rad & Yahua Xu & Yang Zhao, 2021. "Volatility‐of‐volatility risk in the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 245-265, February.
    176. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    177. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    178. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    179. Liu, Yuna, 2016. "Essays on Stock Market Integration - On Stock Market Efficiency, Price Jumps and Stock Market Correlations," Umeå Economic Studies 926, Umeå University, Department of Economics.
    180. Hui Qu & Tianyang Wang & Peng Shangguan & Mengying He, 2024. "Revisiting the puzzle of jumps in volatility forecasting: The new insights of high‐frequency jump intensity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 218-251, February.
    181. Caporin, Massimiliano & Kolokolov, Alexey & Renò, Roberto, 2016. "Systemic co-jumps," SAFE Working Paper Series 149, Leibniz Institute for Financial Research SAFE.
    182. Torben G. Andersen & Oleg Bondarenko & Viktor Todorov & George Tauchen, 2013. "The Fine Structure of Equity-Index Option Dynamics," CREATES Research Papers 2013-52, Department of Economics and Business Economics, Aarhus University.
    183. Johannes Stübinger & Lucas Schneider, 2019. "Statistical Arbitrage with Mean-Reverting Overnight Price Gaps on High-Frequency Data of the S&P 500," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    184. Liu, Xiaoqun & Zhang, Yuchen & Tian, Mengqiao & Chao, Youcong, 2023. "Financial distress and jump tail risk: Evidence from China's listed companies," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 316-336.
    185. Dräger, Lena & Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The Long Memory of Equity Volatility and the Macroeconomy: International Evidence," Hannover Economic Papers (HEP) dp-667, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    186. Neil Shephard, 2005. "Stochastic Volatility," Economics Papers 2005-W17, Economics Group, Nuffield College, University of Oxford.
    187. Jean-Yves Gnabo & J�rôme Lahaye & S�bastien Laurent & Christelle Lecourt, 2012. "Do jumps mislead the FX market?," Quantitative Finance, Taylor & Francis Journals, vol. 12(10), pages 1521-1532, October.
    188. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    189. Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2020. "Do Bitcoin and other cryptocurrencies jump together?," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 396-409.
    190. Fu, Jin-Yu & Lin, Jin-Guan & Hao, Hong-Xia, 2023. "Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1698-1712.
    191. Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 5-31.
    192. John Elder, Hong Miao, and Sanjay Ramchander, 2013. "Jumps in Oil Prices: The Role of Economic News," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    193. Alexander Alvarez & Fabien Panloup & Monique Pontier & Nicolas Savy, 2012. "Estimation of the instantaneous volatility," Statistical Inference for Stochastic Processes, Springer, vol. 15(1), pages 27-59, April.
    194. Hanousek Jan & Kočenda Evžen & Novotný Jan, 2012. "The identification of price jumps," Monte Carlo Methods and Applications, De Gruyter, vol. 18(1), pages 53-77, January.
    195. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2006. "The Information Content Of Treasury Bond Options Concerning Future Volatility And Price Jumps," Working Paper 1188, Economics Department, Queen's University.
    196. Adam D. Bull, 2013. "Estimating time-changes in noisy L\'evy models," Papers 1312.5911, arXiv.org, revised Nov 2014.
    197. Lu, Xinjie & Ma, Feng & Wang, Jianqiong & Dong, Dayong, 2022. "Singlehanded or joint race? Stock market volatility prediction," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 734-754.
    198. Maciej Kostrzewski & Jadwiga Kostrzewska, 2021. "The Impact of Forecasting Jumps on Forecasting Electricity Prices," Energies, MDPI, vol. 14(2), pages 1-17, January.
    199. Hussain, Syed Mujahid & Ahmad, Nisar & Ahmed, Sheraz, 2023. "Applications of high-frequency data in finance: A bibliometric literature review," International Review of Financial Analysis, Elsevier, vol. 89(C).
    200. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Long Memory of Equity Volatility: International Evidence," Hannover Economic Papers (HEP) dp-614, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    201. Barunik, Jozef & Barunikova, Michaela, 2015. "Revisiting the long memory dynamics of implied-realized volatility relation: A new evidence from wavelet band spectrum regression," FinMaP-Working Papers 43, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    202. Almut E. D. Veraart, 2010. "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?," CREATES Research Papers 2010-65, Department of Economics and Business Economics, Aarhus University.
    203. Shabir A A Saleem & Peter N Smith & Abdullah Yalaman, 2021. "Analysis of systematic risk around firm-specific news in an emerging market using high frequency data," CAMA Working Papers 2021-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    204. Angelo Ranaldo & Paul Söderlind, 2007. "Safe Haven Currencies," Working Papers 2007-17, Swiss National Bank.
    205. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    206. Li, Gang & Zhang, Chu, 2016. "On the relationship between conditional jump intensity and diffusive volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 196-213.
    207. Bruce Mizrach, 2007. "Recovering Probabilistic Information From Options Prices and the Underlying," Departmental Working Papers 200702, Rutgers University, Department of Economics.
    208. Frowin Schulz & Karl Mosler, 2011. "The effect of infrequent trading on detecting price jumps," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 27-58, March.
    209. Gabriel Natividad & Olav Sorenson, 2015. "Competitive Threats, Constraint, and Contagion in the Multiunit Firm," Organization Science, INFORMS, vol. 26(6), pages 1721-1733, December.
    210. Degiannakis, Stavros & Filis, George, 2023. "Oil price assumptions for macroeconomic policy," Energy Economics, Elsevier, vol. 117(C).
    211. Schulz, Frowin C., 2010. "Explaining time-varying risk of electricity forwards: trading activity and news announcements," Discussion Papers in Econometrics and Statistics 8/10, University of Cologne, Institute of Econometrics and Statistics.
    212. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 Volatility Using Ultra-high Frequency Data," MPRA Paper 80445, University Library of Munich, Germany.
    213. Jian, Zhihong & Zhu, Zhican & Zhou, Jie & Wu, Shuai, 2020. "Intraday price jumps, market liquidity, and the magnet effect of circuit breakers," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 168-186.
    214. Cheng Jiang & Kose John & David Larsen, 2021. "R&D investment intensity and jump volatility of stock price," Review of Quantitative Finance and Accounting, Springer, vol. 57(1), pages 235-277, July.
    215. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    216. Yuping Song & Weijie Hou & Zhengyan Lin, 2022. "Double Smoothed Volatility Estimation of Potentially Non‐stationary Jump‐diffusion Model of Shibor," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 53-82, January.
    217. Scharth, Marcel & Medeiros, Marcelo C., 2009. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," International Journal of Forecasting, Elsevier, vol. 25(2), pages 304-327.
    218. PeiLin Hsieh & QinQin Zhang & Yajun Wang, 2018. "Jump risk and option liquidity in an incomplete market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1334-1369, November.
    219. Niu, Zilong, 2020. "Essays in empirical asset pricing and international finance," Other publications TiSEM 986cefd5-4d2b-4d5f-be7a-2, Tilburg University, School of Economics and Management.
    220. Figueroa-López, José E. & Nisen, Jeffrey, 2013. "Optimally thresholded realized power variations for Lévy jump diffusion models," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2648-2677.
    221. Bonato, Matteo & Gupta, Rangan & Lau, Chi Keung Marco & Wang, Shixuan, 2020. "Moments-based spillovers across gold and oil markets," Energy Economics, Elsevier, vol. 89(C).
    222. Scaillet, Olivier & Treccani, Adrien & Trevisan, Christopher, 2017. "High-frequency jump analysis of the bitcoin market," Working Papers unige:93900, University of Geneva, Geneva School of Economics and Management.
    223. Grobys, Klaus & Huynh, Toan Luu Duc, 2022. "When Tether says “JUMP!” Bitcoin asks “How low?”," Finance Research Letters, Elsevier, vol. 47(PA).
    224. Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 94289, University Library of Munich, Germany.
    225. Alexeev, Vitali & Dungey, Mardi & Yao, Wenying, 2017. "Time-varying continuous and jump betas: The role of firm characteristics and periods of stress," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 1-19.
    226. Silja Kinnebrock & Mark Podolskij, 2007. "A Note on the Central Limit Theorem for Bipower Variation of General Functions," OFRC Working Papers Series 2007fe03, Oxford Financial Research Centre.
    227. Linton, Oliver & Whang, Yoon-Jae & Yen, Yu-Min, 2016. "A nonparametric test of a strong leverage hypothesis," Journal of Econometrics, Elsevier, vol. 194(1), pages 153-186.
    228. Adam Aleksander Majewski & Giacomo Bormetti & Fulvio Corsi, 2014. "Smile from the Past: A general option pricing framework with multiple volatility and leverage components," Papers 1404.3555, arXiv.org.
    229. Benoît Sévi & César Baena, 2013. "The explanatory power of signed jumps for the risk-return tradeoff," Economics Bulletin, AccessEcon, vol. 33(2), pages 1029-1046.
    230. Prodromou, Tina & Westerholm, P. Joakim, 2022. "Are high frequency traders responsible for extreme price movements?," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 94-111.
    231. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    232. Patton, Andrew J. & Sheppard, Kevin, 2009. "Optimal combinations of realised volatility estimators," International Journal of Forecasting, Elsevier, vol. 25(2), pages 218-238.
    233. Gongyue Jiang & Gaoxiu Qiao & Feng Ma & Lu Wang, 2022. "Directly pricing VIX futures with observable dynamic jumps based on high‐frequency VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1518-1548, August.
    234. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    235. Jing, Bing-Yi & Kong, Xin-Bing & Liu, Zhi & Mykland, Per, 2012. "On the jump activity index for semimartingales," Journal of Econometrics, Elsevier, vol. 166(2), pages 213-223.
    236. Benoît Sévi & César Baena, 2011. "Brownian motion vs. pure-jump processes for individual stocks," Economics Bulletin, AccessEcon, vol. 31(4), pages 3138-3152.
    237. Shixuan Wang & Rangan Gupta & Matteo Bonato & Oguzhan Cepni, 2022. "The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks," Working Papers 202219, University of Pretoria, Department of Economics.
    238. Ye, Xu-Guo & Lin, Jin-Guan & Zhao, Yan-Yong & Hao, Hong-Xia, 2015. "Two-step estimation of the volatility functions in diffusion models with empirical applications," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 135-159.
    239. Hellström, Jörgen & Lönnbark, Carl, 2011. "Identi�cation of jumps in �financial price series," MPRA Paper 30977, University Library of Munich, Germany.
    240. Mingmian Cheng & Norman R. Swanson, 2019. "Fixed and Long Time Span Jump Tests: New Monte Carlo and Empirical Evidence," Econometrics, MDPI, vol. 7(1), pages 1-32, March.
    241. Giacomo Toscano & Maria Cristina Recchioni, 2022. "Bias-optimal vol-of-vol estimation: the role of window overlapping," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 137-185, June.
    242. Wang, Hao & Yue, Mengqi & Zhao, Hua, 2015. "Cojumps in China's spot and stock index futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 541-557.
    243. Masato Ubukata, 2022. "A time-varying jump tail risk measure using high-frequency options data," Empirical Economics, Springer, vol. 63(5), pages 2633-2653, November.
    244. Konstantinos Gkillas & Rangan Gupta & Chi Keung Marco Lau & Tahir Suleman, 2018. "Jumps Beyond the Realms of Cricket: India’s Performance in One Day Internationals and Stock Market Movements," Working Papers 201871, University of Pretoria, Department of Economics.
    245. BOUDT, Kris & PETITJEAN, Mikael, 2014. "Intraday liquidity dynamics and news releases around price jumps: evidence from the DJIA stocks," LIDAM Reprints CORE 2591, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    246. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01442618, HAL.
    247. Wu, Feng & Myers, Robert J. & Guan, Zhengfei & Wang, Zhiguang, 2015. "Risk-adjusted implied volatility and its performance in forecasting realized volatility in corn futures prices," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 260-274.
    248. Charles S. Bos & Paweł Janus & Siem Jan Koopman, 2012. "Spot Variance Path Estimation and Its Application to High-Frequency Jump Testing," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 354-389, 2012 06.
    249. Chen, Chin-Ho, 2019. "Downside jump risk and the levels of futures-cash basis," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    250. Fulvio Corsi & Davide Pirino & Roberto Reno', 2010. "Threshold Bipower Variation and the Impact of Jumps on Volatility Forecasting," LEM Papers Series 2010/11, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    251. Pirino, Davide, 2009. "Jump detection and long range dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1150-1156.
    252. Asgharian, Hossein & Nossman, Marcus, 2011. "Risk contagion among international stock markets," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 22-38, February.
    253. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    254. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of International REITs: The Role of Realized Skewness and Realized Kurtosis," Working Papers 202114, University of Pretoria, Department of Economics.
    255. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
    256. Jiang, George J. & Oomen, Roel C.A., 2008. "Testing for jumps when asset prices are observed with noise-a "swap variance" approach," Journal of Econometrics, Elsevier, vol. 144(2), pages 352-370, June.
    257. Ravi Bansal & Ivan Shaliastovich, 2009. "Learning and Asset-Price Jumps," NBER Working Papers 14814, National Bureau of Economic Research, Inc.
    258. Anders Eriksson, 2010. "A Levy process for the GNIG probability law with 2nd order stochastic volatility and applications to option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 10(1), pages 75-90.
    259. Becker, Ralf & Clements, Adam E. & McClelland, Andrew, 2009. "The jump component of S&P 500 volatility and the VIX index," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1033-1038, June.
    260. Julien Chevallier & Benoît Sévi, 2011. "On the volatility-volume relationship in energy futures markets using intraday data," Working Papers hal-04140997, HAL.
    261. Mohammad Abu Sayeed & Mardi Dungey & Wenying Yao, 2018. "High-frequency Characterisation of Indian Banking Stocks," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2_suppl), pages 213-238, August.
    262. Gajurel, Dinesh & Chowdhury, Biplob, 2020. "Realized volatility, jump and beta: evidence from Canadian stock market," Working Papers 2020-11, University of Tasmania, Tasmanian School of Business and Economics.
    263. G.M. Gallo & D. Lacava & E. Otranto, 2023. "Volatility jumps and the classification of monetary policy announcements," Working Paper CRENoS 202306, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    264. Gabriel Natividad & Olav Sorenson, 2011. "Spread Too Thin: Uncertainty Shocks and Diseconomies of Scope," Working Papers 11-04, NET Institute.
    265. Simon Clinet & Yoann Potiron, 2021. "Estimation for high-frequency data under parametric market microstructure noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
    266. Tim Bollerslev & Viktor Todorov, 2011. "Estimation of Jump Tails," Econometrica, Econometric Society, vol. 79(6), pages 1727-1783, November.
    267. González-Urteaga, Ana & Muga, Luis & Santamaria, Rafael, 2015. "Momentum and default risk. Some results using the jump component," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 185-193.
    268. Liu, Yuna, 2016. "Stock exchange integration and price jump risks - The case of the OMX Nordic exchange mergers," Umeå Economic Studies 925, Umeå University, Department of Economics.
    269. Huang, Darien & Schlag, Christian & Shaliastovich, Ivan & Thimme, Julian, 2018. "Volatility-of-volatility risk," SAFE Working Paper Series 210, Leibniz Institute for Financial Research SAFE.
    270. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2021. "El Nino, La Nina, and Forecastability of the Realized Variance of Agricultural Commodity Prices: Evidence from a Machine Learning Approach," Working Papers 202179, University of Pretoria, Department of Economics.
    271. Liu, Zhenya & Lu, Shanglin & Li, Bo & Wang, Shixuan, 2023. "Time series momentum and reversal: Intraday information from realized semivariance," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 54-77.
    272. Deniz Erdemlioglu & Sebastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    273. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.
    274. Zhang, Chuanhai & Liu, Zhi & Liu, Qiang, 2021. "Jumps at ultra-high frequency: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    275. Garcia, René & Renault, Eric & Veredas, David, 2011. "Estimation of stable distributions by indirect inference," Journal of Econometrics, Elsevier, vol. 161(2), pages 325-337, April.
    276. Nirei, Makoto & Sushko, Vladyslav, 2011. "Jumps in foreign exchange rates and stochastic unwinding of carry trades," International Review of Economics & Finance, Elsevier, vol. 20(1), pages 110-127, January.
    277. Ghosh, Anisha & Linton, Oliver, 2009. "Consistent estimation of the risk-return tradeoff in the presence of measurement error," UC3M Working papers. Economics we094928, Universidad Carlos III de Madrid. Departamento de Economía.
    278. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.
    279. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, Department of Economics and Business Economics, Aarhus University.
    280. Ole E. Barndorff-Nielsen & Almut E. D. Veraart, 2009. "Stochastic volatility of volatility in continuous time," CREATES Research Papers 2009-25, Department of Economics and Business Economics, Aarhus University.
    281. Atak, Alev & Kapetanios, George, 2013. "A factor approach to realized volatility forecasting in the presence of finite jumps and cross-sectional correlation in pricing errors," Economics Letters, Elsevier, vol. 120(2), pages 224-228.
    282. Degiannakis, Stavros & Filis, George, 2022. "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, vol. 123(C).
    283. Yacine Aït-Sahalia & Julio Cacho-Diaz & Roger J.A. Laeven, 2010. "Modeling Financial Contagion Using Mutually Exciting Jump Processes," NBER Working Papers 15850, National Bureau of Economic Research, Inc.
    284. Bollerslev, Tim & Todorov, Viktor, 2014. "Time-varying jump tails," Journal of Econometrics, Elsevier, vol. 183(2), pages 168-180.
    285. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.
    286. Jawadi, Fredj & Louhichi, Waël & Idi Cheffou, Abdoulkarim, 2015. "Testing and modeling jump contagion across international stock markets: A nonparametric intraday approach," Journal of Financial Markets, Elsevier, vol. 26(C), pages 64-84.
    287. Daniel Borup & Martin Thyrsgaard, 2017. "Statistical tests for equal predictive ability across multiple forecasting methods," CREATES Research Papers 2017-19, Department of Economics and Business Economics, Aarhus University.
    288. Odusami, Babatunde O., 2021. "Volatility jumps and their determinants in REIT returns," Journal of Economics and Business, Elsevier, vol. 113(C).
    289. Watanabe, Toshiaki & Nakajima, Jouchi, 2023. "High-frequency realized stochastic volatility model," Discussion paper series HIAS-E-127, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    290. Sévi, Benoît, 2013. "An empirical analysis of the downside risk-return trade-off at daily frequency," Economic Modelling, Elsevier, vol. 31(C), pages 189-197.
    291. Shu, Yin & Feng, Qianmei & Liu, Hao, 2019. "Using degradation-with-jump measures to estimate life characteristics of lithium-ion battery," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    292. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2020. "Uncertainty due to Infectious Diseases and Forecastability of the Realized Variance of US REITs: A Note," Working Papers 202099, University of Pretoria, Department of Economics.
    293. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    294. Vince Vella & Wing Lon Ng, 2015. "A Dynamic Fuzzy Money Management Approach for Controlling the Intraday Risk‐Adjusted Performance of AI Trading Algorithms," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 22(2), pages 153-178, April.
    295. Chourdakis, Kyriakos & Dotsis, George, 2011. "Maximum likelihood estimation of non-affine volatility processes," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 533-545, June.
    296. Ysusi Carla, 2007. "Multipower Variation Under Market Microstructure Effects," Working Papers 2007-13, Banco de México.
    297. Bjursell, Johan & Gentle, James E. & Wang, George H.K., 2015. "Inventory announcements, jump dynamics, volatility and trading volume in U.S. energy futures markets," Energy Economics, Elsevier, vol. 48(C), pages 336-349.
    298. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian & Yoon, Seong-Min, 2021. "OPEC news and jumps in the oil market," Energy Economics, Elsevier, vol. 96(C).
    299. Cartea, Álvaro & Karyampas, Dimitrios, 2009. "The relationship between the volatility of returns and the number of jumps in financial markets," DEE - Working Papers. Business Economics. WB wb097508, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    300. Vortelinos, Dimitrios I. & Thomakos, Dimitrios D., 2013. "Nonparametric realized volatility estimation in the international equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 34-45.
    301. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "Dynamic asset price jumps and the performance of high frequency tests and measures," Monash Econometrics and Business Statistics Working Papers 14/17, Monash University, Department of Econometrics and Business Statistics.
    302. Zeng, Qing & Lu, Xinjie & Li, Tao & Wu, Lan, 2022. "Jumps and stock market variance during the COVID-19 pandemic: Evidence from international stock markets," Finance Research Letters, Elsevier, vol. 48(C).
    303. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
    304. Pukthuanthong, Kuntara & Roll, Richard, 2012. "Internationally correlated jumps," Working Paper Series 1436, European Central Bank.
    305. Dungey, Mardi & McKenzie, Michael & Smith, L. Vanessa, 2009. "Empirical evidence on jumps in the term structure of the US Treasury Market," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 430-445, June.
    306. Paweł Kliber, 2019. "Continuous and jump changes in prices processes in the selected stock markets," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 54, pages 333-344.
    307. Zhou, Dong-hai & Liu, Xiao-xing & Tang, Chun & Yang, Guang-yi, 2023. "Time-varying risk spillovers in Chinese stock market – New evidence from high-frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    308. Guangying Liu & Meiyao Liu & Jinguan Lin, 2022. "Testing the volatility jumps based on the high frequency data," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 669-694, September.
    309. Torben B. Rasmussen, 2009. "Jump Testing and the Speed of Market Adjustment," CREATES Research Papers 2009-08, Department of Economics and Business Economics, Aarhus University.
    310. Donggyu Kim & Minseog Oh, 2023. "Dynamic Realized Minimum Variance Portfolio Models," Papers 2310.13511, arXiv.org.
    311. Dovonon, Prosper & Gonçalves, Sílvia & Meddahi, Nour, 2013. "Bootstrapping realized multivariate volatility measures," Journal of Econometrics, Elsevier, vol. 172(1), pages 49-65.
    312. Hellström, Jörgen & Lönnbark, Carl, 2011. "Identification of jumps in financial price series," Umeå Economic Studies 827, Umeå University, Department of Economics.
    313. David S. Bates, 2016. "How Crashes Develop: Intradaily Volatility and Crash Evolution," NBER Working Papers 22028, National Bureau of Economic Research, Inc.
    314. Adam Clements & Yin Liao, 2013. "The dynamics of co-jumps, volatility and correlation," NCER Working Paper Series 91, National Centre for Econometric Research.
    315. Huang, Henry H. & Wang, Kent & Wang, Zhanglong, 2016. "A test of efficiency for the S&P 500 index option market using the generalized spectrum method," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 52-70.
    316. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2012. "A nonparametric test of the leverage hypothesis," CeMMAP working papers CWP24/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    317. Viktor Todorov & Yang Zhang, 2022. "Information gains from using short‐dated options for measuring and forecasting volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 368-391, March.
    318. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    319. Christian Palmes & Jeannette H. C. Woerner, 2016. "The Gumbel test and jumps in the volatility process," Statistical Inference for Stochastic Processes, Springer, vol. 19(2), pages 235-258, July.
    320. Turan G. Bali & Armen Hovakimian, 2009. "Volatility Spreads and Expected Stock Returns," Management Science, INFORMS, vol. 55(11), pages 1797-1812, November.
    321. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Memory of Stock Return Volatility: Asset Pricing Implications," Hannover Economic Papers (HEP) dp-613, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    322. Demirer, Riza & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2019. "Time-varying risk aversion and realized gold volatility," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    323. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2020. "Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    324. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    325. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2012. "A nonparametric test of the leverage hypothesis," CeMMAP working papers 24/12, Institute for Fiscal Studies.
    326. Sévi, Benoît, 2015. "Explaining the convenience yield in the WTI crude oil market using realized volatility and jumps," Economic Modelling, Elsevier, vol. 44(C), pages 243-251.
    327. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in Equilibrium Prices and Asymmetric News in Foreign Exchange Markets," Working Papers hal-04141414, HAL.
    328. Chien-Hsiu Lin & Shih-Kuei Lin & An-Chi Wu, 2015. "Foreign exchange option pricing in the currency cycle with jump risks," Review of Quantitative Finance and Accounting, Springer, vol. 44(4), pages 755-789, May.
    329. Song, Xinyu & Kim, Donggyu & Yuan, Huiling & Cui, Xiangyu & Lu, Zhiping & Zhou, Yong & Wang, Yazhen, 2021. "Volatility analysis with realized GARCH-Itô models," Journal of Econometrics, Elsevier, vol. 222(1), pages 393-410.
    330. John Cotter & Stuart Gabriel & Richard Roll, 2011. "Integration and Contagion in US Housing Markets," Working Papers 201131, Geary Institute, University College Dublin.
    331. Jan Pospíšil & Tomáš Sobotka & Philipp Ziegler, 2019. "Robustness and sensitivity analyses for stochastic volatility models under uncertain data structure," Empirical Economics, Springer, vol. 57(6), pages 1935-1958, December.
    332. M. Podolskij & D. Ziggel, 2010. "New tests for jumps in semimartingale models," Statistical Inference for Stochastic Processes, Springer, vol. 13(1), pages 15-41, April.
    333. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.
    334. Kapadia, Nishad & Zekhnini, Morad, 2019. "Do idiosyncratic jumps matter?," Journal of Financial Economics, Elsevier, vol. 131(3), pages 666-692.
    335. Lavička, H. & Lichard, T. & Novotný, J., 2016. "Sand in the wheels or wheels in the sand? Tobin taxes and market crashes," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 328-342.
    336. Minseog Oh & Donggyu Kim, 2021. "Effect of the U.S.--China Trade War on Stock Markets: A Financial Contagion Perspective," Papers 2111.09655, arXiv.org.
    337. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    338. Shuichi Nagata, 2012. "Consistent Estimation of Integrated Volatility Using Intraday Absolute Returns for SV Jump Diffusion Processes," Economics Bulletin, AccessEcon, vol. 32(1), pages 306-314.
    339. Schulz, Frowin C., 2010. "Robust estimation of integrated variance and quarticity under flat price and no trading bias," Discussion Papers in Econometrics and Statistics 4/10, University of Cologne, Institute of Econometrics and Statistics.
    340. Luo, Xin & Tao, Yunqing & Zou, Kai, 2022. "A new measure of realized volatility: Inertial and reverse realized semivariance," Finance Research Letters, Elsevier, vol. 47(PA).
    341. Wen, Zhuzhu & Gong, Xu & Ma, Diandian & Xu, Yahua, 2021. "Intraday momentum and return predictability: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 95(C), pages 374-384.
    342. Wang, Yajing & Liang, Fang & Wang, Tianyi & Huang, Zhuo, 2020. "Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market," Economic Modelling, Elsevier, vol. 87(C), pages 148-157.
    343. Pérez-Rodríguez, Jorge V. & Andrada-Félix, Julián & Rachinger, Heiko, 2021. "Testing the forward volatility unbiasedness hypothesis in exchange rates under long-range dependence," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    344. Aitor Ciarreta & Peru Muniain & Ainhoa Zarraga, 2020. "Realized volatility and jump testing in the Japanese electricity spot market," Empirical Economics, Springer, vol. 58(3), pages 1143-1166, March.
    345. José Figueroa-López, 2012. "Statistical estimation of Lévy-type stochastic volatility models," Annals of Finance, Springer, vol. 8(2), pages 309-335, May.
    346. Kobayashi, Masahito, 2009. "Testing for jumps in the stochastic volatility models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2597-2608.
    347. Wing Hong Chan & Ranjini Jha & Madhu Kalimipalli, 2009. "The Economic Value Of Using Realized Volatility In Forecasting Future Implied Volatility," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 32(3), pages 231-259, September.
    348. Wang, Kent & Liu, Junwei & Liu, Zhi, 2013. "Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1777-1786.
    349. Qiao, Gaoxiu & Teng, Yuxin & Li, Weiping & Liu, Wenwen, 2019. "Improving volatility forecasting based on Chinese volatility index information: Evidence from CSI 300 index and futures markets," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 133-151.
    350. Chao Yu & Yue Fang & Zeng Li & Bo Zhang & Xujie Zhao, 2014. "Non-Parametric Estimation Of High-Frequency Spot Volatility For Brownian Semimartingale With Jumps," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 572-591, November.
    351. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    352. Yang, Ben-Zhang & Yue, Jia & Wang, Ming-Hui & Huang, Nan-Jing, 2019. "Volatility swaps valuation under stochastic volatility with jumps and stochastic intensity," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 73-84.
    353. Xu, Weijun & Liu, Guifang & Li, Hongyi, 2016. "A novel jump diffusion model based on SGT distribution and its applications," Economic Modelling, Elsevier, vol. 59(C), pages 74-92.
    354. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
    355. Tong, Yuan & Wan, Ning & Dai, Xingyu & Bi, Xiaoyi & Wang, Qunwei, 2022. "China's energy stock market jumps: To what extent does the COVID-19 pandemic play a part?," Energy Economics, Elsevier, vol. 109(C).
    356. Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
    357. José E. Figueroa-López & Jeffrey Nisen, 2019. "Second-order properties of thresholded realized power variations of FJA additive processes," Statistical Inference for Stochastic Processes, Springer, vol. 22(3), pages 431-474, October.
    358. Xindan Li & Bing Zhang, 2013. "Spillover and Cojumps Between the U.S. and Chinese Stock Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S2), pages 23-42, March.
    359. Gkillas, Konstantinos & Boako, Gideon & Vortelinos, Dimitrios & Vasiliadis, Lavrentios, 2020. "Non-parametric quantile dependencies between volatility discontinuities and political risk," Finance Research Letters, Elsevier, vol. 32(C).
    360. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    361. Yi, Chae-Deug, 2020. "Jump probability using volatility periodicity filters in US Dollar/Euro exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    362. Bollerslev, Tim & Li, Sophia Zhengzi & Todorov, Viktor, 2016. "Roughing up beta: Continuous versus discontinuous betas and the cross section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 120(3), pages 464-490.
    363. Yang Gao & Chengjie Zhao & Bianxia Sun & Wandi Zhao, 2022. "Effects of investor sentiment on stock volatility: new evidences from multi-source data in China’s green stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-30, December.
    364. BOUSALAM, Issam & HAMZAOUI, Moustapha & ZOUHAYR, Otman, 2016. "Forecasting Daily Stock Volatility Using GARCH-CJ Type Models with Continuous and Jump Variation," MPRA Paper 69636, University Library of Munich, Germany.
    365. Wu, Fan & Wang, Guan-jun & Kong, Xin-bing, 2022. "Inference on common intraday periodicity at high frequencies," Statistics & Probability Letters, Elsevier, vol. 191(C).
    366. Xin Huang, 2015. "Macroeconomic News Announcements, Systemic Risk, Financial Market Volatility and Jumps," Finance and Economics Discussion Series 2015-97, Board of Governors of the Federal Reserve System (U.S.).
    367. Liu, Cheng & Wang, Moming & Xia, Ningning, 2022. "Design-free estimation of integrated covariance matrices for high-frequency data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    368. Vortelinos, Dimitrios I., 2014. "Optimally sampled realized range-based volatility estimators," Research in International Business and Finance, Elsevier, vol. 30(C), pages 34-50.
    369. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
    370. Konstantinos Gkillas & Dimitrios Vortelinos & Christos Floros & Alexandros Garefalakis & Nikolaos Sariannidis, 2020. "Greek sovereign crisis and European exchange rates: effects of news releases and their providers," Annals of Operations Research, Springer, vol. 294(1), pages 515-536, November.
    371. Hu, Genhua & Jiang, Haifeng, 2023. "Time-varying jumps in China crude oil futures market impacted by COVID-19 pandemic," Resources Policy, Elsevier, vol. 82(C).
    372. Diep Duong & Norman R. Swanson, 2011. "Empirical Evidence on Jumps and Large Fluctuations in Individual Stocks," Departmental Working Papers 201116, Rutgers University, Department of Economics.
    373. Fredj Jawadi & Waël Louhichi & Abdoulkarim Idi Cheffou & Rivo Randrianarivony, 2016. "Intraday jumps and trading volume: a nonlinear Tobit specification," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1167-1186, November.
    374. Sensoy, Ahmet & Serdengeçti, Süleyman, 2020. "Impact of portfolio flows and heterogeneous expectations on FX jumps: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 68(C).
    375. Leonidas S. Rompolis & Elias Tzavalis, 2017. "Retrieving risk neutral moments and expected quadratic variation from option prices," Review of Quantitative Finance and Accounting, Springer, vol. 48(4), pages 955-1002, May.
    376. Li, Jianhua & Xu, Jianxiang, 2023. "Does the introduction of market maker improve market quality? Evidence from China's Sci-Tech innovation board," Finance Research Letters, Elsevier, vol. 55(PA).
    377. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    378. Slim, Skander & Dahmene, Meriam, 2016. "Asymmetric information, volatility components and the volume–volatility relationship for the CAC40 stocks," Global Finance Journal, Elsevier, vol. 29(C), pages 70-84.
    379. Papantonis Ioannis & Tzavalis Elias & Agapitos Orestis & Rompolis Leonidas S., 2023. "Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 171-198, April.
    380. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    381. Zhou, Chunyang & Wu, Chongfeng & Wang, Yudong, 2019. "Dynamic portfolio allocation with time-varying jump risk," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 113-124.
    382. John Cotter & Stuart Gabriel & Richard Roll, 2012. "Can Metropolitan Housing Risk be Diversified? A Cautionary Tale from the Recent Boom and Bust," Papers 1208.0371, arXiv.org.
    383. Yin-Wong Cheung & Wenhao Wang, 2020. "Uncovered Interest Rate Parity Redux: Non- Uniform Effects," GRU Working Paper Series GRU_2020_004, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    384. Lee, Suzanne S. & Mykland, Per A., 2012. "Jumps in equilibrium prices and market microstructure noise," Journal of Econometrics, Elsevier, vol. 168(2), pages 396-406.
    385. Li, Jia & Todorov, Viktor & Tauchen, George, 2017. "Adaptive estimation of continuous-time regression models using high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 36-47.
    386. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    387. Johnson, James A. & Medeiros, Marcelo C. & Paye, Bradley S., 2022. "Jumps in stock prices: New insights from old data," Journal of Financial Markets, Elsevier, vol. 60(C).
    388. Vortelinos, Dimitrios I., 2010. "The properties of realized correlation: Evidence from the French, German and Greek equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 273-290, August.
    389. George Jiang & Ingrid Lo & Adrien Verdelhan, 2008. "Information Shocks, Jumps, and Price Discovery -- Evidence from the U.S. Treasury Market," Staff Working Papers 08-22, Bank of Canada.
    390. Ana-Maria Dumitru, 2013. "Bootstrapping tests for jumps with an application to test averaging," School of Economics Discussion Papers 0113, School of Economics, University of Surrey.
    391. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena.
    392. Worapree Maneesoonthorn & Gael M Martin & Catherine S Forbes, 2018. "Dynamic price jumps: The performance of high frequency tests and measures, and the robustness of inference," Monash Econometrics and Business Statistics Working Papers 17/18, Monash University, Department of Econometrics and Business Statistics.
    393. Gong, Xu & Lin, Boqiang, 2019. "Modeling stock market volatility using new HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 194-211.
    394. Todorov, Viktor & Tauchen, George & Grynkiv, Iaryna, 2011. "Realized Laplace transforms for estimation of jump diffusive volatility models," Journal of Econometrics, Elsevier, vol. 164(2), pages 367-381, October.
    395. Tim Bollerslev & Viktor Todorov, 2010. "Jump Tails, Extreme Dependencies, and the Distribution of Stock Returns," CREATES Research Papers 2010-64, Department of Economics and Business Economics, Aarhus University.
    396. Ceylan, Ozcan, 2012. "Time-Varying Volatility Asymmetry: A Conditioned HAR-RV(CJ) EGARCH-M Model," GIAM Working Papers 12-4, Galatasaray University Economic Research Center.
    397. Rene Carmona & Laura Leal, 2021. "Optimal Execution with Quadratic Variation Inventories," Papers 2104.14615, arXiv.org.
    398. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2023. "Exploring volatility of crude oil intraday return curves: A functional GARCH-X model," Journal of Commodity Markets, Elsevier, vol. 32(C).
    399. Ao Kong & Hongliang Zhu & Robert Azencott, 2021. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 416-438, April.
    400. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    401. Fulvio Corsi & Roberto Renò, 2012. "Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 368-380, January.
    402. Lena Cleanthous & Pany Karamanou, 2011. "The ECB Monetary Policy and the Current Financial Crisis," Working Papers 2011-1, Central Bank of Cyprus.
    403. Wang, Yunyan & Zhang, Lixin & Tang, Mingtian, 2012. "Local M-estimation for jump-diffusion processes," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1273-1284.
    404. Vortelinos, Dimitrios I. & Saha, Shrabani, 2016. "The impact of political risk on return, volatility and discontinuity: Evidence from the international stock and foreign exchange markets," Finance Research Letters, Elsevier, vol. 17(C), pages 222-226.
    405. Donggyu Kim & Minseok Shin, 2023. "Volatility models for stylized facts of high‐frequency financial data," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(3), pages 262-279, May.
    406. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.
    407. John, Kose & Li, Jingrui, 2021. "COVID-19, volatility dynamics, and sentiment trading," Journal of Banking & Finance, Elsevier, vol. 133(C).
    408. Jan Hanousek & Jan Novotný, 2014. "Cenové skoky během finanční nejistoty: od intuice k regulační perspektivě [Price Jumps during Financial Crisis: From Intuition to Financial Regulation]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 32-48.
    409. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    410. Majewski, Adam A. & Bormetti, Giacomo & Corsi, Fulvio, 2015. "Smile from the past: A general option pricing framework with multiple volatility and leverage components," Journal of Econometrics, Elsevier, vol. 187(2), pages 521-531.
    411. Caporin, Massimiliano & Kolokolov, Aleksey & Renò, Roberto, 2014. "Multi-jumps," MPRA Paper 58175, University Library of Munich, Germany.
    412. Piyachart Phiromswad & Pattanaporn Chatjuthamard & Sirimon Treepongkaruna & Sabin Srivannaboon, 2021. "Jumps and Cojumps analyses of major and minor cryptocurrencies," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-9, February.
    413. Ji, Qiang & Zhang, Dayong, 2019. "China’s crude oil futures: Introduction and some stylized facts," Finance Research Letters, Elsevier, vol. 28(C), pages 376-380.
    414. Ao Kong & Robert Azencott & Hongliang Zhu & Xindan Li, 2020. "Pattern recognition in micro-trading behaviors before stock price jumps: A framework based on multivariate time series analysis," Papers 2011.04939, arXiv.org, revised Feb 2021.
    415. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    416. Chunyang Zhou & Chongfeng Wu & Weidong Xu, 2020. "Incorporating time‐varying jump intensities in the mean‐variance portfolio decisions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 460-478, March.
    417. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    418. Neil Shephard & Kevin Sheppard, 2012. "Efficient and feasible inference for the components of financial variation using blocked multipower variation," Economics Series Working Papers 593, University of Oxford, Department of Economics.
    419. Xie, Nan & Wang, Zongrun & Chen, Sicen & Gong, Xu, 2019. "Forecasting downside risk in China’s stock market based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 530-541.
    420. Huynh, Toan Luu Duc, 2021. "Does Bitcoin React to Trump’s Tweets?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    421. Weber, Christoph S., 2019. "The effect of central bank transparency on exchange rate volatility," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 165-181.
    422. Jan Novotný & Giovanni Urga, 2018. "Testing for Co-jumps in Financial Markets," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 118-128.
    423. Hwang, Eunju & Shin, Dong Wan, 2014. "A bootstrap test for jumps in financial economics," Economics Letters, Elsevier, vol. 125(1), pages 74-78.
    424. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Business Applications and State-Level Stock Market Realized Volatility: A Forecasting Experiment," Working Papers 202247, University of Pretoria, Department of Economics.
    425. William A. Brock & Steven N. Durlauf, 2009. "Adoption Curves and Social Interactions," NBER Working Papers 15065, National Bureau of Economic Research, Inc.
    426. Qiang Liu & Zhi Liu & Chuanhai Zhang, 2020. "Heteroscedasticity test of high-frequency data with jumps and microstructure noise," Papers 2010.07659, arXiv.org.
    427. Anupam Dutta & Debojyoti Das, 2022. "Forecasting realized volatility: New evidence from time‐varying jumps in VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2165-2189, December.
    428. YI, Chae-Deug, 2023. "Exchange rate volatility and intraday jump probability with periodicity filters using a local robust variance," Finance Research Letters, Elsevier, vol. 55(PA).
    429. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Density Estimators for Daily Volatility Based on the Use of Realized Measures," Departmental Working Papers 200620, Rutgers University, Department of Economics.
    430. Jin-Huei Yeh & Jying-Nan Wang & Chung-Ming Kuan, 2014. "A noise-robust estimator of volatility based on interquantile ranges," Review of Quantitative Finance and Accounting, Springer, vol. 43(4), pages 751-779, November.
    431. Zhang, Yuan-Yuan & Zhang, Yue-Jun, 2022. "The impact of institutional analyst forecast divergence on crude oil market: Evidence from the mixed frequency models," International Review of Financial Analysis, Elsevier, vol. 84(C).
    432. Pierre Bajgrowicz & Olivier Scaillet & Adrien Treccani, 2016. "Jumps in High-Frequency Data: Spurious Detections, Dynamics, and News," Management Science, INFORMS, vol. 62(8), pages 2198-2217, August.
    433. Yin Liao, 2012. "Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction," CAMA Working Papers 2012-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    434. Yu, Chao & Fang, Yue & Zhao, Xujie & Zhang, Bo, 2013. "Kernel filtering of spot volatility in presence of Lévy jumps and market microstructure noise," MPRA Paper 63293, University Library of Munich, Germany, revised 10 Mar 2014.
    435. Hainaut, Donatien, 2016. "Impact of volatility clustering on equity indexed annuities," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 367-381.
    436. Mardi Dungey & Lyudmyla Hvozdyk, 2010. "Cojumping: Evidence from the US Treasury Bond and Futures Markets," NCER Working Paper Series 56, National Centre for Econometric Research, revised 20 Jul 2010.
    437. Elezovic, Suad, 2009. "Functional modelling of volatility in the Swedish limit order book," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2107-2118, April.
    438. Andrey Rafalson, 2012. "Bootstrap inference about integrated volatility (in Russian)," Quantile, Quantile, issue 10, pages 91-108, December.
    439. Dimitrios I. Vortelinos, 2015. "Out‐of‐sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini‐futures markets," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 58-67, November.
    440. Figueroa-López, José E. & Mancini, Cecilia, 2019. "Optimum thresholding using mean and conditional mean squared error," Journal of Econometrics, Elsevier, vol. 208(1), pages 179-210.
    441. Vortelinos, Dimitrios I., 2014. "Non-parametric analysis of equity arbitrage," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 199-216.
    442. Odusami, Babatunde O, 2021. "Forecasting the Value-at-Risk of REITs using realized volatility jump models," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    443. Piccotti, Louis R., 2018. "Jumps, cojumps, and efficiency in the spot foreign exchange market," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 49-67.
    444. Sanjay Sehgal & Neharika Sobti & Florent Diesting, 2021. "Who leads in intraday gold price discovery and volatility connectedness: Spot, futures, or exchange‐traded fund?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1092-1123, July.
    445. Jan Novotny, 2010. "Were Stocks during the Financial Crisis More Jumpy: A Comparative Study," CERGE-EI Working Papers wp416, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    446. Donatien Hainaut, 2016. "A model for interest rates with clustering effects," Post-Print hal-01393994, HAL.
    447. Gnabo, Jean-Yves & Hvozdyk, Lyudmyla & Lahaye, Jérôme, 2014. "System-wide tail comovements: A bootstrap test for cojump identification on the S&P 500, US bonds and currencies," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 147-174.
    448. Ben-zhang Yang & Jia Yue & Ming-hui Wang & Nan-jing Huang, 2018. "Volatility swaps valuation under stochastic volatility with jumps and stochastic intensity," Papers 1805.06226, arXiv.org, revised May 2018.
    449. Dungey, Mardi & Hvozdyk, Lyudmyla, 2010. "Cojumping: Evidence from the US Treasury Bond and Future Markets (Discussion Paper 2010-06)," Working Papers 10450, University of Tasmania, Tasmanian School of Business and Economics, revised 14 Jul 2010.
    450. Frömmel, Michael & Han, Xing & Kratochvil, Stepan, 2014. "Modeling the daily electricity price volatility with realized measures," Energy Economics, Elsevier, vol. 44(C), pages 492-502.
    451. Dion Bongaerts & Richard Roll & Dominik Rösch & Mathijs van Dijk & Darya Yuferova, 2022. "How Do Shocks Arise and Spread Across Stock Markets? A Microstructure Perspective," Management Science, INFORMS, vol. 68(4), pages 3071-3089, April.
    452. Masato Ubukata, 2023. "Variance Risk Premium Components in Japan for Predictability: Evidence from the COVID-19 Pandemic," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 15(8), pages 1-27, August.
    453. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    454. Chan, Kam Fong & Powell, John G. & Treepongkaruna, Sirimon, 2014. "Currency jumps and crises: Do developed and emerging market currencies jump together?," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 132-157.
    455. Li, Meiyu & Gençay, Ramazan & Xue, Yi, 2016. "Is it Brownian or fractional Brownian motion?," Economics Letters, Elsevier, vol. 145(C), pages 52-55.
    456. Wang Pu & Yixiang Chen & Feng Ma, 2016. "Forecasting the realized volatility in the Chinese stock market: further evidence," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3116-3130, July.
    457. Yousaf, Imran & Jareño, Francisco & Esparcia, Carlos, 2022. "Tail connectedness between lending/borrowing tokens and commercial bank stocks," International Review of Financial Analysis, Elsevier, vol. 84(C).
    458. Michal Czerwonko & Stylianos Perrakis, 2016. "Portfolio Selection with Transaction Costs and Jump-Diffusion Asset Dynamics II: Economic Implications," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 1-28, December.
    459. Liu, Guangying & Zhang, Xinsheng, 2011. "Power variation of fractional integral processes with jumps," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 962-972, August.
    460. Dinesh Gajurel & Mardi Dungey & Wenying Yao & Nagaratnam Jeyasreedharan, 2020. "Jump Risk in the US Financial Sector," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 331-349, September.
    461. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    462. Neda Todorova & Michael Soucek & Eduardo Roca, 2015. "Volatility spillovers from international commodity markets to the Australian equity market," Discussion Papers in Finance finance:201505, Griffith University, Department of Accounting, Finance and Economics.
    463. Neil Shephard & Silja Kinnebrock & Ole E. Barndorff-Neilsen, 2008. "Measuring downside risk - realised semivariance," Economics Series Working Papers 382, University of Oxford, Department of Economics.
    464. Christopher Krauss & Klaus Herrmann, 2017. "On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts," JRFM, MDPI, vol. 10(1), pages 1-24, February.
    465. Adamantios Ntakaris & Giorgio Mirone & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Feature Engineering for Mid-Price Prediction with Deep Learning," Papers 1904.05384, arXiv.org, revised Jun 2019.
    466. Aitor Ciarreta & Peru Muniainy & Ainhoa Zarraga, 2017. "Modelling Realized Volatility in Electricity Spot Prices: New insights and Application to the Japanese Electricity Market," ISER Discussion Paper 0991, Institute of Social and Economic Research, Osaka University.
    467. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    468. Chen, Xi & Wang, Junbo & Wu, Chunchi, 2022. "Jump and volatility risk in the cross-section of corporate bond returns," Journal of Financial Markets, Elsevier, vol. 60(C).
    469. Palandri, Alessandro, 2015. "Do negative and positive equity returns share the same volatility dynamics?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 486-505.
    470. Ao Kong & Hongliang Zhu & Robert Azencott, 2019. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Papers 1912.07165, arXiv.org.
    471. Cecilia Mancini, 2009. "Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 270-296, June.
    472. Wymer Clifford R., 2012. "Continuous-Tme Econometrics of Structural Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(2), pages 1-28, April.
    473. Kim, Jihyun & Park, Joon & Wang, Bin, 2020. "Estimation of Volatility Functions in Jump Diffusions Using Truncated Bipower Increments," TSE Working Papers 20-1096, Toulouse School of Economics (TSE).
    474. Adam E Clements & Yin Liao, 2013. "Modeling and forecasting realized volatility: getting the most out of the jump component," NCER Working Paper Series 93, National Centre for Econometric Research.
    475. Ma, Feng & Wei, Yu & Huang, Dengshi & Chen, Yixiang, 2014. "Which is the better forecasting model? A comparison between HAR-RV and multifractality volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 171-180.
    476. Donggyu Kim & Minseok Shin & Yazhen Wang, 2021. "Overnight GARCH-It\^o Volatility Models," Papers 2102.13467, arXiv.org, revised Jun 2022.
    477. Fuertes, Ana-Maria & Izzeldin, Marwan & Kalotychou, Elena, 2009. "On forecasting daily stock volatility: The role of intraday information and market conditions," International Journal of Forecasting, Elsevier, vol. 25(2), pages 259-281.
    478. Bruno Solnik & Thaisiri Watewai, 2016. "International Correlation Asymmetries: Frequent-but-Small and Infrequent-but-Large Equity Returns," PIER Discussion Papers 31, Puey Ungphakorn Institute for Economic Research.
    479. Rama Cont & Cecilia Mancini, 2010. "Nonparametric tests for pathwise properties of semimartingales," Working Papers - Mathematical Economics 2010-02, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    480. Song, Shijia & Li, Handong, 2023. "Is a co-jump in prices a sparse jump?," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    481. Nattapong Laksomya & John G. Powell & Suparatana Tanthanongsakkun & Sirimon Treepongkaruna, 2018. "Are Internet message boards used to facilitate stock price manipulation? Evidence from an emerging market, Thailand," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 275-309, November.
    482. Tseng Tseng-Chan & Chung Huimin & Huang Chin-Sheng, 2009. "Modeling Jump and Continuous Components in the Volatility of Oil Futures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-30, May.
    483. Talpsepp, Tõnn & Rieger, Marc Oliver, 2010. "Explaining asymmetric volatility around the world," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 938-956, December.
    484. Jozef Barunik & Michaela Barunikova, 2012. "Revisiting the fractional cointegrating dynamics of implied-realized volatility relation with wavelet band spectrum regression," Papers 1208.4831, arXiv.org, revised Feb 2013.
    485. Tian, Xiao & Duong, Huu Nhan & Kalev, Petko S., 2019. "Information content of the limit order book for crude oil futures price volatility," Energy Economics, Elsevier, vol. 81(C), pages 584-597.
    486. Ji‐Eun Choi & Dong Wan Shin, 2018. "Forecasts for leverage heterogeneous autoregressive models with jumps and other covariates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 691-704, September.
    487. Ping, Yuan & Li, Rui, 2018. "Forecasting realized volatility based on the truncated two-scales realized volatility estimator (TTSRV): Evidence from China's stock market," Finance Research Letters, Elsevier, vol. 25(C), pages 222-229.
    488. Shi, Xiuhong & Kobayashi, Masahito, 2009. "Testing for jumps in the EGARCH process," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2797-2808.
    489. Bent Jesper Christensen & Petra Posedel, 2010. "The Risk-Return Tradeoff and Leverage Effect in a Stochastic Volatility-in-Mean Model," CREATES Research Papers 2010-50, Department of Economics and Business Economics, Aarhus University.
    490. Benoît Sévi & César Baena, 2012. "A reassessment of the risk-return tradeoff at the daily horizon," Economics Bulletin, AccessEcon, vol. 32(1), pages 190-203.
    491. Dai, Xingyu & Li, Matthew C. & Xiao, Ling & Wang, Qunwei, 2022. "COVID-19 and China commodity price jump behavior: An information spillover and wavelet coherency analysis," Resources Policy, Elsevier, vol. 79(C).
    492. Todorova, Neda & Clements, Adam E., 2018. "The volatility-volume relationship in the LME futures market for industrial metals," Resources Policy, Elsevier, vol. 58(C), pages 111-124.
    493. Ahdi Noomen Ajmi & Roula Inglesi-Lotz, 2021. "Revisiting the Kuznets Curve Hypothesis for Tunisia: Carbon Dioxide vs. Ecological Footprint," Working Papers 202171, University of Pretoria, Department of Economics.
    494. Pattanaporn Chatjuthamard & Pavitra Jindahra & Pattarake Sarajoti & Sirimon Treepongkaruna, 2021. "The effect of COVID‐19 on the global stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4923-4953, September.
    495. Hassan Zada & Huma Maqsood & Shakeel Ahmed & Muhammad Zeb Khan, 2023. "Information shocks, market returns and volatility: a comparative analysis of developed equity markets in Asia," SN Business & Economics, Springer, vol. 3(1), pages 1-22, January.
    496. Ahn, Yongkil & Tsai, Shih-Chuan, 2021. "What factors are associated with stock price jumps in high frequency?," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    497. Wang, Jianxin & Yang, Minxian, 2009. "Asymmetric volatility in the foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 597-615, October.
    498. Ullrich, Carl J., 2012. "Realized volatility and price spikes in electricity markets: The importance of observation frequency," Energy Economics, Elsevier, vol. 34(6), pages 1809-1818.
    499. Evans, Kevin P., 2011. "Intraday jumps and US macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2511-2527, October.
    500. Bin Wu & Pengzhan Chen & Wuyi Ye, 2021. "Jump activity analysis of the equity index and the corresponding volatility: Evidence from the Chinese market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1055-1073, July.
    501. Amengual, Dante & Xiu, Dacheng, 2018. "Resolution of policy uncertainty and sudden declines in volatility," Journal of Econometrics, Elsevier, vol. 203(2), pages 297-315.
    502. Ronald Gallant, A. & Tauchen, George, 2018. "Exact Bayesian moment based inference for the distribution of the small-time movements of an Itô semimartingale," Journal of Econometrics, Elsevier, vol. 205(1), pages 140-155.
    503. Feng Ma & Yu Wei & Wang Chen & Feng He, 2018. "Forecasting the volatility of crude oil futures using high-frequency data: further evidence," Empirical Economics, Springer, vol. 55(2), pages 653-678, September.
    504. Maria Čuljak & Josip Arnerić & Ante Žigman, 2022. "Is Jump Robust Two Times Scaled Estimator Superior among Realized Volatility Competitors?," Mathematics, MDPI, vol. 10(12), pages 1-11, June.
    505. Martin, Ryan & Ouyang, Cheng & Domagni, Francois, 2018. "‘Purposely misspecified’ posterior inference on the volatility of a jump diffusion process," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 106-113.
    506. Song, Xiaodong & Johnson, Paul & Duck, Peter, 2021. "A novel combination of Mycielski–Markov, regime switching and jump diffusion models for solar energy," Applied Energy, Elsevier, vol. 301(C).
    507. Aida Karmous & Heni Boubaker & Lotfi Belkacem, 2021. "Forecasting Volatility for an Optimal Portfolio with Stylized Facts Using Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 461-482, August.
    508. Vortelinos, Dimitrios I. & Lakshmi, Geeta, 2015. "Market risk of BRIC Eurobonds in the financial crisis period," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 295-310.
    509. Sun, Bianxia & Gao, Yang, 2020. "Market liquidity and macro announcement around intraday jumps: Evidence from Chinese stock index futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    510. Qiao, Gaoxiu & Yang, Jiyu & Li, Weiping, 2020. "VIX forecasting based on GARCH-type model with observable dynamic jumps: A new perspective," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    511. Hassan Zada & Arshad Hassan & Wing-Keung Wong, 2021. "Do Jumps Matter in Both Equity Market Returns and Integrated Volatility: A Comparison of Asian Developed and Emerging Markets," Economies, MDPI, vol. 9(2), pages 1-26, June.
    512. Hung, Jui-Cheng, 2015. "Evaluation of realized multi-power variations in minimum variance hedging," Economic Modelling, Elsevier, vol. 51(C), pages 672-679.
    513. Wright, Jonathan H. & Zhou, Hao, 2009. "Bond risk premia and realized jump risk," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2333-2345, December.
    514. Federico A. Bugni & Jia Li & Qiyuan Li, 2020. "Permutation-based tests for discontinuities in event studies," Papers 2007.09837, arXiv.org, revised Jul 2022.
    515. Haigang Zhou & John Zhu, 2011. "Jump risk and cross section of stock returns: evidence from China’s stock market," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 35(3), pages 309-331, July.
    516. Da Fonseca, José & Ignatieva, Katja & Ziveyi, Jonathan, 2016. "Explaining credit default swap spreads by means of realized jumps and volatilities in the energy market," Energy Economics, Elsevier, vol. 56(C), pages 215-228.
    517. Buncic, Daniel & Gisler, Katja I.M., 2017. "The role of jumps and leverage in forecasting volatility in international equity markets," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 1-19.
    518. Todorov, Viktor, 2009. "Estimation of continuous-time stochastic volatility models with jumps using high-frequency data," Journal of Econometrics, Elsevier, vol. 148(2), pages 131-148, February.
    519. Lennart Ante & Ingo Fiedler & Jan Marius Willruth & Fred Steinmetz, 2023. "A Systematic Literature Review of Empirical Research on Stablecoins," FinTech, MDPI, vol. 2(1), pages 1-14, January.
    520. Dumitru, Ana-Maria & Hizmeri, Rodrigo & Izzeldin, Marwan, 2019. "Forecasting the Realized Variance in the Presence of Intraday Periodicity," EconStor Preprints 193631, ZBW - Leibniz Information Centre for Economics.
    521. Panagiotis Delis & Stavros Degiannakis & George Filis, 2022. "What matters when developing oil price volatility forecasting frameworks?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 361-382, March.
    522. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    523. Ignatieva, Katja & Wong, Patrick, 2022. "Modelling high frequency crude oil dynamics using affine and non-affine jump–diffusion models," Energy Economics, Elsevier, vol. 108(C).
    524. Dinesh Gajurel & Biplob Chowdhury, 2021. "Realized Volatility, Jump and Beta: evidence from Canadian Stock Market," Applied Economics, Taylor & Francis Journals, vol. 53(55), pages 6376-6397, November.
    525. Jan Novotn?? & Jan Hanousek & Ev??en Ko??enda, 2013. "Price Jump Indicators: Stock Market Empirics During the Crisis," William Davidson Institute Working Papers Series wp1050, William Davidson Institute at the University of Michigan.
    526. Shimizu, Yasutaka, 2009. "Functional estimation for Lvy measures of semimartingales with Poissonian jumps," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1073-1092, July.
    527. Juho Kanniainen & Ye Yue, 2019. "The Arrival of News and Return Jumps in Stock Markets: A Nonparametric Approach," Papers 1901.02691, arXiv.org.
    528. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay & Villupuram, Sriram, 2014. "Currency jumps, cojumps and the role of macro news," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 42-62.
    529. Jan Posp'iv{s}il & Tom'av{s} Sobotka & Philipp Ziegler, 2019. "Robustness and sensitivity analyses for stochastic volatility models under uncertain data structure," Papers 1912.06709, arXiv.org.
    530. Maciej Kostrzewski, 2012. "Bayesian Pricing of the Optimal-Replication Strategy for European Option in the JD(M)J Model," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 12, pages 53-72.
    531. Behfar, Stefan Kambiz, 2016. "Long memory behavior of returns after intraday financial jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 716-725.
    532. Xin Huang, 2018. "Macroeconomic news announcements, systemic risk, financial market volatility, and jumps," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(5), pages 513-534, May.
    533. Anabelle Couleau & Teresa Serra & Philip Garcia, 2020. "Are Corn Futures Prices Getting “Jumpy”?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 569-588, March.
    534. Yingjie Dong & Yiu-Kuen Tse, 2017. "Business Time Sampling Scheme with Applications to Testing Semi-Martingale Hypothesis and Estimating Integrated Volatility," Econometrics, MDPI, vol. 5(4), pages 1-19, November.
    535. Zhang, Yi & Zhou, Long & Chen, Yajiao & Liu, Fang, 2022. "The contagion effect of jump risk across Asian stock markets during the Covid-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    536. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    537. Zhang, Yiting & Lee, Gladys Hui Ting & Wong, Jian Cheng & Kok, Jun Liang & Prusty, Manamohan & Cheong, Siew Ann, 2011. "Will the US economy recover in 2010? A minimal spanning tree study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2020-2050.
    538. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    539. Diep Duong & Norman R. Swanson, 2011. "Volatility in Discrete and Continuous Time Models: A Survey with New Evidence on Large and Small Jumps," Departmental Working Papers 201117, Rutgers University, Department of Economics.
    540. Jos'e E. Figueroa-L'opez & Cecilia Mancini, 2017. "Optimum thresholding using mean and conditional mean square error," Papers 1708.04339, arXiv.org.
    541. Figueroa-López, José E. & Gong, Ruoting & Houdré, Christian, 2012. "Small-time expansions of the distributions, densities, and option prices of stochastic volatility models with Lévy jumps," Stochastic Processes and their Applications, Elsevier, vol. 122(4), pages 1808-1839.
    542. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.

  25. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Power and bipower variation with stochastic volatility and jumps," Economics Papers 2003-W17, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Yu-Min Yen, 2013. "Testing Jumps via False Discovery Rate Control," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    2. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    3. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    4. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    5. Réveillac, Anthony, 2009. "Estimation of quadratic variation for two-parameter diffusions," Stochastic Processes and their Applications, Elsevier, vol. 119(5), pages 1652-1672, May.
    6. Tim Bollerslev & Viktor Todorov, 2010. "Tails, Fears and Risk Premia," Working Papers 10-33, Duke University, Department of Economics.
    7. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    8. Matteo Bonato & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Investor Happiness and Predictability of the Realized Volatility of Oil Price," Working Papers 202009, University of Pretoria, Department of Economics.
    9. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    10. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
    11. Dette, Holger & Golosnoy, Vasyl & Kellermann, Janosch, 2022. "Correcting Intraday Periodicity Bias in Realized Volatility Measures," Econometrics and Statistics, Elsevier, vol. 23(C), pages 36-52.
    12. Grace Lee Ching Yap, 2020. "Optimal Filter Approximations for Latent Long Memory Stochastic Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 547-568, August.
    13. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    14. Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2017. "Equity index variance: Evidence from flexible parametric jump–diffusion models," Journal of Banking & Finance, Elsevier, vol. 83(C), pages 85-103.
    15. Christopher F. Baum & Mustafa Caglayan & Oleksandr Talavera, 2006. "On the Sensitivity of Firms' Investment to Cash Flow and Uncertainty," Boston College Working Papers in Economics 638, Boston College Department of Economics, revised 26 Apr 2008.
    16. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    17. Yuqian Xu & Lingjiong Zhu & Michael Pinedo, 2020. "Operational Risk Management: A Stochastic Control Framework with Preventive and Corrective Controls," Operations Research, INFORMS, vol. 68(6), pages 1804-1825, November.
    18. Sankar, Ganesh & Ramachandran, Shankar & Lukose P J, Jijo, 2020. "Dynamics of variance risk premium: Evidence from India," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 321-334.
    19. Da Fonseca, José & Ignatieva, Katja, 2019. "Jump activity analysis for affine jump-diffusion models: Evidence from the commodity market," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 45-62.
    20. Nkwoma John Inekwe, 2016. "Financial uncertainty, risk aversion and monetary policy," Empirical Economics, Springer, vol. 51(3), pages 939-961, November.
    21. Vit Bubak, 2010. "Forecasting the Quantiles of Daily Equity Returns Using Realized Volatility: Evidence from the Czech Stock Market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00650666, HAL.
    22. Kakinaka, Shinji & Umeno, Ken, 2021. "Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    23. Jozef Barunik & Lukas Vacha, 2015. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1347-1364, August.
    24. Shahzad, Syed Jawad Hussain & Raza, Naveed & Balcilar, Mehmet & Ali, Sajid & Shahbaz, Muhammad, 2017. "Can economic policy uncertainty and investors sentiment predict commodities returns and volatility?," Resources Policy, Elsevier, vol. 53(C), pages 208-218.
    25. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    26. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    27. Peter Christoffersen & Bruno Feunou & Yoontae Jeon, 2014. "Option Valuation with Observable Volatility and Jump Dynamics," CREATES Research Papers 2015-07, Department of Economics and Business Economics, Aarhus University.
    28. Hecq, A.W. & Lieb, L.M. & Telg, J.M.A., 2015. "Identification of Mixed Causal-Noncausal Models : How Fat Should We Go?," Research Memorandum 035, Maastricht University, Graduate School of Business and Economics (GSBE).
    29. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    30. Viktor Todorov & George Tauchen & Iaryna Grynkiv, 2011. "Volatility Activity: Specification and Estimation," Working Papers 11-23, Duke University, Department of Economics.
    31. Basel M. A. Awartani, 2008. "Forecasting volatility with noisy jumps: an application to the Dow Jones Industrial Average stocks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 267-278.
    32. Ourania Theodosiadou & Sotiris Skaperas & George Tsaklidis, 2017. "Change Point Detection and Estimation of the Two-Sided Jumps of Asset Returns Using a Modified Kalman Filter," Risks, MDPI, vol. 5(1), pages 1-14, March.
    33. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    34. Dufour, Jean-Marie & García, René & Taamouti, Abderrahim, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    35. Podolskij, Mark & Vetter, Mathias, 2008. "Bipower-type estimation in a noisy diffusion setting," Technical Reports 2008,24, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    36. Doureige J. Jurdi, 2020. "Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    37. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    38. Lahiri, Ananya & Sen, Rituparna, 2020. "Fractional Brownian markets with time-varying volatility and high-frequency data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 91-107.
    39. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    40. Xu, Weiju & Ma, Feng & Chen, Wang & Zhang, Bing, 2019. "Asymmetric volatility spillovers between oil and stock markets: Evidence from China and the United States," Energy Economics, Elsevier, vol. 80(C), pages 310-320.
    41. Virgil DAMIAN & Cosmin – Octavian CEPOI, 2016. "Volatility Estimators With High-Frequency Data From Bucharest Stock Exchange," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 247-264.
    42. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01411808, HAL.
    43. Lee, Hwang Hee & Hyun, Jung-Soon, 2019. "The asymmetric effect of equity volatility on credit default swap spreads," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 125-136.
    44. Vacca, Gianmarco & Zoia, Maria Grazia & Bagnato, Luca, 2022. "Forecasting in GARCH models with polynomially modified innovations," International Journal of Forecasting, Elsevier, vol. 38(1), pages 117-141.
    45. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and state-level stock market realized volatility," Journal of Financial Markets, Elsevier, vol. 66(C).
    46. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    47. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "High-Frequency Jump Tests: Which Test Should We Use?," Papers 1708.09520, arXiv.org, revised Jan 2020.
    48. Giot, Pierre & Laurent, Sébastien & Petitjean, Mikael, 2010. "Trading activity, realized volatility and jumps," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 168-175, January.
    49. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
    50. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2015. "Volatility transmission in global financial markets," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 3-18.
    51. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    52. Wen Cheong Chin & Min Cherng Lee, 2018. "S&P500 volatility analysis using high-frequency multipower variation volatility proxies," Empirical Economics, Springer, vol. 54(3), pages 1297-1318, May.
    53. Wang, Fangfang, 2014. "Optimal design of Fourier estimator in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 708-722.
    54. Huang, Jianbai & Tang, Jing & Zhang, Hongwei, 2020. "The effect of investors’ information search behaviors on rebar market return dynamics using high frequency data," Resources Policy, Elsevier, vol. 66(C).
    55. Michel Beine & Jerome Lahaye & Sebastien Laurent & Christopher J. Neely & Franz C. Palm, 2007. "Central bank intervention and exchange rate volatility, its continuous and jump components," Working Papers 2006-031, Federal Reserve Bank of St. Louis.
    56. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
    57. Wang, Jiqian & Lu, Xinjie & He, Feng & Ma, Feng, 2020. "Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    58. Bouri, Elie & Lei, Xiaojie & Jalkh, Naji & Xu, Yahua & Zhang, Hongwei, 2021. "Spillovers in higher moments and jumps across US stock and strategic commodity markets," Resources Policy, Elsevier, vol. 72(C).
    59. Barbara Będowska-Sójka, 2018. "Is intraday data useful for forecasting VaR? The evidence from EUR/PLN exchange rate," Risk Management, Palgrave Macmillan, vol. 20(4), pages 326-346, November.
    60. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    61. Leonidas S. Rompolis & Elias Tzavalis, 2017. "Pricing and hedging contingent claims using variance and higher order moment swaps," Quantitative Finance, Taylor & Francis Journals, vol. 17(4), pages 531-550, April.
    62. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    63. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2015. "Which continuous-time model is most appropriate for exchange rates?," Post-Print hal-01457402, HAL.
    64. Daniel Preve, "undated". "Linear programming-based estimators in nonnegative autoregression," GRU Working Paper Series GRU_2016_001, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    65. Li, Xiafei & Liao, Yin & Lu, Xinjie & Ma, Feng, 2022. "An oil futures volatility forecast perspective on the selection of high-frequency jump tests," Energy Economics, Elsevier, vol. 116(C).
    66. Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
    67. LUPU, Radu & MATEESCU, Alexandra, 2016. "Systemic Risk And Cojumps In High Frequency Data," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 20(4), pages 6-16.
    68. Serdengeçti, Süleyman & Sensoy, Ahmet & Nguyen, Duc Khuong, 2021. "Dynamics of return and liquidity (co) jumps in emerging foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    69. Ozcan Ceylan, 2015. "Limited information-processing capacity and asymmetric stock correlations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1031-1039, June.
    70. Füss, Roland & Grabellus, Markus & Mager, Ferdinand & Stein, Michael, 2018. "Something in the air: Information density, news surprises, and price jumps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 50-75.
    71. Jeremy Large, 2007. "Estimating Quadratic Variation When Quoted Prices Change by a Constant Increment," Economics Series Working Papers 340, University of Oxford, Department of Economics.
    72. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
    73. Liu, Wenwen & Zhang, Chang & Qiao, Gaoxiu & Xu, Lei, 2022. "Impact of network investor sentiment and news arrival on jumps," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    74. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2017. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Working Papers 2017-10, University of Tasmania, Tasmanian School of Business and Economics.
    75. Rangel José Gonzalo, 2009. "Macroeconomic News, Announcements, and Stock Market Jump Intensity Dynamics," Working Papers 2009-15, Banco de México.
    76. Kislay Kumar Jha & Dirk G. Baur, 2020. "Regime-Dependent Good and Bad Volatility of Bitcoin," JRFM, MDPI, vol. 13(12), pages 1-16, December.
    77. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
    78. Sébastien Laurent & Shuping Shi, 2018. "Volatility Estimation and Jump Detection for drift-diffusion Processes," Working Papers halshs-01944449, HAL.
    79. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
    80. Ai-ru (Meg) Cheng & Kuntal Das & Takeshi Shimatani, 2013. "Central Bank Intervention and Exchange Rate Volatility: Evidence from Japan Using Realized Volatility," Working Papers in Economics 13/19, University of Canterbury, Department of Economics and Finance.
    81. Juho Kanniainen & Martin Magris, 2018. "Option market (in)efficiency and implied volatility dynamics after return jumps," Papers 1810.12200, arXiv.org.
    82. Eom, Cheoljun & Kaizoji, Taisei & Kang, Sang Hoon & Pichl, Lukas, 2019. "Bitcoin and investor sentiment: Statistical characteristics and predictability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 511-521.
    83. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    84. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org.
    85. Bergsli, Lykke Øverland & Lind, Andrea Falk & Molnár, Peter & Polasik, Michał, 2022. "Forecasting volatility of Bitcoin," Research in International Business and Finance, Elsevier, vol. 59(C).
    86. Torben G. Andersen & Nicola Fusari & Viktor Todorov & Rasmus T. Varneskov, 2018. "Unified Inference for Nonlinear Factor Models from Panels with Fixed and Large Time Span," CREATES Research Papers 2018-03, Department of Economics and Business Economics, Aarhus University.
    87. Jo-Hui & Chen & Sabbor Hussain, 2022. "Jump Dynamics and Leverage Effect: Evidences from Energy Exchange Traded Fund (ETFs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-7.
    88. Dovonon, Prosper & Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping high-frequency jump tests," IDEI Working Papers 870, Institut d'Économie Industrielle (IDEI), Toulouse.
    89. Dario Alitab & Giacomo Bormetti & Fulvio Corsi & Adam A. Majewski, 2019. "A realized volatility approach to option pricing with continuous and jump variance components," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 639-664, December.
    90. Jing-zhi Huang & Hao Zhou, 2008. "Specification analysis of structural credit risk models," Finance and Economics Discussion Series 2008-55, Board of Governors of the Federal Reserve System (U.S.).
    91. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
    92. Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
    93. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Limit theorems for functionals of higher order differences of Brownian semi-stationary processes," CREATES Research Papers 2009-60, Department of Economics and Business Economics, Aarhus University.
    94. Bent Jesper Christensen & Rasmus Tangsgaard Varneskov, 2021. "Dynamic Global Currency Hedging [Arbitrage in the Foreign Exchange Market: Turning on the Microscope]," Journal of Financial Econometrics, Oxford University Press, vol. 19(1), pages 97-127.
    95. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    96. Li, Jia & Todorov, Viktor & Tauchen, George & Chen, Rui, 2017. "Mixed-scale jump regressions with bootstrap inference," Journal of Econometrics, Elsevier, vol. 201(2), pages 417-432.
    97. Mei, Dexiang & Ma, Feng & Liao, Yin & Wang, Lu, 2020. "Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models," Energy Economics, Elsevier, vol. 86(C).
    98. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," Global COE Hi-Stat Discussion Paper Series gd08-032, Institute of Economic Research, Hitotsubashi University.
    99. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Forecasting with mixed-frequency data," University of Cyprus Working Papers in Economics 10-2010, University of Cyprus Department of Economics.
    100. Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    101. Vassilios G. Papavassiliou, 2016. "Allowing For Jump Measurements In Volatility: A High-Frequency Financial Data Analysis Of Individual Stocks," Bulletin of Economic Research, Wiley Blackwell, vol. 68(2), pages 124-132, April.
    102. Mehmet Balcilar & Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "The Effect of Investor Sentiment on Gold Market Dynamics," Working Papers 201638, University of Pretoria, Department of Economics.
    103. Yeh, Jin-Huei & Chen, Lien-Chuan, 2014. "Stabilizing the market with short sale constraint? New evidence from price jump activities," Finance Research Letters, Elsevier, vol. 11(3), pages 238-246.
    104. Anderson, Heather M. & Vahid, Farshid, 2007. "Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 76-90, January.
    105. Kim Christensen & Roel Oomen & Mark Podolskij, 2011. "Fact or friction: Jumps at ultra high frequency," CREATES Research Papers 2011-19, Department of Economics and Business Economics, Aarhus University.
    106. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    107. Yuta Koike, 2014. "An estimator for the cumulative co-volatility of asynchronously observed semimartingales with jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 460-481, June.
    108. Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan & Gkillas, Konstantinos, 2020. "Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model," Energy Economics, Elsevier, vol. 88(C).
    109. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    110. Pan, Ging-Ginq & Shiu, Yung-Ming & Wu, Tu-Cheng, 2022. "Can risk-neutral skewness and kurtosis subsume the information content of historical jumps?," Journal of Financial Markets, Elsevier, vol. 57(C).
    111. Chuong Luong & Nikolai Dokuchaev, 2018. "Forecasting of Realised Volatility with the Random Forests Algorithm," JRFM, MDPI, vol. 11(4), pages 1-15, October.
    112. Ymir Mäkinen & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Forecasting jump arrivals in stock prices: new attention-based network architecture using limit order book data," Quantitative Finance, Taylor & Francis Journals, vol. 19(12), pages 2033-2050, December.
    113. Liu, Cheng & Tang, Cheng Yong, 2014. "A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data," Journal of Econometrics, Elsevier, vol. 180(2), pages 217-232.
    114. Liu, Qiang & Liu, Yiqi & Liu, Zhi, 2018. "Estimating spot volatility in the presence of infinite variation jumps," Stochastic Processes and their Applications, Elsevier, vol. 128(6), pages 1958-1987.
    115. Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
    116. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
    117. Bonaccolto, G. & Caporin, M. & Gupta, R., 2018. "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 446-469.
    118. Gael M. Martin & Andrew Reidy & Jill Wright, 2006. "Assessing the Impact of Market Microstructure Noise and Random Jumps on the Relative Forecasting Performance of Option-Implied and Returns-Based Volatility," Monash Econometrics and Business Statistics Working Papers 10/06, Monash University, Department of Econometrics and Business Statistics.
    119. Liu, Guangqiang & Wang, Yan & Chen, Xiaodan & Zhang, Yifeng & Shang, Yue, 2020. "Forecasting volatility of the Chinese stock markets using TVP HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    120. Rituparna Sen & Pulkit Mehrotra, 2016. "Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 137-150, June.
    121. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2014. "The Risk Premia Embedded in Index Options," CREATES Research Papers 2014-56, Department of Economics and Business Economics, Aarhus University.
    122. Besma Hkiri & Juncal Cunado & Mehmet Balcilar & Rangan Gupta, 2019. "Time-Varying Relationship between Conventional and Unconventional Monetary Policies and Risk Aversion: International Evidence from Time- and Frequency-Domains," Working Papers 201965, University of Pretoria, Department of Economics.
    123. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    124. Masato Ubukata & Toshiaki Watanabe, 2014. "Pricing Nikkei 225 Options Using Realized Volatility," The Japanese Economic Review, Japanese Economic Association, vol. 65(4), pages 431-467, December.
    125. Chan, Kam Fong & Gray, Philip & van Campen, Bart, 2008. "A new approach to characterizing and forecasting electricity price volatility," International Journal of Forecasting, Elsevier, vol. 24(4), pages 728-743.
    126. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    127. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2016. "Time-Varying Persistence of Inflation: Evidence from a Wavelet-based Approach," Working papers 2016-09, University of Connecticut, Department of Economics.
    128. Stavros Degiannakis & Alexandra Livada, 2016. "Evaluation of realized volatility predictions from models with leptokurtically and asymmetrically distributed forecast errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 871-892, April.
    129. Lin, Xiaoqiang & Fei, Fangyu & Wang, Yudong, 2011. "Analysis of the efficiency of the Shanghai stock market: A volatility perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3486-3495.
    130. Gabriel P. Mathy, 2014. "Uncertainty Shocks and Equity Return Jumps and Volatility During the Great Depression," Working Papers 2014-02, American University, Department of Economics.
    131. Mark Podolskij & Mathias Vetter, 2007. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," CREATES Research Papers 2007-27, Department of Economics and Business Economics, Aarhus University.
    132. Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
    133. Eric Jondeau & Jérôme Lahaye & Michael Rockinger, 2013. "Estimating the Price Impact of Trades in an High-Frequency Microstructure Model with Jumps," Swiss Finance Institute Research Paper Series 13-47, Swiss Finance Institute, revised Feb 2016.
    134. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    135. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.
    136. Nikolaus Hautsch & Mark Podolskij, 2013. "Preaveraging-Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 165-183, April.
    137. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    138. Ole Barndorff-Nielsen & Svend Erik Graversen & Jean Jacod & Mark Podolskij & Neil Shephard, 2004. "A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales," Economics Papers 2004-W29, Economics Group, Nuffield College, University of Oxford.
    139. Benjamin Yibin Zhang & Hao Zhou & Haibin Zhu, 2009. "Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5099-5131, December.
    140. Park, Yang-Ho, 2015. "Volatility-of-volatility and tail risk hedging returns," Journal of Financial Markets, Elsevier, vol. 26(C), pages 38-63.
    141. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillovers and connectedness between crude oil and currency markets using high-frequency data," Resources Policy, Elsevier, vol. 77(C).
    142. Będowska-Sójka, Barbara & Kliber, Agata, 2021. "Information content of liquidity and volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    143. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    144. Yu, Qian & Bajja, Salwa, 2020. "Volatility estimation of general Gaussian Ornstein–Uhlenbeck process," Statistics & Probability Letters, Elsevier, vol. 163(C).
    145. Marcelo Fernandes & Ms. Deniz O Igan & Marcelo Pinheiro, 2015. "March Madness in Wall Street: (What) Does the Market Learn from Stress Tests?," IMF Working Papers 2015/271, International Monetary Fund.
    146. Arouri, Mohamed El Hedi & M’saddek, Oussama & Nguyen, Duc Khuong & Pukthuanthong, Kuntara, 2017. "Cojumps and Asset Allocation in International Equity Markets," MPRA Paper 89938, University Library of Munich, Germany, revised May 2018.
    147. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "Long Memory and Tail dependence in Trading Volume and Volatility," CREATES Research Papers 2009-30, Department of Economics and Business Economics, Aarhus University.
    148. John M. Maheu & Thomas H. McCurdy, 2009. "Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions?," Working Paper series 19_09, Rimini Centre for Economic Analysis.
    149. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    150. Degiannakis, Stavros, 2016. "The one-trading-day-ahead forecast errors of intra-day realized volatility," MPRA Paper 80163, University Library of Munich, Germany.
    151. Julien Chevallier & Benoît Sévi, 2012. "On the Stochastic Properties of Carbon Futures Prices," Working Papers halshs-00720166, HAL.
    152. Zhou, Haigang & Zhu, John Qi, 2019. "Firm characteristics and jump dynamics in stock prices around earnings announcements," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    153. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk-realised semivariance," Economics Papers 2008-W02, Economics Group, Nuffield College, University of Oxford.
    154. Olesya V. Grishchenko & Zhaogang Song & Hao Zhou, 2015. "Term Structure of Interest Rates with Short-run and Long-run Risks," Finance and Economics Discussion Series 2015-95, Board of Governors of the Federal Reserve System (U.S.).
    155. Federico M. Bandi & Roberto Reno, 2009. "Nonparametric Stochastic Volatility," Global COE Hi-Stat Discussion Paper Series gd08-035, Institute of Economic Research, Hitotsubashi University.
    156. Julien Chevallier & Benoît Sévi, 2012. "On the volatility-volume relationship in energy futures markets using intraday data," Post-Print hal-00988926, HAL.
    157. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
    158. Maki, Daiki & Ota, Yasushi, 2021. "Impacts of asymmetry on forecasting realized volatility in Japanese stock markets," Economic Modelling, Elsevier, vol. 101(C).
    159. Audrino, Francesco & Hu, Yujia, 2011. "Volatility Forecasting: Downside Risk, Jumps and Leverage Effect," Economics Working Paper Series 1138, University of St. Gallen, School of Economics and Political Science.
    160. Patrick Chang, 2020. "Fourier instantaneous estimators and the Epps effect," Papers 2007.03453, arXiv.org, revised Sep 2020.
    161. Mazzarisi, Piero & Zaoli, Silvia & Campajola, Carlo & Lillo, Fabrizio, 2020. "Tail Granger causalities and where to find them: Extreme risk spillovers vs spurious linkages," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    162. Bissoondoyal-Bheenick, Emawtee & Do, Hung & Hu, Xiaolu & Zhong, Angel, 2022. "Sentiment and stock market connectedness: Evidence from the U.S. – China trade war," International Review of Financial Analysis, Elsevier, vol. 80(C).
    163. Souček, Michael & Todorova, Neda, 2014. "Realized volatility transmission: The role of jumps and leverage effects," Economics Letters, Elsevier, vol. 122(2), pages 111-115.
    164. Nepp, Alexander & Okhrin, Ostap & Egorova, Julia & Dzhuraeva, Zarnigor & Zykov, Alexander, 2022. "What threatens stock markets more - The coronavirus or the hype around it?," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 519-539.
    165. Yu, Miao & Song, Jinguo, 2018. "Volatility forecasting: Global economic policy uncertainty and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 316-323.
    166. Yao, Wenying & Tian, Jing, 2015. "The role of intra-day volatility pattern in jump detection: empirical evidence on how financial markets respond to macroeconomic news announcements," Working Papers 2015-05, University of Tasmania, Tasmanian School of Business and Economics.
    167. Todorov, Viktor & Bollerslev, Tim, 2010. "Jumps and betas: A new framework for disentangling and estimating systematic risks," Journal of Econometrics, Elsevier, vol. 157(2), pages 220-235, August.
    168. Cui, Jinxin & Maghyereh, Aktham & Goh, Mark & Zou, Huiwen, 2022. "Risk spillovers and time-varying links between international oil and China’s commodity futures markets: Fresh evidence from the higher-order moments," Energy, Elsevier, vol. 238(PB).
    169. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2007. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," CREATES Research Papers 2007-22, Department of Economics and Business Economics, Aarhus University.
    170. Yao Axel Ehouman, 2020. "Volatility transmission between oil prices and banks’ stock prices as a new source of instability: Lessons from the United States experience," Post-Print hal-02960571, HAL.
    171. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    172. Chen, Wang & Lu, Xinjie & Wang, Jiqian, 2022. "Modeling and managing stock market volatility using MRS-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 625-635.
    173. Zhen Fang & Zhang Jin E., 2020. "Dissecting skewness under affine jump-diffusions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-19, September.
    174. Song, Zhaogang, 2011. "A martingale approach for testing diffusion models based on infinitesimal operator," Journal of Econometrics, Elsevier, vol. 162(2), pages 189-212, June.
    175. Diep Duong & Norman Swanson, 2013. "Empirical Evidence on the Importance of Aggregation, Asymmetry, and Jumps for Volatility Prediction," Departmental Working Papers 201321, Rutgers University, Department of Economics.
    176. Masato Ubukata & Toshiaki Watanabe, 2011. "Market Variance Risk Premiums in Japan as Predictor Variables and Indicators of Risk Aversion," Global COE Hi-Stat Discussion Paper Series gd11-214, Institute of Economic Research, Hitotsubashi University.
    177. Ole E. Barndorff-Nielsen & Neil Shephard & Matthias Winkel, 2005. "Limit theorems for multipower variation in the presence of jumps," OFRC Working Papers Series 2005fe06, Oxford Financial Research Centre.
    178. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, Center for Economic and Financial Research (CEFIR).
    179. Filip Zikes & Jozef Barunik, 2013. "Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility," Papers 1308.4276, arXiv.org.
    180. Boudt, Kris & Croux, Christophe & Laurent, Sébastien, 2011. "Robust estimation of intraweek periodicity in volatility and jump detection," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 353-367, March.
    181. Jia Liu & John M. Maheu, 2018. "Improving Markov switching models using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 297-318, April.
    182. Martin Magris & Perttu Barholm & Juho Kanniainen, 2017. "Implied volatility smile dynamics in the presence of jumps," Papers 1711.02925, arXiv.org, revised May 2020.
    183. Kim Christensen & Mark Podolskij & Mathias Vetter, 2009. "Bias-correcting the realized range-based variance in the presence of market microstructure noise," Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
    184. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    185. Hoerova, Marie & Bekaert, Geert, 2014. "The VIX, the variance premium and stock market volatility," Working Paper Series 1675, European Central Bank.
    186. Degiannakis, Stavros & Livada, Alexandra, 2013. "Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process," MPRA Paper 80449, University Library of Munich, Germany.
    187. Wen, Zhuzhu & Bouri, Elie & Xu, Yahua & Zhao, Yang, 2022. "Intraday return predictability in the cryptocurrency markets: Momentum, reversal, or both," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    188. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
    189. Leopoldo Catania & Mads Sandholdt, 2019. "Bitcoin at High Frequency," JRFM, MDPI, vol. 12(1), pages 1-20, February.
    190. Taoufik Bouezmarni & Jeroen Rombouts & Abderrahim Taamouti, 2009. "A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality," CIRANO Working Papers 2009s-28, CIRANO.
    191. Kaminska, Iryna & Roberts-Sklar, Matt, 2017. "Volatility in equity markets and monetary policy rate uncertainty," Bank of England working papers 700, Bank of England.
    192. Dimitrios I. Vortelinos, 2015. "The Effect of Macro News on Volatility and Jumps," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 425-447, November.
    193. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight momentum, informational shocks, and late informed trading in China," International Review of Financial Analysis, Elsevier, vol. 66(C).
    194. Hanousek, Jan & Novotný, Jan, 2012. "Price jumps in Visegrad-country stock markets: An empirical analysis," Emerging Markets Review, Elsevier, vol. 13(2), pages 184-201.
    195. Xin Zhang & Donggyu Kim & Yazhen Wang, 2016. "Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets," Econometrics, MDPI, vol. 4(3), pages 1-26, August.
    196. Ding, Y., 2021. "Augmented Real-Time GARCH: A Joint Model for Returns, Volatility and Volatility of Volatility," Cambridge Working Papers in Economics 2112, Faculty of Economics, University of Cambridge.
    197. Maciej Kostrzewski, 2014. "Bayesian DEJD model and detection of asymmetric jumps," Papers 1404.2050, arXiv.org.
    198. Lin, Tiantian & Liu, Dehong & Zhang, Lili & Lung, Peter, 2019. "The information content of realized volatility of sector indices in China’s stock market," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 625-640.
    199. Youcong Chao & Xiaoqun Liu & Shijun Guo, 2017. "Sign realized jump risk and the cross-section of stock returns: Evidence from China's stock market," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-14, August.
    200. Chu, Shan-Ying & Chan, Lin Kun & Yeh, Jin-Huei, 2019. "The stabilizing effects of price limits: New evidence from jump contributed price variations," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 529-539.
    201. Liao, Yin & Anderson, Heather M., 2019. "Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
    202. Cui, Jing & Zhao, Hua, 2015. "Intraday jumps in China's Treasury bond market and macro news announcements," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 211-223.
    203. Martin Tegnér & Rolf Poulsen, 2018. "Volatility Is Log-Normal—But Not for the Reason You Think," Risks, MDPI, vol. 6(2), pages 1-16, April.
    204. Yu, Xing & Li, Yanyan & Gong, Xue & Zhang, Nan, 2022. "Evaluating the performance of futures hedging using factors-driven realized volatility," International Review of Financial Analysis, Elsevier, vol. 84(C).
    205. Lucio Maria Calcagnile & Fulvio Corsi & Stefano Marmi, 2020. "Entropy and Efficiency of the ETF Market," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 143-184, January.
    206. Balcilar, Mehmet & Bonato, Matteo & Demirer, Riza & Gupta, Rangan, 2017. "The effect of investor sentiment on gold market return dynamics: Evidence from a nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 51(C), pages 77-84.
    207. Štefan Lyócsa & Roman Horváth, 2018. "Stock Market Contagion: a New Approach," Open Economies Review, Springer, vol. 29(3), pages 547-577, July.
    208. Jean Jacod & Viktor Todorov, 2010. "Do price and volatility jump together?," Papers 1010.4990, arXiv.org.
    209. Linlan Xiao & Vigdis Boasson & Sergey Shishlenin & Victoria Makushina, 2018. "Volatility forecasting: combinations of realized volatility measures and forecasting models," Applied Economics, Taylor & Francis Journals, vol. 50(13), pages 1428-1441, March.
    210. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
    211. Ahmad, Wasim & Prakash, Ravi & Uddin, Gazi Salah & Chahal, Rishman Jot Kaur & Rahman, Md. Lutfur & Dutta, Anupam, 2020. "On the intraday dynamics of oil price and exchange rate: What can we learn from China and India?," Energy Economics, Elsevier, vol. 91(C).
    212. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    213. Abramov, Vyacheslav & Klebaner, Fima, 2006. "Forecasting and testing a non-constant volatility," MPRA Paper 207, University Library of Munich, Germany.
    214. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    215. Jang, Bong-Gyu & Rhee, Yuna & Yoon, Ji Hee, 2016. "Business cycle and credit risk modeling with jump risks," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 15-36.
    216. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2012. "International market links and volatility transmission," Journal of Econometrics, Elsevier, vol. 170(1), pages 117-141.
    217. Dumitru, Ana-Maria & Urga, Giovanni, 2016. "Jumps and Information Asymmetry in the US Treasury Market," EconStor Preprints 130148, ZBW - Leibniz Information Centre for Economics.
    218. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.
    219. Zhihong Jian & Zhican Zhu & Jie Zhou & Shuai Wu, 2018. "The Magnet Effect of Circuit Breakers: A role of price jumps and market liquidity," Departmental Working Papers 2018-01, The University of Winnipeg, Department of Economics.
    220. Bo Yu & Bruce Mizrach & Norman R. Swanson, 2020. "New Evidence of the Marginal Predictive Content of Small and Large Jumps in the Cross-Section," Econometrics, MDPI, vol. 8(2), pages 1-52, May.
    221. Hossein Asgharian & Mia Holmfeldt & Marcus Larson, 2011. "An event study of price movements following realized jumps," Quantitative Finance, Taylor & Francis Journals, vol. 11(6), pages 933-946.
    222. Thierry Ane & Carole Metais, 2010. "Jump Distribution Characteristics: Evidence from European Stock Markets," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 9(1), pages 1-22, April.
    223. Yin Liao & Heather M. Anderson & Farshid Vahid, 2010. "Do Jumps Matter? Forecasting Multivariate Realized Volatility allowing for Common Jumps," Monash Econometrics and Business Statistics Working Papers 11/10, Monash University, Department of Econometrics and Business Statistics.
    224. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
    225. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    226. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    227. Johannes Stübinger & Lucas Schneider, 2019. "Statistical Arbitrage with Mean-Reverting Overnight Price Gaps on High-Frequency Data of the S&P 500," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    228. Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    229. Jacod, Jean & Li, Yingying & Mykland, Per A. & Podolskij, Mark & Vetter, Mathias, 2007. "Microstructure noise in the continuous case: the pre-averaging approach," Technical Reports 2007,41, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    230. Neil Shephard, 2005. "Stochastic Volatility," Economics Papers 2005-W17, Economics Group, Nuffield College, University of Oxford.
    231. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    232. Jean-Yves Gnabo & J�rôme Lahaye & S�bastien Laurent & Christelle Lecourt, 2012. "Do jumps mislead the FX market?," Quantitative Finance, Taylor & Francis Journals, vol. 12(10), pages 1521-1532, October.
    233. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting," MPRA Paper 35252, University Library of Munich, Germany.
    234. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    235. Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 5-31.
    236. Klein, Tony & Todorova, Neda, 2021. "Night trading with futures in China: The case of Aluminum and Copper," Resources Policy, Elsevier, vol. 73(C).
    237. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    238. Alizadeh, Amir H. & Huang, Chih-Yueh & Marsh, Ian W., 2021. "Modelling the volatility of TOCOM energy futures: A regime switching realised volatility approach," Energy Economics, Elsevier, vol. 93(C).
    239. John Elder, Hong Miao, and Sanjay Ramchander, 2013. "Jumps in Oil Prices: The Role of Economic News," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    240. Hanousek Jan & Kočenda Evžen & Novotný Jan, 2012. "The identification of price jumps," Monte Carlo Methods and Applications, De Gruyter, vol. 18(1), pages 53-77, January.
    241. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2006. "The Information Content Of Treasury Bond Options Concerning Future Volatility And Price Jumps," Working Paper 1188, Economics Department, Queen's University.
    242. Lu, Xinjie & Ma, Feng & Wang, Jianqiong & Dong, Dayong, 2022. "Singlehanded or joint race? Stock market volatility prediction," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 734-754.
    243. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš, 2019. "Central bank announcements and realized volatility of stock markets in G7 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 117-135.
    244. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    245. Maciej Kostrzewski & Jadwiga Kostrzewska, 2021. "The Impact of Forecasting Jumps on Forecasting Electricity Prices," Energies, MDPI, vol. 14(2), pages 1-17, January.
    246. Vuorenmaa, Tommi A., 2008. "Decimalization, Realized Volatility, and Market Microstructure Noise," MPRA Paper 8692, University Library of Munich, Germany.
    247. Hounyo, Ulrich & Varneskov, Rasmus T., 2017. "A local stable bootstrap for power variations of pure-jump semimartingales and activity index estimation," Journal of Econometrics, Elsevier, vol. 198(1), pages 10-28.
    248. Venter, J.H. & de Jongh, P.J., 2014. "Extended stochastic volatility models incorporating realised measures," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 687-707.
    249. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    250. Fredj Jawadi & Waël Louhichi & Hachmi Ben Ameur & Abdoulkarim Idi Cheffou, 2017. "On Oil-US Exchange Rate Volatility Relationships: an Intradaily Analysis," EconomiX Working Papers 2017-11, University of Paris Nanterre, EconomiX.
    251. Angelo Ranaldo & Paul Söderlind, 2007. "Safe Haven Currencies," Working Papers 2007-17, Swiss National Bank.
    252. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    253. Li, Jia & Todorov, Viktor & Tauchen, George, 2016. "Inference theory for volatility functional dependencies," Journal of Econometrics, Elsevier, vol. 193(1), pages 17-34.
    254. Li, Gang & Zhang, Chu, 2016. "On the relationship between conditional jump intensity and diffusive volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 196-213.
    255. Degiannakis, Stavros & Filis, George, 2023. "Oil price assumptions for macroeconomic policy," Energy Economics, Elsevier, vol. 117(C).
    256. Schulz, Frowin C., 2010. "Explaining time-varying risk of electricity forwards: trading activity and news announcements," Discussion Papers in Econometrics and Statistics 8/10, University of Cologne, Institute of Econometrics and Statistics.
    257. Bee, Marco & Dupuis, Debbie J. & Trapin, Luca, 2016. "Realizing the extremes: Estimation of tail-risk measures from a high-frequency perspective," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 86-99.
    258. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
    259. Jian, Zhihong & Zhu, Zhican & Zhou, Jie & Wu, Shuai, 2020. "Intraday price jumps, market liquidity, and the magnet effect of circuit breakers," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 168-186.
    260. Bekierman, Jeremias & Manner, Hans, 2018. "Forecasting realized variance measures using time-varying coefficient models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 276-287.
    261. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    262. Cheng Jiang & Kose John & David Larsen, 2021. "R&D investment intensity and jump volatility of stock price," Review of Quantitative Finance and Accounting, Springer, vol. 57(1), pages 235-277, July.
    263. D. Schneller & S. Heiden & M. Heiden & A. Hamid, 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, Verein für Socialpolitik, vol. 19(2), pages 209-236, May.
    264. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    265. Martin L. Scholtus & Dick van Dijk & Bart Frijns, 2012. "Speed, Algorithmic Trading, and Market Quality around Macroeconomic News Announcements," Tinbergen Institute Discussion Papers 12-121/III, Tinbergen Institute.
    266. Ostap Okhrin & Anastasija Tetereva, 2017. "The Realized Hierarchical Archimedean Copula in Risk Modelling," Econometrics, MDPI, vol. 5(2), pages 1-31, June.
    267. Hattori, Masazumi & Shim, Ilhyock & Sugihara, Yoshihiko, 2021. "Cross-stock market spillovers through variance risk premiums and equity flows," Journal of International Money and Finance, Elsevier, vol. 119(C).
    268. Bandi, F.M. & Renò, R., 2016. "Price and volatility co-jumps," Journal of Financial Economics, Elsevier, vol. 119(1), pages 107-146.
    269. Sharon S. Yang & Jr-Wei Huang & Chuang-Chang Chang, 2016. "Detecting and modelling the jump risk of CO 2 emission allowances and their impact on the valuation of option on futures contracts," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 749-762, May.
    270. Figueroa-López, José E. & Nisen, Jeffrey, 2013. "Optimally thresholded realized power variations for Lévy jump diffusion models," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2648-2677.
    271. Bonato, Matteo & Gupta, Rangan & Lau, Chi Keung Marco & Wang, Shixuan, 2020. "Moments-based spillovers across gold and oil markets," Energy Economics, Elsevier, vol. 89(C).
    272. Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 94289, University Library of Munich, Germany.
    273. Ilze KALNINA & Dacheng XIU, 2015. "Nonparametric Estimation of the Leverage Effect : A Trade-off between Robustness and Efficiency," Cahiers de recherche 09-2015, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    274. Francis Breedon & Louisa Chen & Angelo Ranaldo & Nicholas Vause, 2019. "Judgment Day: Algorithmic Trading Around The Swiss Franc Cap Removal," Working Papers on Finance 1912, University of St. Gallen, School of Finance.
    275. Heiny, Johannes & Podolskij, Mark, 2021. "On estimation of quadratic variation for multivariate pure jump semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 138(C), pages 234-254.
    276. Silja Kinnebrock & Mark Podolskij, 2007. "A Note on the Central Limit Theorem for Bipower Variation of General Functions," OFRC Working Papers Series 2007fe03, Oxford Financial Research Centre.
    277. Alain Hecq & Sébastien Laurent & Franz C. Palm, 2011. "Common Intraday Periodicity," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 325-353, 2012 20 1.
    278. Benoît Sévi & César Baena, 2013. "The explanatory power of signed jumps for the risk-return tradeoff," Economics Bulletin, AccessEcon, vol. 33(2), pages 1029-1046.
    279. Omura, Akihiro & Li, Bin & Chung, Richard & Todorova, Neda, 2018. "Convenience yield, realised volatility and jumps: Evidence from non-ferrous metals," Economic Modelling, Elsevier, vol. 70(C), pages 496-510.
    280. Prodromou, Tina & Westerholm, P. Joakim, 2022. "Are high frequency traders responsible for extreme price movements?," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 94-111.
    281. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    282. Dooyeon Cho & Seunghwa Rho, 2022. "On asymmetric volatility effects in currency markets," Empirical Economics, Springer, vol. 62(5), pages 2149-2177, May.
    283. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    284. Walter Distaso & Basel Awartani & Valentina Corradi, 2004. "Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average," Econometric Society 2004 Australasian Meetings 273, Econometric Society.
    285. Piero Mazzarisi & Silvia Zaoli & Carlo Campajola & Fabrizio Lillo, 2020. "Tail Granger causalities and where to find them: extreme risk spillovers vs. spurious linkages," Papers 2005.01160, arXiv.org, revised May 2021.
    286. Benoît Sévi & César Baena, 2011. "Brownian motion vs. pure-jump processes for individual stocks," Economics Bulletin, AccessEcon, vol. 31(4), pages 3138-3152.
    287. Tingguo Zheng & Tao Song, 2014. "A Realized Stochastic Volatility Model With Box-Cox Transformation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 593-605, October.
    288. Wong, Alfred, 2019. "Currency jumps, Euribor-OIS spreads and the volatility skew: A study on the dollar-euro crash risk of 2007–2015," Finance Research Letters, Elsevier, vol. 29(C), pages 7-16.
    289. Shixuan Wang & Rangan Gupta & Matteo Bonato & Oguzhan Cepni, 2022. "The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks," Working Papers 202219, University of Pretoria, Department of Economics.
    290. Ye, Xu-Guo & Lin, Jin-Guan & Zhao, Yan-Yong & Hao, Hong-Xia, 2015. "Two-step estimation of the volatility functions in diffusion models with empirical applications," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 135-159.
    291. Svetlana Borovkova & Diego Mahakena, 2015. "News, volatility and jumps: the case of natural gas futures," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1217-1242, July.
    292. Georg Dettmann, 2011. "A View on Global Imbalances and their Contribution to the Financial Crisis," Birkbeck Working Papers in Economics and Finance 1102, Birkbeck, Department of Economics, Mathematics & Statistics.
    293. Guido Russi, 2012. "Estimating the Leverage Effect Using High Frequency Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 1-24, February.
    294. Hellström, Jörgen & Lönnbark, Carl, 2011. "Identi�cation of jumps in �financial price series," MPRA Paper 30977, University Library of Munich, Germany.
    295. Kato, Kengo & Kurisu, Daisuke, 2020. "Bootstrap confidence bands for spectral estimation of Lévy densities under high-frequency observations," Stochastic Processes and their Applications, Elsevier, vol. 130(3), pages 1159-1205.
    296. Ehouman, Yao Axel, 2020. "Volatility transmission between oil prices and banks' stock prices as a new source of instability: Lessons from the United States experience," Economic Modelling, Elsevier, vol. 91(C), pages 198-217.
    297. Mingmian Cheng & Norman R. Swanson, 2019. "Fixed and Long Time Span Jump Tests: New Monte Carlo and Empirical Evidence," Econometrics, MDPI, vol. 7(1), pages 1-32, March.
    298. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2009. "Dynamic Stock Market Interactions between the Canadian, Mexican, and the United States Markets: The NAFTA Experience," Working Papers 0905, University of Nevada, Las Vegas , Department of Economics.
    299. Wang, Hao & Yue, Mengqi & Zhao, Hua, 2015. "Cojumps in China's spot and stock index futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 541-557.
    300. Yacine Aït-Sahalia & Jean Jacod, 2010. "Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data," NBER Working Papers 15808, National Bureau of Economic Research, Inc.
    301. B. Cooper Boniece & Jos'e E. Figueroa-L'opez & Yuchen Han, 2022. "Efficient Volatility Estimation for L\'evy Processes with Jumps of Unbounded Variation," Papers 2202.00877, arXiv.org.
    302. Fang, Yan & Ielpo, Florian & Sévi, Benoît, 2012. "Empirical bias in intraday volatility measures," Finance Research Letters, Elsevier, vol. 9(4), pages 231-237.
    303. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01442618, HAL.
    304. Wu, Feng & Myers, Robert J. & Guan, Zhengfei & Wang, Zhiguang, 2015. "Risk-adjusted implied volatility and its performance in forecasting realized volatility in corn futures prices," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 260-274.
    305. Gkillas, Konstantinos & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2022. "Spillovers in Higher-Order Moments of Crude Oil, Gold, and Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 398-406.
    306. Lin, Edward M.H. & Chen, Cathy W.S. & Gerlach, Richard, 2012. "Forecasting volatility with asymmetric smooth transition dynamic range models," International Journal of Forecasting, Elsevier, vol. 28(2), pages 384-399.
    307. Ahadzie, Richard Mawulawoe & Jeyasreedharan, Nagaratnam, 2020. "Trading volume and realized higher-order moments in the Australian stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    308. Charles S. Bos & Paweł Janus & Siem Jan Koopman, 2012. "Spot Variance Path Estimation and Its Application to High-Frequency Jump Testing," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 354-389, 2012 06.
    309. Chen, Chin-Ho, 2019. "Downside jump risk and the levels of futures-cash basis," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    310. Fulvio Corsi & Davide Pirino & Roberto Reno', 2010. "Threshold Bipower Variation and the Impact of Jumps on Volatility Forecasting," LEM Papers Series 2010/11, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    311. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    312. Pirino, Davide, 2009. "Jump detection and long range dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1150-1156.
    313. Hiroyuki Kawakatsu, 2022. "Local projection variance impulse response," Empirical Economics, Springer, vol. 62(3), pages 1219-1244, March.
    314. Liu, Yuanyuan & Niu, Zibo & Suleman, Muhammad Tahir & Yin, Libo & Zhang, Hongwei, 2022. "Forecasting the volatility of crude oil futures: The role of oil investor attention and its regime switching characteristics under a high-frequency framework," Energy, Elsevier, vol. 238(PA).
    315. Asgharian, Hossein & Nossman, Marcus, 2011. "Risk contagion among international stock markets," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 22-38, February.
    316. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    317. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of International REITs: The Role of Realized Skewness and Realized Kurtosis," Working Papers 202114, University of Pretoria, Department of Economics.
    318. Ewald, Christian & Zou, Yihan, 2021. "Stochastic volatility: A tale of co-jumps, non-normality, GMM and high frequency data," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 37-52.
    319. Jiang, George J. & Oomen, Roel C.A., 2008. "Testing for jumps when asset prices are observed with noise-a "swap variance" approach," Journal of Econometrics, Elsevier, vol. 144(2), pages 352-370, June.
    320. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2020. "Examining stress in Asian currencies: A perspective offered by high frequency financial market data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    321. Becker, Ralf & Clements, Adam E. & McClelland, Andrew, 2009. "The jump component of S&P 500 volatility and the VIX index," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1033-1038, June.
    322. Sonnan Chen & Yuchi Gu, 2021. "Joint estimation of volatility risk and tail risk premia with time-varying macro-state-dependent property," Review of Quantitative Finance and Accounting, Springer, vol. 56(4), pages 1357-1397, May.
    323. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
    324. Duan, Yunpeng & Xue, Yi, 2014. "Bipower variation with jumps and correlated returns," Economics Letters, Elsevier, vol. 125(3), pages 367-371.
    325. Mohammad Abu Sayeed & Mardi Dungey & Wenying Yao, 2018. "High-frequency Characterisation of Indian Banking Stocks," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2_suppl), pages 213-238, August.
    326. Peng, Huan & Chen, Ruoxun & Mei, Dexiang & Diao, Xiaohua, 2018. "Forecasting the realized volatility of the Chinese stock market: Do the G7 stock markets help?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 78-85.
    327. Ahmed, Walid M.A., 2020. "Is there a risk-return trade-off in cryptocurrency markets? The case of Bitcoin," Journal of Economics and Business, Elsevier, vol. 108(C).
    328. Eunjeong Choi & Soohwan Cho & Dong Keun Kim, 2020. "Power Demand Forecasting using Long Short-Term Memory (LSTM) Deep-Learning Model for Monitoring Energy Sustainability," Sustainability, MDPI, vol. 12(3), pages 1-14, February.
    329. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2013. "Stylized Facts and Dynamic Modeling of High-frequency Data on Precious Metals," Working Papers on Finance 1318, University of St. Gallen, School of Finance.
    330. Simon Clinet & Yoann Potiron, 2021. "Estimation for high-frequency data under parametric market microstructure noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
    331. Friesen, Geoffrey C. & Weller, Paul A. & Dunham, Lee M., 2009. "Price trends and patterns in technical analysis: A theoretical and empirical examination," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1089-1100, June.
    332. Lyócsa, Štefan & Molnár, Peter, 2017. "The effect of non-trading days on volatility forecasts in equity markets," Finance Research Letters, Elsevier, vol. 23(C), pages 39-49.
    333. Tim Bollerslev & Viktor Todorov, 2011. "Estimation of Jump Tails," Econometrica, Econometric Society, vol. 79(6), pages 1727-1783, November.
    334. González-Urteaga, Ana & Muga, Luis & Santamaria, Rafael, 2015. "Momentum and default risk. Some results using the jump component," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 185-193.
    335. Huang, Darien & Schlag, Christian & Shaliastovich, Ivan & Thimme, Julian, 2018. "Volatility-of-volatility risk," SAFE Working Paper Series 210, Leibniz Institute for Financial Research SAFE.
    336. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," Journal of Econometrics, Elsevier, vol. 193(2), pages 367-389.
    337. Zhi Liu, 2017. "Jump-robust estimation of volatility with simultaneous presence of microstructure noise and multiple observations," Finance and Stochastics, Springer, vol. 21(2), pages 427-469, April.
    338. Deniz Erdemlioglu & Sebastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    339. Çelik, Sibel & Ergin, Hüseyin, 2014. "Volatility forecasting using high frequency data: Evidence from stock markets," Economic Modelling, Elsevier, vol. 36(C), pages 176-190.
    340. Xie, Haibin & Yu, Chengtan, 2020. "Realized GARCH models: Simpler is better," Finance Research Letters, Elsevier, vol. 33(C).
    341. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.
    342. Visser, Marcel P., 2008. "Forecasting S&P 500 Daily Volatility using a Proxy for Downward Price Pressure," MPRA Paper 11100, University Library of Munich, Germany.
    343. Garcia, René & Renault, Eric & Veredas, David, 2011. "Estimation of stable distributions by indirect inference," Journal of Econometrics, Elsevier, vol. 161(2), pages 325-337, April.
    344. Nirei, Makoto & Sushko, Vladyslav, 2011. "Jumps in foreign exchange rates and stochastic unwinding of carry trades," International Review of Economics & Finance, Elsevier, vol. 20(1), pages 110-127, January.
    345. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.
    346. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, Department of Economics and Business Economics, Aarhus University.
    347. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2007. "Power variation for Gaussian processes with stationary increments," CREATES Research Papers 2007-42, Department of Economics and Business Economics, Aarhus University.
    348. Atak, Alev & Kapetanios, George, 2013. "A factor approach to realized volatility forecasting in the presence of finite jumps and cross-sectional correlation in pricing errors," Economics Letters, Elsevier, vol. 120(2), pages 224-228.
    349. Degiannakis, Stavros & Filis, George, 2022. "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, vol. 123(C).
    350. Thibault Vatter & Hau-Tieng Wu & Valérie Chavez-Demoulin & Bin Yu, 2015. "Non-Parametric Estimation of Intraday Spot Volatility: Disentangling Instantaneous Trend and Seasonality," Econometrics, MDPI, vol. 3(4), pages 1-24, December.
    351. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
    352. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    353. Bollerslev, Tim & Todorov, Viktor, 2014. "Time-varying jump tails," Journal of Econometrics, Elsevier, vol. 183(2), pages 168-180.
    354. Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.
    355. Jawadi, Fredj & Louhichi, Waël & Idi Cheffou, Abdoulkarim, 2015. "Testing and modeling jump contagion across international stock markets: A nonparametric intraday approach," Journal of Financial Markets, Elsevier, vol. 26(C), pages 64-84.
    356. Qian, Lihua & Wang, Jiqian & Ma, Feng & Li, Ziyang, 2022. "Bitcoin volatility predictability–The role of jumps and regimes," Finance Research Letters, Elsevier, vol. 47(PB).
    357. Gianluca Cubadda & Barbara Guardabascio & Alain Hecq, 2016. "A Vector Heterogeneous Autoregressive Index Model for Realized Volatily Measures," CEIS Research Paper 391, Tor Vergata University, CEIS, revised 23 Jul 2016.
    358. Liu, Min & Lee, Chien-Chiang, 2021. "Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting," Energy Economics, Elsevier, vol. 103(C).
    359. J. Piplack & M. Beine & B. Candelon, 2009. "Comovements of Returns and Volatility in International Stock Markets: A High-Frequency Approach," Working Papers 09-10, Utrecht School of Economics.
    360. Bandi, Federico M. & Renò, Roberto, 2012. "Time-varying leverage effects," Journal of Econometrics, Elsevier, vol. 169(1), pages 94-113.
    361. Odusami, Babatunde O., 2021. "Volatility jumps and their determinants in REIT returns," Journal of Economics and Business, Elsevier, vol. 113(C).
    362. Vyacheslav Abramov & Fima Klebaner, 2007. "Estimation and Prediction of a Non-Constant Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(1), pages 1-23, March.
    363. Lars Winkelmann & Markus Bibinger & Tobias Linzert, 2016. "ECB Monetary Policy Surprises: Identification Through Cojumps in Interest Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 613-629, June.
    364. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Duration-Based Volatility Estimation," Global COE Hi-Stat Discussion Paper Series gd08-034, Institute of Economic Research, Hitotsubashi University.
    365. Garcia, René & Lewis, Marc-André & Pastorello, Sergio & Renault, Éric, 2011. "Estimation of objective and risk-neutral distributions based on moments of integrated volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 22-32, January.
    366. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2020. "Uncertainty due to Infectious Diseases and Forecastability of the Realized Variance of US REITs: A Note," Working Papers 202099, University of Pretoria, Department of Economics.
    367. Ysusi Carla, 2007. "Multipower Variation Under Market Microstructure Effects," Working Papers 2007-13, Banco de México.
    368. Carlo Rosa, 2013. "The high-frequency response of energy prices to monetary policy: understanding the empirical evidence," Staff Reports 598, Federal Reserve Bank of New York.
    369. Bjursell, Johan & Gentle, James E. & Wang, George H.K., 2015. "Inventory announcements, jump dynamics, volatility and trading volume in U.S. energy futures markets," Energy Economics, Elsevier, vol. 48(C), pages 336-349.
    370. Baum, Christopher F. & Zerilli, Paola, 2016. "Jumps and stochastic volatility in crude oil futures prices using conditional moments of integrated volatility," Energy Economics, Elsevier, vol. 53(C), pages 175-181.
    371. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian & Yoon, Seong-Min, 2021. "OPEC news and jumps in the oil market," Energy Economics, Elsevier, vol. 96(C).
    372. Cartea, Álvaro & Karyampas, Dimitrios, 2009. "The relationship between the volatility of returns and the number of jumps in financial markets," DEE - Working Papers. Business Economics. WB wb097508, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    373. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
    374. Dimitrios Louzis & Spyros Xanthopoulos-Sisinis & Apostolos Refenes, 2011. "Stock index realized volatility forecasting in the presence of heterogeneous leverage effects and long range dependence in the volatility of realized volatility," Post-Print hal-00709559, HAL.
    375. Vortelinos, Dimitrios I. & Thomakos, Dimitrios D., 2013. "Nonparametric realized volatility estimation in the international equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 34-45.
    376. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "Dynamic asset price jumps and the performance of high frequency tests and measures," Monash Econometrics and Business Statistics Working Papers 14/17, Monash University, Department of Econometrics and Business Statistics.
    377. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
    378. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
    379. Zeng, Qing & Lu, Xinjie & Li, Tao & Wu, Lan, 2022. "Jumps and stock market variance during the COVID-19 pandemic: Evidence from international stock markets," Finance Research Letters, Elsevier, vol. 48(C).
    380. Dimitrios Vortelinos & Dimitrios Thomakos, 2009. "Realized Volatility and Jumps in the Athens Stock Exchange," Working Papers 00044, University of Peloponnese, Department of Economics.
    381. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
    382. Kyungsub Lee & Byoung Ki Seo, 2019. "Performance of tail hedged portfolio with third moment variation swap," Papers 1908.05105, arXiv.org.
    383. David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Brendan P.M. McCabe, 2018. "Approximate Bayesian forecasting," Monash Econometrics and Business Statistics Working Papers 2/18, Monash University, Department of Econometrics and Business Statistics.
    384. Li, Yingying & Xie, Shangyu & Zheng, Xinghua, 2016. "Efficient estimation of integrated volatility incorporating trading information," Journal of Econometrics, Elsevier, vol. 195(1), pages 33-50.
    385. Dungey, Mardi & McKenzie, Michael & Smith, L. Vanessa, 2009. "Empirical evidence on jumps in the term structure of the US Treasury Market," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 430-445, June.
    386. Bedoui, Rihab & Braeik, Sana & Goutte, Stéphane & Guesmi, Khaled, 2018. "On the study of conditional dependence structure between oil, gold and USD exchange rates," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 134-146.
    387. Paweł Kliber, 2019. "Continuous and jump changes in prices processes in the selected stock markets," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 54, pages 333-344.
    388. Markku Lanne, 2006. "Forecasting Realized Volatility by Decomposition," Economics Working Papers ECO2006/20, European University Institute.
    389. Wang, Jiqian & Huang, Yisu & Ma, Feng & Chevallier, Julien, 2020. "Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? New evidence," Energy Economics, Elsevier, vol. 91(C).
    390. Arouri, Mohamed & M’saddek, Oussama & Pukthuanthong, Kuntara, 2019. "Jump risk premia across major international equity markets," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 1-21.
    391. Czado, Claudia & Ivanov, Eugen & Okhrin, Yarema, 2019. "Modelling temporal dependence of realized variances with vines," Econometrics and Statistics, Elsevier, vol. 12(C), pages 198-216.
    392. Torben B. Rasmussen, 2009. "Jump Testing and the Speed of Market Adjustment," CREATES Research Papers 2009-08, Department of Economics and Business Economics, Aarhus University.
    393. Lucio Maria Calcagnile & Giacomo Bormetti & Michele Treccani & Stefano Marmi & Fabrizio Lillo, 2015. "Collective synchronization and high frequency systemic instabilities in financial markets," Papers 1505.00704, arXiv.org.
    394. Jean Jacod & Mark Podolskij & Mathias Vetter, 2008. "Intertemporal Asset Allocation with Habit Formation in Preferences: An Approximate Analytical Solution," CREATES Research Papers 2008-61, Department of Economics and Business Economics, Aarhus University.
    395. Avouyi-Dovi, S. & Idier, J., 2010. "Central bank liquidity and market liquidity: the role of collateral provision on the French government debt securities market," Working papers 278, Banque de France.
    396. Haugom, Erik & Westgaard, Sjur & Solibakke, Per Bjarte & Lien, Gudbrand, 2011. "Realized volatility and the influence of market measures on predictability: Analysis of Nord Pool forward electricity data," Energy Economics, Elsevier, vol. 33(6), pages 1206-1215.
    397. David S. Bates, 2016. "How Crashes Develop: Intradaily Volatility and Crash Evolution," NBER Working Papers 22028, National Bureau of Economic Research, Inc.
    398. Gupta, Varun & Perera, Sandun, 2021. "Managing surges in online demand using bandwidth throttling: An optimal strategy amid the COVID-19 pandemic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    399. Torben G. Andersen & Tim Bollerslev & Dobrislav Dobrev, 2007. "No-Arbitrage Semi-Martingale Restrictions for Continuous-Time Volatility Models subject to Leverage Effects, Jumps and i.i.d. Noise: Theory and Testable Distributional Implications," NBER Working Papers 12963, National Bureau of Economic Research, Inc.
    400. Huang, Henry H. & Wang, Kent & Wang, Zhanglong, 2016. "A test of efficiency for the S&P 500 index option market using the generalized spectrum method," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 52-70.
    401. Ralf Becker & Adam Clements, 2010. "Volatility and the role of order book structure," NCER Working Paper Series 64, National Centre for Econometric Research.
    402. Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2019. "Forecasting Realized Volatility of Agricultural Commodities," MPRA Paper 96267, University Library of Munich, Germany.
    403. Dimitrios Karyampas & Paola Paiardini, 2011. "Probability of Informed Trading and Volatility for an ETF," Birkbeck Working Papers in Economics and Finance 1101, Birkbeck, Department of Economics, Mathematics & Statistics.
    404. Demirer, Riza & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2019. "Time-varying risk aversion and realized gold volatility," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    405. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2020. "Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    406. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    407. Sévi, Benoît, 2015. "Explaining the convenience yield in the WTI crude oil market using realized volatility and jumps," Economic Modelling, Elsevier, vol. 44(C), pages 243-251.
    408. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    409. Wang, Bin & Zheng, Xu, 2022. "Testing for the presence of jump components in jump diffusion models," Journal of Econometrics, Elsevier, vol. 230(2), pages 483-509.
    410. Radu LUPU & Alexandra MATEESCU & Mihai MITRACHE, 2017. "Analysis of Macroeconomic Events Impact Using the Event Study Methodology," Hyperion Economic Journal, Faculty of Economic Sciences, Hyperion University of Bucharest, Romania, vol. 5(2), pages 3-13, June.
    411. Adam Albogatchiev & Jean-Sébastien Fontaine & Jabir Sandhu & Reginald Xie, 2018. "The Impact of Surprising Monetary Policy Announcements on Exchange Rate Volatility," Staff Analytical Notes 2018-39, Bank of Canada.
    412. Markus Bibinger & Mathias Vetter, 2015. "Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 707-743, August.
    413. Inekwe John Nkwoma, 2014. "Business Cycle Variability and Growth Linkage," Monash Economics Working Papers 38-14, Monash University, Department of Economics.
    414. Duan, Yinying & Chen, Wang & Zeng, Qing & Liu, Zhicao, 2018. "Leverage effect, economic policy uncertainty and realized volatility with regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 148-154.
    415. Liu, Wenwen & Gui, Yiming & Qiao, Gaoxiu, 2022. "Dynamics lead-lag relationship of jumps among Chinese stock index and futures market during the Covid-19 epidemic," Research in International Business and Finance, Elsevier, vol. 61(C).
    416. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.
    417. M. Podolskij & D. Ziggel, 2010. "New tests for jumps in semimartingale models," Statistical Inference for Stochastic Processes, Springer, vol. 13(1), pages 15-41, April.
    418. Lam, K.P. & Ng, H.S., 2009. "Intra-daily information of range-based volatility for MEM-GARCH," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2625-2632.
    419. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2012. "Ranking systemically important financial institutions," Working Papers 15473, University of Tasmania, Tasmanian School of Business and Economics, revised 21 Nov 2012.
    420. Lavička, H. & Lichard, T. & Novotný, J., 2016. "Sand in the wheels or wheels in the sand? Tobin taxes and market crashes," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 328-342.
    421. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    422. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.
    423. Pan, Zhiyuan & Shuai, Jiangyu & Liang, Zhilei & Sun, Xianchao, 2022. "Jump dynamics, spillover effect and option valuation," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    424. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Wang, Jianqiong, 2020. "Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models," Energy, Elsevier, vol. 212(C).
    425. Maslyuk-Escobedo, Svetlana & Rotaru, Kristian & Dokumentov, Alexander, 2017. "News sentiment and jumps in energy spot and futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 186-210.
    426. Schulz, Frowin C., 2010. "Robust estimation of integrated variance and quarticity under flat price and no trading bias," Discussion Papers in Econometrics and Statistics 4/10, University of Cologne, Institute of Econometrics and Statistics.
    427. Hotta, Luiz & Trucíos, Carlos & Ruiz Ortega, Esther, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    428. Özbekler, Ali Gencay & Kontonikas, Alexandros & Triantafyllou, Athanasios, 2020. "Volatility Forecasting in European Government Bond Markets," Essex Finance Centre Working Papers 27362, University of Essex, Essex Business School.
    429. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.
    430. Valenzuela, Marcela & Zer, Ilknur & Fryzlewicz, Piotr & Rheinländer, Thorsten, 2015. "Relative liquidity and future volatility," Journal of Financial Markets, Elsevier, vol. 24(C), pages 25-48.
    431. Wen, Zhuzhu & Gong, Xu & Ma, Diandian & Xu, Yahua, 2021. "Intraday momentum and return predictability: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 95(C), pages 374-384.
    432. Amorino, Chiara & Gloter, Arnaud, 2020. "Unbiased truncated quadratic variation for volatility estimation in jump diffusion processes," Stochastic Processes and their Applications, Elsevier, vol. 130(10), pages 5888-5939.
    433. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    434. Štefan Lyócsa & Peter Molnár, 2016. "Volatility forecasting of strategically linked commodity ETFs: gold-silver," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1809-1822, December.
    435. Avouyi-Dovi, S. & Idier, J., 2011. "The impact of unconventional monetary policy on the market for collateral: The case of the French bond market," Working papers 339, Banque de France.
    436. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
    437. Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
    438. Aitor Ciarreta & Peru Muniain & Ainhoa Zarraga, 2020. "Realized volatility and jump testing in the Japanese electricity spot market," Empirical Economics, Springer, vol. 58(3), pages 1143-1166, March.
    439. José Figueroa-López, 2012. "Statistical estimation of Lévy-type stochastic volatility models," Annals of Finance, Springer, vol. 8(2), pages 309-335, May.
    440. Wing Hong Chan & Ranjini Jha & Madhu Kalimipalli, 2009. "The Economic Value Of Using Realized Volatility In Forecasting Future Implied Volatility," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 32(3), pages 231-259, September.
    441. Yunus Emre Ergemen & Abderrahim Taamouti, 2015. "Parametric Portfolio Policies with Common Volatility Dynamics," CREATES Research Papers 2015-41, Department of Economics and Business Economics, Aarhus University.
    442. Juan M. Londono, 2016. "Bad Bad Contagion," International Finance Discussion Papers 1178, Board of Governors of the Federal Reserve System (U.S.).
    443. Mancini, Cecilia & Renò, Roberto, 2011. "Threshold estimation of Markov models with jumps and interest rate modeling," Journal of Econometrics, Elsevier, vol. 160(1), pages 77-92, January.
    444. Qiao, Gaoxiu & Teng, Yuxin & Li, Weiping & Liu, Wenwen, 2019. "Improving volatility forecasting based on Chinese volatility index information: Evidence from CSI 300 index and futures markets," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 133-151.
    445. Chuliá, Helena & Martens, Martin & Dijk, Dick van, 2010. "Asymmetric effects of federal funds target rate changes on S&P100 stock returns, volatilities and correlations," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 834-839, April.
    446. Chao Yu & Yue Fang & Zeng Li & Bo Zhang & Xujie Zhao, 2014. "Non-Parametric Estimation Of High-Frequency Spot Volatility For Brownian Semimartingale With Jumps," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 572-591, November.
    447. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    448. Yang, Ben-Zhang & Yue, Jia & Wang, Ming-Hui & Huang, Nan-Jing, 2019. "Volatility swaps valuation under stochastic volatility with jumps and stochastic intensity," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 73-84.
    449. Won Seo, Sung & Jin Chung, Hae, 2017. "Capital structure and corporate reaction to negative stock return shocks," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 292-312.
    450. Daniela Osterrieder & Daniel Ventosa-Santaulària & J. Eduardo Vera-Valdés, 2015. "Unbalanced Regressions and the Predictive Equation," CREATES Research Papers 2015-09, Department of Economics and Business Economics, Aarhus University.
    451. Dahlqvist, Carl-Henrik & Gnabo, Jean-Yves, 2018. "Effective network inference through multivariate information transfer estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 376-394.
    452. Luca Spadafora & Francesca Sivero & Nicola Picchiotti, 2018. "Jumping VaR: Order Statistics Volatility Estimator for Jumps Classification and Market Risk Modeling," Papers 1803.07021, arXiv.org, revised Mar 2018.
    453. Roh, Tai-Yong & Byun, Suk Joon & Xu, Yahua, 2020. "Downside uncertainty shocks in the oil and gold markets," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 291-307.
    454. Flávio B. Gonçalves & Gareth O. Roberts, 2014. "Exact Simulation Problems for Jump-Diffusions," Methodology and Computing in Applied Probability, Springer, vol. 16(4), pages 907-930, December.
    455. Ma, Feng & Liu, Jing & Wahab, M.I.M. & Zhang, Yaojie, 2018. "Forecasting the aggregate oil price volatility in a data-rich environment," Economic Modelling, Elsevier, vol. 72(C), pages 320-332.
    456. Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
    457. José E. Figueroa-López & Jeffrey Nisen, 2019. "Second-order properties of thresholded realized power variations of FJA additive processes," Statistical Inference for Stochastic Processes, Springer, vol. 22(3), pages 431-474, October.
    458. Aktas, Osman Ulas & Kryzanowski, Lawrence & Zhang, Jie, 2021. "Volatility spillover around price limits in an emerging market," Finance Research Letters, Elsevier, vol. 39(C).
    459. Zhang, Congshan & Li, Jia & Todorov, Viktor & Tauchen, George, 2022. "Variation and efficiency of high-frequency betas," Journal of Econometrics, Elsevier, vol. 228(1), pages 156-175.
    460. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Aug 2018.
    461. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    462. Chao YU & Xujie ZHAO, 2021. "Measuring the Jump Risk Contribution under Market Microstructure Noise – Evidence from Chinese Stock Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 32-47, December.
    463. Yi, Chae-Deug, 2020. "Jump probability using volatility periodicity filters in US Dollar/Euro exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    464. Ulrich Hounyo, 2013. "Bootstrapping realized volatility and realized beta under a local Gaussianity assumption," CREATES Research Papers 2013-30, Department of Economics and Business Economics, Aarhus University.
    465. Lanne, Markku, 2007. "Forecasting realized exchange rate volatility by decomposition," International Journal of Forecasting, Elsevier, vol. 23(2), pages 307-320.
    466. Xie, Haibin & Qi, Nan & Wang, Shouyang, 2019. "A new variant of RealGARCH for volatility modeling," Finance Research Letters, Elsevier, vol. 28(C), pages 438-443.
    467. Bruno Feunou & Cédric Okou, 2017. "Good Volatility, Bad Volatility and Option Pricing," Staff Working Papers 17-52, Bank of Canada.
    468. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    469. Bollerslev, Tim & Li, Sophia Zhengzi & Todorov, Viktor, 2016. "Roughing up beta: Continuous versus discontinuous betas and the cross section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 120(3), pages 464-490.
    470. Dewachter, Hans & Erdemlioglu, Deniz & Gnabo, Jean-Yves & Lecourt, Christelle, 2014. "The intra-day impact of communication on euro-dollar volatility and jumps," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 131-154.
    471. Wanidwaranan, Phasin & Padungsaksawasdi, Chaiyuth, 2020. "The effect of return jumps on herd behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    472. Yang Gao & Chengjie Zhao & Bianxia Sun & Wandi Zhao, 2022. "Effects of investor sentiment on stock volatility: new evidences from multi-source data in China’s green stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-30, December.
    473. Dimos Kambouroudis & David McMillan & Katerina Tsakou, 2019. "Forecasting Realized Volatility: The role of implied volatility, leverage effect, overnight returns and volatility of realized volatility," Working Papers 2019-03, Swansea University, School of Management.
    474. Alam, Md. Samsul & Shahzad, Syed Jawad Hussain & Ferrer, Román, 2019. "Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility," Energy Economics, Elsevier, vol. 84(C).
    475. Xin Huang, 2015. "Macroeconomic News Announcements, Systemic Risk, Financial Market Volatility and Jumps," Finance and Economics Discussion Series 2015-97, Board of Governors of the Federal Reserve System (U.S.).
    476. Vortelinos, Dimitrios I., 2014. "Optimally sampled realized range-based volatility estimators," Research in International Business and Finance, Elsevier, vol. 30(C), pages 34-50.
    477. Konstantinos Gkillas & Dimitrios Vortelinos & Christos Floros & Alexandros Garefalakis & Nikolaos Sariannidis, 2020. "Greek sovereign crisis and European exchange rates: effects of news releases and their providers," Annals of Operations Research, Springer, vol. 294(1), pages 515-536, November.
    478. Andras Fulop & Junye Li & Jun Yu, 2012. "Investigating Impacts of Self-Exciting Jumps in Returns and Volatility: A Bayesian Learning Approach," Global COE Hi-Stat Discussion Paper Series gd12-264, Institute of Economic Research, Hitotsubashi University.
    479. Wang, Chengyang & Nishiyama, Yoshihiko, 2015. "Volatility forecast of stock indices by model averaging using high-frequency data," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 324-337.
    480. Bucci, Andrea, 2019. "Cholesky-ANN models for predicting multivariate realized volatility," MPRA Paper 95137, University Library of Munich, Germany.
    481. Martens, Martin & van Dijk, Dick & de Pooter, Michiel, 2009. "Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements," International Journal of Forecasting, Elsevier, vol. 25(2), pages 282-303.
    482. Gianluca Cubadda & Alain Hecq & Antonio Riccardo, 2018. "Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector," CEIS Research Paper 445, Tor Vergata University, CEIS, revised 30 Oct 2018.
    483. Fredj Jawadi & Waël Louhichi & Abdoulkarim Idi Cheffou & Rivo Randrianarivony, 2016. "Intraday jumps and trading volume: a nonlinear Tobit specification," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1167-1186, November.
    484. Creal, Drew D., 2008. "Analysis of filtering and smoothing algorithms for Lévy-driven stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2863-2876, February.
    485. Sensoy, Ahmet & Serdengeçti, Süleyman, 2020. "Impact of portfolio flows and heterogeneous expectations on FX jumps: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 68(C).
    486. Peter Christoffersen & Bruno Feunou & Yoontae Jeon & Chayawat Ornthanalai, 2016. "Time-Varying Crash Risk: The Role of Stock Market Liquidity," Staff Working Papers 16-35, Bank of Canada.
    487. Ma, Chaoqun & Mi, Xianhua & Cai, Zongwu, 2020. "Nonlinear and time-varying risk premia," China Economic Review, Elsevier, vol. 62(C).
    488. Lucio Maria Calcagnile & Fulvio Corsi & Stefano Marmi, 2016. "Entropy and efficiency of the ETF market," Papers 1609.04199, arXiv.org.
    489. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    490. Slim, Skander & Dahmene, Meriam, 2016. "Asymmetric information, volatility components and the volume–volatility relationship for the CAC40 stocks," Global Finance Journal, Elsevier, vol. 29(C), pages 70-84.
    491. Qu, Hui & Duan, Qingling & Niu, Mengyi, 2018. "Modeling the volatility of realized volatility to improve volatility forecasts in electricity markets," Energy Economics, Elsevier, vol. 74(C), pages 767-776.
    492. Mete Kilic & Ivan Shaliastovich, 2019. "Good and Bad Variance Premia and Expected Returns," Management Science, INFORMS, vol. 67(6), pages 2522-2544, June.
    493. Dobrislav Dobrev & Pawel J. Szerszen, 2010. "The information content of high-frequency data for estimating equity return models and forecasting risk," Finance and Economics Discussion Series 2010-45, Board of Governors of the Federal Reserve System (U.S.).
    494. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
    495. Křehlík, Tomáš & Baruník, Jozef, 2017. "Cyclical properties of supply-side and demand-side shocks in oil-based commodity markets," Energy Economics, Elsevier, vol. 65(C), pages 208-218.
    496. Taylor, Nick, 2017. "Realised variance forecasting under Box-Cox transformations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 770-785.
    497. Cartea, Álvaro & Karyampas, Dimitrios, 2009. "Volatility and covariation of financial assets: a high-frequency analysis," DEE - Working Papers. Business Economics. WB wb097609, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    498. Piotr Fiszeder & Grzegorz Perczak, 2013. "A new look at variance estimation based on low, high and closing prices taking into account the drift," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(4), pages 456-481, November.
    499. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    500. Melanie Frick & Annabelle Kehl, 2010. "Event risk—Parametrization and estimation in a generalized Pareto model with time-varying thresholds," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 455-460.
    501. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    502. Johnson, James A. & Medeiros, Marcelo C. & Paye, Bradley S., 2022. "Jumps in stock prices: New insights from old data," Journal of Financial Markets, Elsevier, vol. 60(C).
    503. Vortelinos, Dimitrios I., 2010. "The properties of realized correlation: Evidence from the French, German and Greek equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 273-290, August.
    504. George Jiang & Ingrid Lo & Adrien Verdelhan, 2008. "Information Shocks, Jumps, and Price Discovery -- Evidence from the U.S. Treasury Market," Staff Working Papers 08-22, Bank of Canada.
    505. Hui Qu & Ping Ji, 2016. "Modeling Realized Volatility Dynamics with a Genetic Algorithm," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(5), pages 434-444, August.
    506. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena.
    507. Worapree Maneesoonthorn & Gael M Martin & Catherine S Forbes, 2018. "Dynamic price jumps: The performance of high frequency tests and measures, and the robustness of inference," Monash Econometrics and Business Statistics Working Papers 17/18, Monash University, Department of Econometrics and Business Statistics.
    508. Gong, Xu & Lin, Boqiang, 2019. "Modeling stock market volatility using new HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 194-211.
    509. Liu, Min, 2022. "The driving forces of green bond market volatility and the response of the market to the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 288-309.
    510. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    511. Kshatriya, Saranya & Prasanna, Krishna, 2021. "Jump Interdependencies: Stochastic linkages among international stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    512. Todorov, Viktor & Tauchen, George & Grynkiv, Iaryna, 2011. "Realized Laplace transforms for estimation of jump diffusive volatility models," Journal of Econometrics, Elsevier, vol. 164(2), pages 367-381, October.
    513. Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
    514. Anzarut, Michelle & Mena, Ramsés H., 2019. "A Harris process to model stochastic volatility," Econometrics and Statistics, Elsevier, vol. 10(C), pages 151-169.
    515. Tim Bollerslev & Viktor Todorov, 2010. "Jump Tails, Extreme Dependencies, and the Distribution of Stock Returns," CREATES Research Papers 2010-64, Department of Economics and Business Economics, Aarhus University.
    516. Aganin, Artem, 2017. "Forecast comparison of volatility models on Russian stock market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 48, pages 63-84.
    517. Ceylan, Ozcan, 2012. "Time-Varying Volatility Asymmetry: A Conditioned HAR-RV(CJ) EGARCH-M Model," GIAM Working Papers 12-4, Galatasaray University Economic Research Center.
    518. Haugom, Erik & Ullrich, Carl J., 2012. "Forecasting spot price volatility using the short-term forward curve," Energy Economics, Elsevier, vol. 34(6), pages 1826-1833.
    519. Ana-Maria Dumitru & Giovanni Urga, 2011. "Identifying Jumps in Financial Assets: A Comparison Between Nonparametric Jump Tests," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 242-255, October.
    520. Bing-Yi Jing & Zhi Liu & Xin-Bing Kong, 2014. "On the Estimation of Integrated Volatility With Jumps and Microstructure Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 457-467, July.
    521. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    522. Fulvio Corsi & Roberto Renò, 2012. "Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 368-380, January.
    523. Lena Cleanthous & Pany Karamanou, 2011. "The ECB Monetary Policy and the Current Financial Crisis," Working Papers 2011-1, Central Bank of Cyprus.
    524. Diego Amaya & Peter Christoffersen & Kris Jacobs & Aurelio Vasquez, 2013. "Does Realized Skewness Predict the Cross-Section of Equity Returns?," CREATES Research Papers 2013-41, Department of Economics and Business Economics, Aarhus University.
    525. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2015. "Modelling systemic price cojumps with Hawkes factor models," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1137-1156, July.
    526. Ghysels, Eric & Sohn, Bumjean, 2009. "Which power variation predicts volatility well?," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 686-700, September.
    527. T. -N. Nguyen & M. -N. Tran & R. Kohn, 2020. "Recurrent Conditional Heteroskedasticity," Papers 2010.13061, arXiv.org, revised Jan 2022.
    528. Patrick Chang, 2020. "Fourier instantaneous estimators and the Epps effect," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-24, September.
    529. Donatien Hainaut, 2016. "A model for interest rates with clustering effects," Quantitative Finance, Taylor & Francis Journals, vol. 16(8), pages 1203-1218, August.
    530. Perron, Benoit, 2004. "Détection non paramétrique de sauts dans la volatilité des marchés financiers," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 229-251, Juin-Sept.
    531. Yu, Jialin, 2007. "Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese Yuan," Journal of Econometrics, Elsevier, vol. 141(2), pages 1245-1280, December.
    532. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
    533. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.
    534. John, Kose & Li, Jingrui, 2021. "COVID-19, volatility dynamics, and sentiment trading," Journal of Banking & Finance, Elsevier, vol. 133(C).
    535. Ole E. Barndorff-Nielsen & Svend Erik Graversen & Neil Shephard, 2003. "Power variation & stochastic volatility: a review and some new results," Economics Papers 2003-W19, Economics Group, Nuffield College, University of Oxford.
    536. Jan Hanousek & Jan Novotný, 2014. "Cenové skoky během finanční nejistoty: od intuice k regulační perspektivě [Price Jumps during Financial Crisis: From Intuition to Financial Regulation]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 32-48.
    537. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    538. Jean Jacod & Yingying Li & Per A. Mykland & Mark Podolskij & Mathias Vetter, 2007. "Microstructure Noise in the Continuous Case: The Pre-Averaging Approach - JLMPV-9," CREATES Research Papers 2007-43, Department of Economics and Business Economics, Aarhus University.
    539. Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.
    540. Christophe Boucher & Gilles de Truchis & Elena Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," EconomiX Working Papers 2017-20, University of Paris Nanterre, EconomiX.
    541. Glenn Kit Foong Ho & Sirimon Treepongkaruna & Marvin Wee & Chaiyuth Padungsaksawasdi, 2022. "The effect of short selling on volatility and jumps," Australian Journal of Management, Australian School of Business, vol. 47(1), pages 34-52, February.
    542. Ji, Qiang & Zhang, Dayong, 2019. "China’s crude oil futures: Introduction and some stylized facts," Finance Research Letters, Elsevier, vol. 28(C), pages 376-380.
    543. Gonçalves, Sílvia & Meddahi, Nour, 2011. "Box-Cox transforms for realized volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 129-144, January.
    544. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    545. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    546. Xie, Nan & Wang, Zongrun & Chen, Sicen & Gong, Xu, 2019. "Forecasting downside risk in China’s stock market based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 530-541.
    547. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Clement Kyei, 2019. "Monetary Policy Uncertainty and Volatility Jumps in Advanced Equity Markets," Working Papers 201939, University of Pretoria, Department of Economics.
    548. Dobrislav Dobrev & Pawel J. Szerszen, 2010. "The information content of high-frequency data for estimating equity return models and forecasting risk," International Finance Discussion Papers 1005, Board of Governors of the Federal Reserve System (U.S.).
    549. Chin Wen CHEONG & Lee Min CHERNG & Grace Lee Ching YAP, 2016. "Heterogeneous Market Hypothesis Evaluations using Various Jump-Robust Realized Volatility," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 50-64, December.
    550. Cheong, Chin Wen, 2008. "Time-varying volatility in Malaysian stock exchange: An empirical study using multiple-volatility-shift fractionally integrated model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 889-898.
    551. Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021. "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 46-61.
    552. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    553. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 29-56, Winter.
    554. Yuan, Ying & Zhang, Tonghui, 2020. "Forecasting stock market in high and low volatility periods: a modified multifractal volatility approach," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    555. Jan Novotný & Giovanni Urga, 2018. "Testing for Co-jumps in Financial Markets," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 118-128.
    556. Hwang, Eunju & Shin, Dong Wan, 2014. "A bootstrap test for jumps in financial economics," Economics Letters, Elsevier, vol. 125(1), pages 74-78.
    557. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Business Applications and State-Level Stock Market Realized Volatility: A Forecasting Experiment," Working Papers 202247, University of Pretoria, Department of Economics.
    558. B. Cooper Boniece & Jos'e E. Figueroa-L'opez & Yuchen Han, 2022. "Efficient Integrated Volatility Estimation in the Presence of Infinite Variation Jumps via Debiased Truncated Realized Variations," Papers 2209.10128, arXiv.org, revised Mar 2023.
    559. Qiang Liu & Zhi Liu & Chuanhai Zhang, 2020. "Heteroscedasticity test of high-frequency data with jumps and microstructure noise," Papers 2010.07659, arXiv.org.
    560. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Density Estimators for Daily Volatility Based on the Use of Realized Measures," Departmental Working Papers 200620, Rutgers University, Department of Economics.
    561. Jin-Huei Yeh & Jying-Nan Wang & Chung-Ming Kuan, 2014. "A noise-robust estimator of volatility based on interquantile ranges," Review of Quantitative Finance and Accounting, Springer, vol. 43(4), pages 751-779, November.
    562. Ciarreta, Aitor & Zarraga, Ainhoa, 2016. "Modeling realized volatility on the Spanish intra-day electricity market," Energy Economics, Elsevier, vol. 58(C), pages 152-163.
    563. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    564. Yu, Chao & Fang, Yue & Zhao, Xujie & Zhang, Bo, 2013. "Kernel filtering of spot volatility in presence of Lévy jumps and market microstructure noise," MPRA Paper 63293, University Library of Munich, Germany, revised 10 Mar 2014.
    565. Cuchiero, Christa & Teichmann, Josef, 2015. "Fourier transform methods for pathwise covariance estimation in the presence of jumps," Stochastic Processes and their Applications, Elsevier, vol. 125(1), pages 116-160.
    566. Hainaut, Donatien, 2016. "Impact of volatility clustering on equity indexed annuities," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 367-381.
    567. Lyócsa, Štefan & Todorova, Neda, 2021. "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, vol. 100(C).
    568. Elezovic, Suad, 2009. "Functional modelling of volatility in the Swedish limit order book," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2107-2118, April.
    569. Lars Winkelmann, 2010. "The Norges Bank’s key rate projections and the news element of monetary policy: a wavelet based jump detection approach," SFB 649 Discussion Papers SFB649DP2010-062, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    570. Fiszeder, Piotr & Perczak, Grzegorz, 2016. "Low and high prices can improve volatility forecasts during periods of turmoil," International Journal of Forecasting, Elsevier, vol. 32(2), pages 398-410.
    571. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    572. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    573. Jean Jacod, 2019. "Estimation of volatility in a high-frequency setting: a short review," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 351-385, December.
    574. Bissoondoyal-Bheenick, Emawtee & Brooks, Robert & Do, Hung Xuan & Smyth, Russell, 2020. "Exploiting the heteroskedasticity in measurement error to improve volatility predictions in oil and biofuel feedstock markets," Energy Economics, Elsevier, vol. 86(C).
    575. Odusami, Babatunde O, 2021. "Forecasting the Value-at-Risk of REITs using realized volatility jump models," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    576. Piccotti, Louis R., 2018. "Jumps, cojumps, and efficiency in the spot foreign exchange market," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 49-67.
    577. Wu, Liuren, 2011. "Variance dynamics: Joint evidence from options and high-frequency returns," Journal of Econometrics, Elsevier, vol. 160(1), pages 280-287, January.
    578. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2014. "Realized volatility models and alternative Value-at-Risk prediction strategies," Economic Modelling, Elsevier, vol. 40(C), pages 101-116.
    579. Cem Cakmakli & Verda Ozturk, 2021. "Economic Value of Modeling the Joint Distribution of Returns and Volatility: Leverage Timing," Koç University-TUSIAD Economic Research Forum Working Papers 2110, Koc University-TUSIAD Economic Research Forum.
    580. Jan Novotny, 2010. "Were Stocks during the Financial Crisis More Jumpy: A Comparative Study," CERGE-EI Working Papers wp416, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    581. Masato Ubukata & Toshiaki Watanabe, 2011. "Pricing Nikkei 225 Options Using Realized Volatility," IMES Discussion Paper Series 11-E-18, Institute for Monetary and Economic Studies, Bank of Japan.
    582. Gnabo, Jean-Yves & Hvozdyk, Lyudmyla & Lahaye, Jérôme, 2014. "System-wide tail comovements: A bootstrap test for cojump identification on the S&P 500, US bonds and currencies," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 147-174.
    583. Ben-zhang Yang & Jia Yue & Ming-hui Wang & Nan-jing Huang, 2018. "Volatility swaps valuation under stochastic volatility with jumps and stochastic intensity," Papers 1805.06226, arXiv.org, revised May 2018.
    584. Frömmel, Michael & Han, Xing & Kratochvil, Stepan, 2014. "Modeling the daily electricity price volatility with realized measures," Energy Economics, Elsevier, vol. 44(C), pages 492-502.
    585. Kaczmarek, Tomasz & Będowska-Sójka, Barbara & Grobelny, Przemysław & Perez, Katarzyna, 2022. "False Safe Haven Assets: Evidence From the Target Volatility Strategy Based on Recurrent Neural Network," Research in International Business and Finance, Elsevier, vol. 60(C).
    586. Chen, Yu-Lun & Tsai, Wei-Che, 2017. "Determinants of price discovery in the VIX futures market," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 59-73.
    587. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    588. Qu, Hui & Chen, Wei & Niu, Mengyi & Li, Xindan, 2016. "Forecasting realized volatility in electricity markets using logistic smooth transition heterogeneous autoregressive models," Energy Economics, Elsevier, vol. 54(C), pages 68-76.
    589. Chan, Kam Fong & Powell, John G. & Treepongkaruna, Sirimon, 2014. "Currency jumps and crises: Do developed and emerging market currencies jump together?," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 132-157.
    590. Peter Reinhard Hansen & Zhuo Huang & Chen Tong & Tianyi Wang, 2021. "Realized GARCH, CBOE VIX, and the Volatility Risk Premium," Papers 2112.05302, arXiv.org.
    591. Kam Fong Chan & Philip Gray, 2017. "Do Scheduled Macroeconomic Announcements Influence Energy Price Jumps?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(1), pages 71-89, January.
    592. Niu, Zibo & Ma, Feng & Zhang, Hongwei, 2022. "The role of uncertainty measures in volatility forecasting of the crude oil futures market before and during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 112(C).
    593. Liu, Guangying & Zhang, Xinsheng, 2011. "Power variation of fractional integral processes with jumps," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 962-972, August.
    594. Li, Yingying & Liu, Guangying & Zhang, Zhiyuan, 2022. "Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps," Journal of Econometrics, Elsevier, vol. 229(2), pages 422-451.
    595. Stefan Lyocsa & Peter Molnar & Igor Fedorko, 2016. "Forecasting Exchange Rate Volatility: The Case of the Czech Republic, Hungary and Poland," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(5), pages 453-475, October.
    596. Jiang, Wei & Ruan, Qingsong & Li, Jianfeng & Li, Ye, 2018. "Modeling returns volatility: Realized GARCH incorporating realized risk measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 249-258.
    597. Neda Todorova & Michael Soucek & Eduardo Roca, 2015. "Volatility spillovers from international commodity markets to the Australian equity market," Discussion Papers in Finance finance:201505, Griffith University, Department of Accounting, Finance and Economics.
    598. Todorov, Viktor, 2011. "Econometric analysis of jump-driven stochastic volatility models," Journal of Econometrics, Elsevier, vol. 160(1), pages 12-21, January.
    599. Neil Shephard & Silja Kinnebrock & Ole E. Barndorff-Neilsen, 2008. "Measuring downside risk - realised semivariance," Economics Series Working Papers 382, University of Oxford, Department of Economics.
    600. Adamantios Ntakaris & Giorgio Mirone & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Feature Engineering for Mid-Price Prediction with Deep Learning," Papers 1904.05384, arXiv.org, revised Jun 2019.
    601. Jia, Zhanliang & Cui, Meilan & Li, Handong, 2012. "Research on the relationship between the multifractality and long memory of realized volatility in the SSECI," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 740-749.
    602. Paula A. Yepes-Henao & Diego A. Agudelo & Ramazan Gencay, 2018. "Muddying the waters: Who Induces Volatility in an Emerging Market?," Documentos de Trabajo de Valor Público 16974, Universidad EAFIT.
    603. Chen, Xi & Wang, Junbo & Wu, Chunchi, 2022. "Jump and volatility risk in the cross-section of corporate bond returns," Journal of Financial Markets, Elsevier, vol. 60(C).
    604. Palandri, Alessandro, 2015. "Do negative and positive equity returns share the same volatility dynamics?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 486-505.
    605. Huang, Alex YiHou, 2016. "Impacts of implied volatility on stock price realized jumps," Economic Systems, Elsevier, vol. 40(4), pages 622-630.
    606. Ao Kong & Hongliang Zhu & Robert Azencott, 2019. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Papers 1912.07165, arXiv.org.
    607. Cecilia Mancini, 2009. "Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 270-296, June.
    608. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    609. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    610. Kim, Jihyun & Park, Joon & Wang, Bin, 2020. "Estimation of Volatility Functions in Jump Diffusions Using Truncated Bipower Increments," TSE Working Papers 20-1096, Toulouse School of Economics (TSE).
    611. Ma, Feng & Wei, Yu & Huang, Dengshi & Chen, Yixiang, 2014. "Which is the better forecasting model? A comparison between HAR-RV and multifractality volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 171-180.
    612. Fuertes, Ana-Maria & Izzeldin, Marwan & Kalotychou, Elena, 2009. "On forecasting daily stock volatility: The role of intraday information and market conditions," International Journal of Forecasting, Elsevier, vol. 25(2), pages 259-281.
    613. Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
    614. Frédéric Délèze & Syed Mujahid Hussain, 2014. "Information Arrival, Jumps and Cojumps in European Financial Markets: Evidence Using Tick by Tick Data," Multinational Finance Journal, Multinational Finance Journal, vol. 18(3-4), pages 169-213, September.
    615. Nattapong Laksomya & John G. Powell & Suparatana Tanthanongsakkun & Sirimon Treepongkaruna, 2018. "Are Internet message boards used to facilitate stock price manipulation? Evidence from an emerging market, Thailand," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 275-309, November.
    616. Tseng Tseng-Chan & Chung Huimin & Huang Chin-Sheng, 2009. "Modeling Jump and Continuous Components in the Volatility of Oil Futures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-30, May.
    617. Peter Reinhard Hansen & Guillaume Horel, 2009. "Quadratic Variation by Markov Chains," CREATES Research Papers 2009-13, Department of Economics and Business Economics, Aarhus University.
    618. Tian, Xiao & Duong, Huu Nhan & Kalev, Petko S., 2019. "Information content of the limit order book for crude oil futures price volatility," Energy Economics, Elsevier, vol. 81(C), pages 584-597.
    619. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    620. Ping, Yuan & Li, Rui, 2018. "Forecasting realized volatility based on the truncated two-scales realized volatility estimator (TTSRV): Evidence from China's stock market," Finance Research Letters, Elsevier, vol. 25(C), pages 222-229.
    621. Tian, Shuairu & Hamori, Shigeyuki, 2015. "Modeling interest rate volatility: A Realized GARCH approach," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 158-171.
    622. Benoît Sévi & César Baena, 2012. "A reassessment of the risk-return tradeoff at the daily horizon," Economics Bulletin, AccessEcon, vol. 32(1), pages 190-203.
    623. Martin, Vance L. & Tang, Chrismin & Yao, Wenying, 2018. "News and expected returns in East Asian equity markets: The RV-GARCHM model," Journal of Asian Economics, Elsevier, vol. 57(C), pages 36-52.
    624. Nkwoma, Inekwe John, 2017. "Futures-Based Measures Of Monetary Policy And Jump Risk," Macroeconomic Dynamics, Cambridge University Press, vol. 21(2), pages 384-405, March.
    625. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2016. "Common trends in global volatility," Journal of International Money and Finance, Elsevier, vol. 67(C), pages 194-214.
    626. Todorova, Neda & Clements, Adam E., 2018. "The volatility-volume relationship in the LME futures market for industrial metals," Resources Policy, Elsevier, vol. 58(C), pages 111-124.
    627. Wang, Jianxin & Yang, Minxian, 2009. "Asymmetric volatility in the foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 597-615, October.
    628. Ullrich, Carl J., 2012. "Realized volatility and price spikes in electricity markets: The importance of observation frequency," Energy Economics, Elsevier, vol. 34(6), pages 1809-1818.
    629. Evans, Kevin P., 2011. "Intraday jumps and US macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2511-2527, October.
    630. Aït-Sahalia, Yacine & Jacod, Jean & Li, Jia, 2012. "Testing for jumps in noisy high frequency data," Journal of Econometrics, Elsevier, vol. 168(2), pages 207-222.
    631. Ronald Gallant, A. & Tauchen, George, 2018. "Exact Bayesian moment based inference for the distribution of the small-time movements of an Itô semimartingale," Journal of Econometrics, Elsevier, vol. 205(1), pages 140-155.
    632. Feng Ma & Yu Wei & Wang Chen & Feng He, 2018. "Forecasting the volatility of crude oil futures using high-frequency data: further evidence," Empirical Economics, Springer, vol. 55(2), pages 653-678, September.
    633. Shahzad, Hassan & Duong, Huu Nhan & Kalev, Petko S. & Singh, Harminder, 2014. "Trading volume, realized volatility and jumps in the Australian stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 414-430.
    634. Aida Karmous & Heni Boubaker & Lotfi Belkacem, 2021. "Forecasting Volatility for an Optimal Portfolio with Stylized Facts Using Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 461-482, August.
    635. Nima Nonejad, 2013. "A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory," CREATES Research Papers 2013-24, Department of Economics and Business Economics, Aarhus University.
    636. Choi, Yongok & Jacewitz, Stefan & Park, Joon Y., 2016. "A reexamination of stock return predictability," Journal of Econometrics, Elsevier, vol. 192(1), pages 168-189.
    637. Xianfei Hui & Baiqing Sun & Indranil SenGupta & Yan Zhou & Hui Jiang, 2022. "Stochastic volatility modeling of high-frequency CSI 300 index and dynamic jump prediction driven by machine learning," Papers 2204.02891, arXiv.org, revised Jan 2023.
    638. Sun, Bianxia & Gao, Yang, 2020. "Market liquidity and macro announcement around intraday jumps: Evidence from Chinese stock index futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    639. Qiang Liu & Zhi Liu, 2022. "Estimating spot volatility under infinite variation jumps with dependent market microstructure noise," Papers 2205.15738, arXiv.org, revised Feb 2023.
    640. Qiao, Gaoxiu & Yang, Jiyu & Li, Weiping, 2020. "VIX forecasting based on GARCH-type model with observable dynamic jumps: A new perspective," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    641. Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020. "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 1-12.
    642. Hassan Zada & Arshad Hassan & Wing-Keung Wong, 2021. "Do Jumps Matter in Both Equity Market Returns and Integrated Volatility: A Comparison of Asian Developed and Emerging Markets," Economies, MDPI, vol. 9(2), pages 1-26, June.
    643. Hung, Jui-Cheng, 2015. "Evaluation of realized multi-power variations in minimum variance hedging," Economic Modelling, Elsevier, vol. 51(C), pages 672-679.
    644. Wright, Jonathan H. & Zhou, Hao, 2009. "Bond risk premia and realized jump risk," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2333-2345, December.
    645. Bregantini, Daniele, 2013. "Moment-based estimation of stochastic volatility," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4755-4764.
    646. Espinosa, Fernando & Vives, Josep, 2006. "A volatility-varying and jump-diffusion Merton type model of interest rate risk," Insurance: Mathematics and Economics, Elsevier, vol. 38(1), pages 157-166, February.
    647. Gnabo, Jean-Yves & Laurent, Sébastien & Lecourt, Christelle, 2009. "Does transparency in central bank intervention policy bring noise to the FX market?: The case of the Bank of Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 94-111, February.
    648. Da Fonseca, José & Ignatieva, Katja & Ziveyi, Jonathan, 2016. "Explaining credit default swap spreads by means of realized jumps and volatilities in the energy market," Energy Economics, Elsevier, vol. 56(C), pages 215-228.
    649. Buncic, Daniel & Gisler, Katja I.M., 2017. "The role of jumps and leverage in forecasting volatility in international equity markets," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 1-19.
    650. Todorov, Viktor, 2009. "Estimation of continuous-time stochastic volatility models with jumps using high-frequency data," Journal of Econometrics, Elsevier, vol. 148(2), pages 131-148, February.
    651. Dumitru, Ana-Maria & Hizmeri, Rodrigo & Izzeldin, Marwan, 2019. "Forecasting the Realized Variance in the Presence of Intraday Periodicity," EconStor Preprints 193631, ZBW - Leibniz Information Centre for Economics.
    652. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    653. Naeyoung Kang & Jungmu Kim, 2019. "An Empirical Analysis of Bitcoin Price Jump Risk," Sustainability, MDPI, vol. 11(7), pages 1-11, April.
    654. Jan Novotn?? & Jan Hanousek & Ev??en Ko??enda, 2013. "Price Jump Indicators: Stock Market Empirics During the Crisis," William Davidson Institute Working Papers Series wp1050, William Davidson Institute at the University of Michigan.
    655. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
    656. Shimizu, Yasutaka, 2009. "Functional estimation for Lvy measures of semimartingales with Poissonian jumps," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1073-1092, July.
    657. Flavia Barsotti & Simona Sanfelici, 2016. "Market Microstructure Effects on Firm Default Risk Evaluation," Econometrics, MDPI, vol. 4(3), pages 1-31, July.
    658. Liu, Guangqiang & Wei, Yu & Chen, Yongfei & Yu, Jiang & Hu, Yang, 2018. "Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 288-297.
    659. Todorova, Neda, 2015. "The course of realized volatility in the LME non-ferrous metal market," Economic Modelling, Elsevier, vol. 51(C), pages 1-12.
    660. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay & Villupuram, Sriram, 2014. "Currency jumps, cojumps and the role of macro news," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 42-62.
    661. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    662. Yang, Kun & Wei, Yu & Li, Shouwei & Liu, Liang & Wang, Lei, 2021. "Global financial uncertainties and China’s crude oil futures market: Evidence from interday and intraday price dynamics," Energy Economics, Elsevier, vol. 96(C).
    663. Behfar, Stefan Kambiz, 2016. "Long memory behavior of returns after intraday financial jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 716-725.
    664. Yingjie Dong & Yiu-Kuen Tse, 2017. "Business Time Sampling Scheme with Applications to Testing Semi-Martingale Hypothesis and Estimating Integrated Volatility," Econometrics, MDPI, vol. 5(4), pages 1-19, November.
    665. Giulia Livieri & Maria Elvira Mancino & Stefano Marmi, 2019. "Asymptotic results for the Fourier estimator of the integrated quarticity," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 471-502, December.
    666. McMillan, David G. & Speight, Alan E.H. & Evans, Kevin P., 2008. "How useful is intraday data for evaluating daily Value-at-Risk?: Evidence from three Euro rates," Journal of Multinational Financial Management, Elsevier, vol. 18(5), pages 488-503, December.
    667. Emawtee Bissoondoyal-Bheenick & Robert Brooks & Wei Chi & Hung Xuan Do, 2018. "Volatility spillover between the US, Chinese and Australian stock markets," Australian Journal of Management, Australian School of Business, vol. 43(2), pages 263-285, May.
    668. Daiki Maki & Yasushi Ota, 2020. "The impacts of asymmetry on modeling and forecasting realized volatility in Japanese stock markets," Papers 2006.00158, arXiv.org.
    669. Xu, Yahua & Bouri, Elie & Saeed, Tareq & Wen, Zhuzhu, 2020. "Intraday return predictability: Evidence from commodity ETFs and their related volatility indices," Resources Policy, Elsevier, vol. 69(C).
    670. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
    671. Lu, Botao & Ma, Feng & Wang, Jiqian & Ding, Hui & Wahab, M.I.M., 2021. "Harnessing the decomposed realized measures for volatility forecasting: Evidence from the US stock market," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 672-689.
    672. Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017. "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, vol. 67(C), pages 136-145.
    673. George Filis & Stavros Degiannakis & Zacharias Bragoudakis, 2022. "Forecasting macroeconomic indicators for Eurozone and Greece: How useful are the oil price assumptions?," Working Papers 296, Bank of Greece.
    674. Valenzuela, Marcela & Zer, Ilknur & Fryzlewicz, Piotr & Rheinlander, Thorsten, 2015. "Relative liquidity and future volatility," LSE Research Online Documents on Economics 62181, London School of Economics and Political Science, LSE Library.
    675. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    676. Kumar, Dilip, 2017. "Realized volatility transmission from crude oil to equity sectors: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 149-167.
    677. Ysusi Carla, 2006. "Estimating Integrated Volatility Using Absolute High-Frequency Returns," Working Papers 2006-13, Banco de México.
    678. Finbarr Murphy & Ehud Ronn, 2015. "The valuation and information content of options on crude-oil futures contracts," Review of Derivatives Research, Springer, vol. 18(2), pages 95-106, July.
    679. Wamg, Jianxin, 2011. "Forecasting Volatility in Asian Stock Markets: Contributions of Local, Regional, and Global Factors," Asian Development Review, Asian Development Bank, vol. 28(2), pages 32-57.
    680. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.

  26. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Nkwoma John Inekwe, 2016. "Financial uncertainty, risk aversion and monetary policy," Empirical Economics, Springer, vol. 51(3), pages 939-961, November.
    2. Almut Veraart & Luitgard Veraart, 2012. "Stochastic volatility and stochastic leverage," Annals of Finance, Springer, vol. 8(2), pages 205-233, May.
    3. Ivan Shaliastovich & George Tauchen, 2010. "Pricing of the Time-Change Risks," Working Papers 10-10, Duke University, Department of Economics.
    4. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    5. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    6. Nolte, Ingmar & Xu, Qi, 2015. "The economic value of volatility timing with realized jumps," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 45-59.
    7. Maciej Kostrzewski, 2014. "Bayesian DEJD model and detection of asymmetric jumps," Papers 1404.2050, arXiv.org.
    8. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford.
    9. Thierry Ane & Carole Metais, 2010. "Jump Distribution Characteristics: Evidence from European Stock Markets," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 9(1), pages 1-22, April.
    10. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    11. Maciej Kostrzewski & Jadwiga Kostrzewska, 2021. "The Impact of Forecasting Jumps on Forecasting Electricity Prices," Energies, MDPI, vol. 14(2), pages 1-17, January.
    12. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Multipower Variation for Brownian Semistationary Processes," CREATES Research Papers 2009-21, Department of Economics and Business Economics, Aarhus University.
    13. Kallsen Jan & Muhle-Karbe Johannes, 2011. "Method of moment estimation in time-changed Lévy models," Statistics & Risk Modeling, De Gruyter, vol. 28(2), pages 169-194, May.
    14. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    15. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    16. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2007. "Power variation for Gaussian processes with stationary increments," CREATES Research Papers 2007-42, Department of Economics and Business Economics, Aarhus University.
    17. Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.
    18. Tomáš Tichý, 2006. "Model Dependency of the Digital Option Replication – Replication under an Incomplete Model (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 56(7-8), pages 361-379, July.
    19. Ole E. Barndorff-Nielsen & Makoto Maejima & Ken-iti Sato, 2006. "Infinite Divisibility for Stochastic Processes and Time Change," Journal of Theoretical Probability, Springer, vol. 19(2), pages 411-446, June.
    20. Almut E. D. Veraart, 2008. "Impact of time–inhomogeneous jumps and leverage type effects on returns and realised variances," CREATES Research Papers 2008-57, Department of Economics and Business Economics, Aarhus University.
    21. Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.
    22. Kleiber, William, 2016. "High resolution simulation of nonstationary Gaussian random fields," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 277-288.
    23. Creal, Drew D., 2008. "Analysis of filtering and smoothing algorithms for Lévy-driven stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2863-2876, February.
    24. Neil Shephard & Torben G. Andersen, 2008. "Stochastic Volatility: Origins and Overview," OFRC Working Papers Series 2008fe23, Oxford Financial Research Centre.
    25. Stefan Klößner, 2010. "A high-low-based omnibus test for symmetry, the Lévy property, and other hypotheses on intraday returns," Finance and Stochastics, Springer, vol. 14(1), pages 1-12, January.
    26. Li, Wenlan & Cheng, Yuxiang & Fang, Qiang, 2020. "Forecast on silver futures linked with structural breaks and day-of-the-week effect," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    27. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic Volatility with Leverage: Fast Likelihood Inference," CIRJE F-Series CIRJE-F-297, CIRJE, Faculty of Economics, University of Tokyo.
    28. Todorov, Viktor, 2011. "Econometric analysis of jump-driven stochastic volatility models," Journal of Econometrics, Elsevier, vol. 160(1), pages 12-21, January.
    29. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
    30. Todorov, Viktor, 2009. "Estimation of continuous-time stochastic volatility models with jumps using high-frequency data," Journal of Econometrics, Elsevier, vol. 148(2), pages 131-148, February.
    31. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic Volatility with Leverage: Fast Likelihood Inference (Revised in April 2006, subsequently published in "Journal of Econometrics", 140, 425-449, 2007. )," CARF F-Series CARF-F-011, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

  27. Ole E. Barndorff-Nielsen & Svend Erik Graversen & Neil Shephard, 2003. "Power variation & stochastic volatility: a review and some new results," Economics Papers 2003-W19, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    2. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    3. John Cotter, 2011. "Absolute Return Volatility," Papers 1103.5976, arXiv.org.
    4. Andrey Rafalson, 2012. "Bootstrap inference about integrated volatility (in Russian)," Quantile, Quantile, issue 10, pages 91-108, December.
    5. Nikolai Dokuchaev, 2015. "On statistical indistinguishability of complete and incomplete discrete time market models," Papers 1505.00638, arXiv.org.

  28. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Power Variation and Time Change," Economics Papers 2002-W24, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    2. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    3. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2004. "Regular and Modified Kernel-Based Estimators of Integrated Variance: The Case with Independent Noise," OFRC Working Papers Series 2004fe20, Oxford Financial Research Centre.
    4. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    5. Herwartz, Helmut & Golosnoy, Vasyl, 2007. "Semiparametric Approaches to the Prediction of Conditional Correlation Matrices in Finance," Economics Working Papers 2007-23, Christian-Albrechts-University of Kiel, Department of Economics.
    6. Pawel Kliber, 2011. "Jumps Activity and Singularity Spectra for Instruments in the Polish Financial Market," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 171-184.

  29. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    2. MEDDAHI, Nour, 2002. "ARMA Representation of Integrated and Realized Variances," Cahiers de recherche 2002-20, Universite de Montreal, Departement de sciences economiques.
    3. Turgut Kısınbay, 2010. "Predictive ability of asymmetric volatility models at medium-term horizons," Applied Economics, Taylor & Francis Journals, vol. 42(30), pages 3813-3829.
    4. Anzarut, Michelle & Mena, Ramsés H., 2019. "A Harris process to model stochastic volatility," Econometrics and Statistics, Elsevier, vol. 10(C), pages 151-169.
    5. Ysusi Carla, 2006. "Estimating Integrated Volatility Using Absolute High-Frequency Returns," Working Papers 2006-13, Banco de México.

  30. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.

    Cited by:

    1. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    2. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    3. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    4. Nour Meddahi, 2002. "A theoretical comparison between integrated and realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 479-508.
    5. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    6. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," Cahiers de recherche 0948, CIRPEE.
    7. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    8. Ole Barndorff-Nielsen & Svend Erik Graversen & Jean Jacod & Mark Podolskij & Neil Shephard, 2004. "A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales," Economics Papers 2004-W29, Economics Group, Nuffield College, University of Oxford.
    9. Michael C. Münnix & Rudi Schäfer & Thomas Guhr, 2011. "Statistical Causes For The Epps Effect In Microstructure Noise," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(08), pages 1231-1246.
    10. Ole E. Barndorff-Nielsen & Neil Shephard & Matthias Winkel, 2005. "Limit theorems for multipower variation in the presence of jumps," OFRC Working Papers Series 2005fe06, Oxford Financial Research Centre.
    11. Christensen, Kim & Kinnebrock, Silja & Podolskij, Mark, 2010. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," Journal of Econometrics, Elsevier, vol. 159(1), pages 116-133, November.
    12. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Power Variation and Time Change," Economics Papers 2002-W24, Economics Group, Nuffield College, University of Oxford.
    13. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "A Feasible Central Limit Theory for Realised Volatility Under Leverage," Economics Papers 2004-W03, Economics Group, Nuffield College, University of Oxford.
    14. Neil Shephard, 2005. "Stochastic Volatility," Economics Papers 2005-W17, Economics Group, Nuffield College, University of Oxford.
    15. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    16. MEDDAHI, Nour, 2002. "ARMA Representation of Integrated and Realized Variances," Cahiers de recherche 2002-20, Universite de Montreal, Departement de sciences economiques.
    17. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    18. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.
    19. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Estimating quadratic variation using realised volatility," Economics Papers 2001-W20, Economics Group, Nuffield College, University of Oxford, revised 01 Nov 2001.
    20. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "How accurate is the asymptotic approximation to the distribution of realised volatility?," Economics Papers 2001-W16, Economics Group, Nuffield College, University of Oxford.
    21. Michael C. Munnix & Rudi Schafer & Thomas Guhr, 2009. "Compensating asynchrony effects in the calculation of financial correlations," Papers 0910.2909, arXiv.org, revised Jul 2010.
    22. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.
    23. Ole E. Barndorff-Nielsen & Svend Erik Graversen & Neil Shephard, 2003. "Power variation & stochastic volatility: a review and some new results," Economics Papers 2003-W19, Economics Group, Nuffield College, University of Oxford.
    24. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.

  31. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Integrated OU Processes," Economics Papers 2001-W1, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Wim Schoutens & Stijn Symens, 2003. "The Pricing Of Exotic Options By Monte–Carlo Simulations In A Lévy Market With Stochastic Volatility," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 6(08), pages 839-864.
    2. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Normal modified stable processes," Economics Papers 2001-W6, Economics Group, Nuffield College, University of Oxford.
    3. Griffin, J.E. & Steel, M.F.J., 2006. "Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility," Journal of Econometrics, Elsevier, vol. 134(2), pages 605-644, October.
    4. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Higher order variation and stochastic volatility models," Economics Papers 2001-W8, Economics Group, Nuffield College, University of Oxford.

  32. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Normal modified stable processes," Economics Papers 2001-W6, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Ole E. Barndorff-Nielsen & David G. Pollard & Neil Shephard, 2010. "Integer-valued Lévy processes and low latency financial econometrics," CREATES Research Papers 2010-66, Department of Economics and Business Economics, Aarhus University.
    2. Young Kim & Rosella Giacometti & Svetlozar Rachev & Frank Fabozzi & Domenico Mignacca, 2012. "Measuring financial risk and portfolio optimization with a non-Gaussian multivariate model," Annals of Operations Research, Springer, vol. 201(1), pages 325-343, December.
    3. Brix, Anne Floor & Lunde, Asger & Wei, Wei, 2018. "A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method," Energy Economics, Elsevier, vol. 72(C), pages 560-582.
    4. Young Shin Kim & Kum-Hwan Roh & Raphael Douady, 2020. "Tempered Stable Processes with Time Varying Exponential Tails," Papers 2006.07669, arXiv.org, revised Aug 2020.
    5. Young Shin Kim, 2018. "First Passage Time for Tempered Stable Process and Its Application to Perpetual American Option and Barrier Option Pricing," Papers 1801.09362, arXiv.org.
    6. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    7. Kim, Young Shin & Lee, Jaesung & Mittnik, Stefan & Park, Jiho, 2015. "Quanto option pricing in the presence of fat tails and asymmetric dependence," Journal of Econometrics, Elsevier, vol. 187(2), pages 512-520.
    8. Scott, David J & Würtz, Diethelm & Dong, Christine & Tran, Thanh Tam, 2009. "Moments of the generalized hyperbolic distribution," MPRA Paper 19081, University Library of Munich, Germany.
    9. Young Shin Kim, 2022. "Portfolio optimization and marginal contribution to risk on multivariate normal tempered stable model," Annals of Operations Research, Springer, vol. 312(2), pages 853-881, May.
    10. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2021. "Random variate generation for exponential and gamma tilted stable distributions," LSE Research Online Documents on Economics 108593, London School of Economics and Political Science, LSE Library.
    11. Young Shin Kim, 2019. "Tempered stable process, first passage time, and path-dependent option pricing," Computational Management Science, Springer, vol. 16(1), pages 187-215, February.
    12. Javier Mencía & Enrique Sentana, 2008. "Multivariate Location-Scale Mixtures of Normals and Mean-Variance-skewness Portfolio Allocation," Working Papers wp2008_0805, CEMFI.
    13. Hasan A. Fallahgoul & David Veredas & Frank J. Fabozzi, 2019. "Quantile-Based Inference for Tempered Stable Distributions," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 51-83, January.
    14. Tiantian Li & Young Shin Kim & Qi Fan & Fumin Zhu, 2021. "Aumann–Serrano index of risk in portfolio optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(2), pages 197-217, October.
    15. Jouchi Nakajima, 2017. "Bayesian analysis of multivariate stochastic volatility with skew return distribution," Econometric Reviews, Taylor & Francis Journals, vol. 36(5), pages 546-562, May.
    16. Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Anand, Abhinav & Li, Tiantian & Kurosaki, Tetsuo & Kim, Young Shin, 2016. "Foster–Hart optimal portfolios," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 117-130.
    18. Young Shin Kim & Hyangju Kim & Jaehyung Choi, 2023. "Deep Calibration With Artificial Neural Network: A Performance Comparison on Option Pricing Models," Papers 2303.08760, arXiv.org.
    19. Ole Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2002. "Some recent developments in stochastic volatility modelling," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 11-23.
    20. S. Z. Levendorskiǐ, 2004. "Pricing Of The American Put Under Lévy Processes," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(03), pages 303-335.
    21. Yuhao Liu & Petar M. Djurić & Young Shin Kim & Svetlozar T. Rachev & James Glimm, 2021. "Systemic Risk Modeling with Lévy Copulas," JRFM, MDPI, vol. 14(6), pages 1-20, June.
    22. Farouk Mselmi, 2022. "Generalized linear model for subordinated Lévy processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 772-801, June.
    23. Karen J. Palmer & Martin S. Ridout & Byron J. T. Morgan, 2008. "Modelling cell generation times by using the tempered stable distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(4), pages 379-397, September.
    24. Abhinav Anand & Tiantian Li & Tetsuo Kurosaki & Young Shin Kim, 2017. "The equity risk posed by the too-big-to-fail banks: a Foster–Hart estimation," Annals of Operations Research, Springer, vol. 253(1), pages 21-41, June.
    25. Gajda, J. & Kumar, A. & Wyłomańska, A., 2019. "Stable Lévy process delayed by tempered stable subordinator," Statistics & Probability Letters, Elsevier, vol. 145(C), pages 284-292.
    26. Roberto Baviera & Pietro Manzoni, 2024. "Fast and General Simulation of L\'evy-driven OU processes for Energy Derivatives," Papers 2401.15483, arXiv.org.
    27. Creal, Drew D., 2008. "Analysis of filtering and smoothing algorithms for Lévy-driven stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2863-2876, February.
    28. Matthias Fischer & Kevin Jakob, 2016. "pTAS distributions with application to risk management," Journal of Statistical Distributions and Applications, Springer, vol. 3(1), pages 1-18, December.
    29. Vijverberg, Chu-Ping C. & Vijverberg, Wim P.M. & Taşpınar, Süleyman, 2016. "Linking Tukey’s legacy to financial risk measurement," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 595-615.
    30. Todorov, Viktor & Tauchen, George & Grynkiv, Iaryna, 2011. "Realized Laplace transforms for estimation of jump diffusive volatility models," Journal of Econometrics, Elsevier, vol. 164(2), pages 367-381, October.
    31. Young Shin Kim, 2020. "Portfolio Optimization on the Dispersion Risk and the Asymmetric Tail Risk," Papers 2007.13972, arXiv.org, revised Sep 2020.
    32. Shin Kim, Young & Rachev, Svetlozar T. & Leonardo Bianchi, Michele & Fabozzi, Frank J., 2010. "Tempered stable and tempered infinitely divisible GARCH models," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2096-2109, September.
    33. Holger Fink & Stefan Mittnik, 2021. "Quanto Pricing beyond Black–Scholes," JRFM, MDPI, vol. 14(3), pages 1-27, March.
    34. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. H. Fink & S. Geissel & J. Sass & F. T. Seifried, 2019. "Implied risk aversion: an alternative rating system for retail structured products," Review of Derivatives Research, Springer, vol. 22(3), pages 357-387, October.
    36. Hasan Fallahgoul & Gregoire Loeper, 2021. "Modelling tail risk with tempered stable distributions: an overview," Annals of Operations Research, Springer, vol. 299(1), pages 1253-1280, April.
    37. Christophe Andrieu & Arnaud Doucet & Roman Holenstein, 2010. "Particle Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 269-342, June.
    38. Sung Ik Kim & Young Shin Kim, 2018. "Tempered stable structural model in pricing credit spread and credit default swap," Review of Derivatives Research, Springer, vol. 21(1), pages 119-148, April.
    39. Cerquetti, Annalisa, 2007. "A note on Bayesian nonparametric priors derived from exponentially tilted Poisson-Kingman models," Statistics & Probability Letters, Elsevier, vol. 77(18), pages 1705-1711, December.
    40. Young Shin Kim, 2023. "Portfolio Optimization with Relative Tail Risk," Papers 2303.12209, arXiv.org, revised Mar 2023.

  33. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Realised power variation and stochastic volatility models," Economics Papers 2001-W18, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Woerner Jeannette H. C., 2003. "Variational sums and power variation: a unifying approach to model selection and estimation in semimartingale models," Statistics & Risk Modeling, De Gruyter, vol. 21(1/2003), pages 47-68, January.
    2. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    3. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    4. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    5. Nour Meddahi, 2002. "A theoretical comparison between integrated and realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 479-508.
    6. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    7. Nour Meddahi, 2001. "A Theoretical Comparison Between Integrated and Realized Volatilities," CIRANO Working Papers 2001s-71, CIRANO.
    8. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    9. Benjamin Yibin Zhang & Hao Zhou & Haibin Zhu, 2009. "Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5099-5131, December.
    10. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    11. Neil Shephard & Ole E. Barndorff-Nielsen & University of Aarhus, 2001. "Econometric Analysis of Realised Volatility and Its Use in Estimating Stochastic Volatility Models," Economics Series Working Papers 71, University of Oxford, Department of Economics.
    12. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Power Variation and Time Change," Economics Papers 2002-W24, Economics Group, Nuffield College, University of Oxford.
    13. MEDDAHI, Nour, 2002. "ARMA Representation of Integrated and Realized Variances," Cahiers de recherche 2002-20, Universite de Montreal, Departement de sciences economiques.
    14. Ole Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2002. "Some recent developments in stochastic volatility modelling," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 11-23.
    15. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    16. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO.
    17. Sam Howison & Avraam Rafailidis & Henrik Rasmussen, 2004. "On the pricing and hedging of volatility derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 11(4), pages 317-346.
    18. Ole E. Barndorff-Nielsen & Svend Erik Graversen & Neil Shephard, 2003. "Power variation & stochastic volatility: a review and some new results," Economics Papers 2003-W19, Economics Group, Nuffield College, University of Oxford.
    19. Elena Andreou & Eric Ghysels, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," CIRANO Working Papers 2004s-25, CIRANO.
    20. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.

  34. Ole E. Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2001. "Some recent developments in stochastic volatility modelling," Economics Papers 2001-W25, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Ioannis Kyriakou & Panos K. Pouliasis & Nikos C. Papapostolou, 2016. "Jumps and stochastic volatility in crude oil prices and advances in average option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1859-1873, December.
    2. Liang Wang & Weixuan Xia, 2022. "Power‐type derivatives for rough volatility with jumps," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1369-1406, July.
    3. Nour Meddahi, 2002. "A theoretical comparison between integrated and realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 479-508.
    4. Kumar, A. & Wyłomańska, A. & Połoczański, R. & Sundar, S., 2017. "Fractional Brownian motion time-changed by gamma and inverse gamma process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 648-667.
    5. Alexander Bade & Gabriel Frahm & Uwe Jaekel, 2009. "A general approach to Bayesian portfolio optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 70(2), pages 337-356, October.
    6. Dassios, Angelos & Qu, Yan & Zhao, Hongbiao, 2018. "Exact simulation for a class of tempered stable," LSE Research Online Documents on Economics 86981, London School of Economics and Political Science, LSE Library.
    7. Degiannakis, Stavros & Livada, Alexandra & Panas, Epaminondas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," MPRA Paper 80464, University Library of Munich, Germany.
    8. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Power Variation and Time Change," Economics Papers 2002-W24, Economics Group, Nuffield College, University of Oxford.
    9. Wang, XiaoTian & Yang, ZiJian & Cao, PiYao & Wang, ShiLin, 2021. "The closed-form option pricing formulas under the sub-fractional Poisson volatility models," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    10. Friedrich Hubalek & Martin Keller-Ressel & Carlo Sgarra, 2014. "Geometric Asian Option Pricing in General Affine Stochastic Volatility Models with Jumps," Papers 1407.2514, arXiv.org.
    11. Hautsch, Nikolaus & Scheuch, Christoph & Voigt, Stefan, 2018. "Limits to arbitrage in markets with stochastic settlement latency," CFS Working Paper Series 616, Center for Financial Studies (CFS).
    12. Fasen, Vicky, 2013. "Statistical estimation of multivariate Ornstein–Uhlenbeck processes and applications to co-integration," Journal of Econometrics, Elsevier, vol. 172(2), pages 325-337.
    13. MEDDAHI, Nour, 2002. "ARMA Representation of Integrated and Realized Variances," Cahiers de recherche 2002-20, Universite de Montreal, Departement de sciences economiques.
    14. Gong, Xiao-li & Zhuang, Xin-tian, 2016. "Option pricing and hedging for optimized Lévy driven stochastic volatility models," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 118-127.
    15. Lim, Kian Guan & Chen, Ying & Yap, Nelson K.L., 2019. "Intraday information from S&P 500 Index futures options," Journal of Financial Markets, Elsevier, vol. 42(C), pages 29-55.
    16. Tomáš Tichý, 2006. "Model Dependency of the Digital Option Replication – Replication under an Incomplete Model (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 56(7-8), pages 361-379, July.
    17. Griffin, J.E. & Steel, M.F.J., 2006. "Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility," Journal of Econometrics, Elsevier, vol. 134(2), pages 605-644, October.
    18. Ole E. Barndorff-Nielsen & Makoto Maejima & Ken-iti Sato, 2006. "Infinite Divisibility for Stochastic Processes and Time Change," Journal of Theoretical Probability, Springer, vol. 19(2), pages 411-446, June.
    19. Masuda, H. & Yoshida, N., 2005. "Asymptotic expansion for Barndorff-Nielsen and Shephard's stochastic volatility model," Stochastic Processes and their Applications, Elsevier, vol. 115(7), pages 1167-1186, July.
    20. Shu Ling Chiang & Ming Shann Tsai, 2019. "Valuation of an option using non-parametric methods," Review of Derivatives Research, Springer, vol. 22(3), pages 419-447, October.
    21. Farshid Mehrdoust & Idin Noorani, 2023. "Valuation of Spark-Spread Option Written on Electricity and Gas Forward Contracts Under Two-Factor Models with Non-Gaussian Lévy Processes," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 807-853, February.
    22. S. T. Tse & Justin W. L. Wan, 2013. "Low-bias simulation scheme for the Heston model by Inverse Gaussian approximation," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 919-937, May.
    23. Friedrich Hubalek & Petra Posedel, 2008. "Asymptotic analysis for a simple explicit estimator in Barndorff-Nielsen and Shephard stochastic volatility models," Papers 0807.3479, arXiv.org.
    24. Di Nunno, Giulia & Sjursen, Steffen, 2014. "BSDEs driven by time-changed Lévy noises and optimal control," Stochastic Processes and their Applications, Elsevier, vol. 124(4), pages 1679-1709.
    25. Carmen Broto & Esther Ruiz, 2004. "Estimation methods for stochastic volatility models: a survey," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
    26. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(4), pages 445-463, October.
    27. Riccardo Brignone & Carlo Sgarra, 2020. "Asian options pricing in Hawkes-type jump-diffusion models," Annals of Finance, Springer, vol. 16(1), pages 101-119, March.
    28. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2023. "Shot-noise cojumps: exact simulation and option pricing," LSE Research Online Documents on Economics 111537, London School of Economics and Political Science, LSE Library.
    29. Anusha Chari & Felipe Garcés & Juan Francisco Martínez & Patricio Valenzuela, 2022. "Sovereign Credit Spreads, Banking Fragility, and Global Factors," Working Papers Central Bank of Chile 957, Central Bank of Chile.
    30. Sergei Levendorskii, 2002. "Pseudo-diffusions and Quadratic term structure models," Papers cond-mat/0212249, arXiv.org, revised Apr 2004.
    31. Himadri Ghosh & Bishal Gurung & Prajneshu, 2015. "Kalman filter-based modelling and forecasting of stochastic volatility with threshold," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 492-507, March.
    32. Anatoliy Swishchuk, 2013. "Modeling and Pricing of Swaps for Financial and Energy Markets with Stochastic Volatilities," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8660, December.
    33. Nikolaus Hautsch & Christoph Scheuch & Stefan Voigt, 2018. "Building Trust Takes Time: Limits to Arbitrage for Blockchain-Based Assets," Papers 1812.00595, arXiv.org, revised Oct 2023.
    34. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    35. Yanhui Mi, 2016. "A modified stochastic volatility model based on Gamma Ornstein–Uhlenbeck process and option pricing," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 1-16, June.
    36. Corsaro, Stefania & Kyriakou, Ioannis & Marazzina, Daniele & Marino, Zelda, 2019. "A general framework for pricing Asian options under stochastic volatility on parallel architectures," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1082-1095.

  35. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "How accurate is the asymptotic approximation to the distribution of realised volatility?," Economics Papers 2001-W16, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    2. Dimitrios Thomakos & Michail Koubouros, 2008. "The Role of Realized Volatility in the Athens Stock Exchange," Working Papers 0020, University of Peloponnese, Department of Economics.
    3. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    4. Lars Forsberg & Tim Bollerslev, 2002. "Bridging the gap between the distribution of realized (ECU) volatility and ARCH modelling (of the Euro): the GARCH-NIG model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 535-548.
    5. Helmut Herwartz, 2006. "Econometric analysis of high frequency data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 89-104, March.
    6. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    7. ANDERSEN, Torben G. & BOLLERSLEV, Tim & MEDDAHI, Nour, 2002. "Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," Cahiers de recherche 2002-21, Universite de Montreal, Departement de sciences economiques.
    8. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    9. Dimitrios D. Thomakos & Michail S. Koubouros, 2005. "Realized Volatility and Asymmetries in the A.S.E. Returns," Finance 0507012, University Library of Munich, Germany, revised 17 Jan 2006.
    10. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    11. Neil Shephard & Ole E. Barndorff-Nielsen & University of Aarhus, 2001. "Econometric Analysis of Realised Volatility and Its Use in Estimating Stochastic Volatility Models," Economics Series Working Papers 71, University of Oxford, Department of Economics.
    12. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "A Feasible Central Limit Theory for Realised Volatility Under Leverage," Economics Papers 2004-W03, Economics Group, Nuffield College, University of Oxford.
    13. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," NBER Technical Working Papers 0279, National Bureau of Economic Research, Inc.
    14. Ole Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2002. "Some recent developments in stochastic volatility modelling," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 11-23.
    15. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Estimating quadratic variation using realised volatility," Economics Papers 2001-W20, Economics Group, Nuffield College, University of Oxford, revised 01 Nov 2001.
    16. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO.
    17. Jeffrey R. Russell & Federico M. Bandi, 2004. "Microstructure noise, realized volatility, and optimal sampling," Econometric Society 2004 Latin American Meetings 220, Econometric Society.
    18. Peter C.B. Phillips & Jun Yu, 2007. "Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance," Cowles Foundation Discussion Papers 1597, Cowles Foundation for Research in Economics, Yale University.
    19. Damien Lynch & Nikolaos Panigirtzoglou, 2004. "Option Implied and Realised Measures of Variance," Money Macro and Finance (MMF) Research Group Conference 2004 94, Money Macro and Finance Research Group.
    20. Elena Andreou & Eric Ghysels, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," CIRANO Working Papers 2004s-25, CIRANO.
    21. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    22. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Realised power variation and stochastic volatility models," Economics Papers 2001-W18, Economics Group, Nuffield College, University of Oxford.
    23. Peter C.B. Phillips & Jun Yu, 2005. "A Two-Stage Realized Volatility Approach to the Estimation for Diffusion Processes from Discrete Observations," Cowles Foundation Discussion Papers 1523, Cowles Foundation for Research in Economics, Yale University.

  36. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Estimating quadratic variation using realised volatility," Economics Papers 2001-W20, Economics Group, Nuffield College, University of Oxford, revised 01 Nov 2001.

    Cited by:

    1. MEDDAHI, Nour, 2001. "A Theoretical Comparison Between Integrated and Realized Volatilies," Cahiers de recherche 2001-26, Universite de Montreal, Departement de sciences economiques.
    2. Peter Reinhard Hansen & Asger Lunde & James M. Nason, 2003. "Choosing the best volatility models: the model confidence set approach," FRB Atlanta Working Paper 2003-28, Federal Reserve Bank of Atlanta.

  37. Ole Barndorff-Nielsen & Neil Shephard, 2000. "Non-Gaussian OU based models and some of their uses in financial economics," OFRC Working Papers Series 2000mf01, Oxford Financial Research Centre.

    Cited by:

    1. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July.
    2. Ali Alami & Eric Renault, 2001. "Risque de modèle de volatilité," CIRANO Working Papers 2001s-06, CIRANO.
    3. Christian Bontemps & Nour Meddahi, 2002. "Testing Normality: A GMM Approach," CIRANO Working Papers 2002s-63, CIRANO.
    4. MEDDAHI, Nour, 2001. "An Eigenfunction Approach for Volatility Modeling," Cahiers de recherche 2001-29, Universite de Montreal, Departement de sciences economiques.
    5. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Economics Working Papers ECO2006/3, European University Institute.
    6. Nour Meddahi, 2000. "Temporal Aggregation of Volatility Models," Econometric Society World Congress 2000 Contributed Papers 1903, Econometric Society.
    7. Catherine Doz & Eric Renault, 2004. "Conditionaly Heteroskedastic Factor Models : Identificationand Instrumental variables Estmation," THEMA Working Papers 2004-13, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    8. Zhong, Guang-Yan & Li, Jiang-Cheng & Jiang, George J. & Li, Hai-Feng & Tao, Hui-Ming, 2018. "The time delay restraining the herd behavior with Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 335-346.
    9. Marina Resta & Davide Sciutti, "undated". "A characterization of self-affine processes in finance through the scaling function," Modeling, Computing, and Mastering Complexity 2003 13, Society for Computational Economics.
    10. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Higher order variation and stochastic volatility models," Economics Papers 2001-W8, Economics Group, Nuffield College, University of Oxford.
    11. P. Brockwell, 2001. "Lévy-Driven Carma Processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 113-124, March.

  38. Ole E. Barndorff-Nielsen & Neil Shephard, 2000. "Econometric analysis of realised volatility and its use in estimating stochastic volatility models," Economics Papers 2001-W4, Economics Group, Nuffield College, University of Oxford, revised 05 Jul 2001.

    Cited by:

    1. Eric Hillebrand & Gunther Schnabl & Yasemin Ulu, 2006. "Japanese Foreign Exchange Intervention and the Yen/Dollar Exchange Rate: A Simultaneous Equations Approach Using Realized Volatility," CESifo Working Paper Series 1766, CESifo.
    2. Jieun Lee & Doojin Ryu, 2019. "The impacts of public news announcements on intraday implied volatility dynamics," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(6), pages 656-685, June.
    3. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    4. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    5. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    6. Brian Sing Fan Chan & Andy Cheuk Hin Cheng & Alfred Ka Chun Ma, 2018. "Stock Market Volatility and Trading Volume: A Special Case in Hong Kong With Stock Connect Turnover," JRFM, MDPI, vol. 11(4), pages 1-17, October.
    7. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
    8. Cavit Pakel & Neil Shephard & Kevin Sheppard, 2009. "Nuisance parameters, composite likelihoods and a panel of GARCH models," OFRC Working Papers Series 2009fe03, Oxford Financial Research Centre.
    9. Yuta Koike, 2013. "Limit Theorems for the Pre-averaged Hayashi-Yoshida Estimator with Random Sampling," Global COE Hi-Stat Discussion Paper Series gd12-276, Institute of Economic Research, Hitotsubashi University.
    10. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    11. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
    12. Anisha Ghosh & Oliver Linton, 2019. "Estimation with Mixed Data Frequencies: A Bias-Correction Approach," CeMMAP working papers CWP65/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Tihana Škrinjarić, 2019. "Time Varying Spillovers between the Online Search Volume and Stock Returns: Case of CESEE Markets," IJFS, MDPI, vol. 7(4), pages 1-30, October.
    14. Beyer, Deborah B. & Fan, Zaifeng S., 2023. "The calming effects of conflict: The impact of partisan conflict on market volatility," International Review of Financial Analysis, Elsevier, vol. 85(C).
    15. Dette, Holger & Golosnoy, Vasyl & Kellermann, Janosch, 2022. "Correcting Intraday Periodicity Bias in Realized Volatility Measures," Econometrics and Statistics, Elsevier, vol. 23(C), pages 36-52.
    16. Hung Do & Rabindra Nepal & Tooraj Jamasb, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," CAMA Working Papers 2020-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
    18. Ole E. Barndorff-Nielsen & David G. Pollard & Neil Shephard, 2010. "Integer-valued Lévy processes and low latency financial econometrics," CREATES Research Papers 2010-66, Department of Economics and Business Economics, Aarhus University.
    19. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    20. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    21. Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
    22. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    23. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    24. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    25. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    26. Christian Wolff & Thorsten Lehnert & Yuehao Lin, 2014. "Skewness Risk Premium: Theory and Empirical Evidence," LSF Research Working Paper Series 14-05, Luxembourg School of Finance, University of Luxembourg.
    27. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," KIER Working Papers 840, Kyoto University, Institute of Economic Research.
    28. Sankar, Ganesh & Ramachandran, Shankar & Lukose P J, Jijo, 2020. "Dynamics of variance risk premium: Evidence from India," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 321-334.
    29. Degiannakis, Stavros & Filis, George & Kizys, Renatas, 2014. "The effects of oil price shocks on stock market volatility: Evidence from European data," MPRA Paper 96296, University Library of Munich, Germany.
    30. Katerina Papagiannouli, 2022. "A Lepskiĭ-type stopping rule for the covariance estimation of multi-dimensional Lévy processes," Statistical Inference for Stochastic Processes, Springer, vol. 25(3), pages 505-535, October.
    31. Vit Bubak, 2010. "Forecasting the Quantiles of Daily Equity Returns Using Realized Volatility: Evidence from the Czech Stock Market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00650666, HAL.
    32. Alessandro Rossi & Giampiero M. Gallo, 2002. "Volatility Estimation via Hidden Markov Models," Econometrics Working Papers Archive wp2002_14, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    33. Silja Kinnebrock & Mark Podolskij, 2008. "An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models," CREATES Research Papers 2008-23, Department of Economics and Business Economics, Aarhus University.
    34. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
    35. Nicholas Apergis & Christina Christou & Stephen M. Miller, 2011. "Country and Industry Convergence of Equity Markets: International Evidence from Club Convergence and Clustering," Working Papers 1105, University of Nevada, Las Vegas , Department of Economics.
    36. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    37. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    38. Peter Christoffersen & Bruno Feunou & Yoontae Jeon, 2014. "Option Valuation with Observable Volatility and Jump Dynamics," CREATES Research Papers 2015-07, Department of Economics and Business Economics, Aarhus University.
    39. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    40. Koike, Yuta, 2014. "Limit theorems for the pre-averaged Hayashi–Yoshida estimator with random sampling," Stochastic Processes and their Applications, Elsevier, vol. 124(8), pages 2699-2753.
    41. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2017. "On the gains of using high frequency data and higher moments in Portfolio Selection," CeBER Working Papers 2017-02, Centre for Business and Economics Research (CeBER), University of Coimbra.
    42. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    43. Yu-Hua Zeng & Shou-Lei Wang & Yu-Fei Yang, 2014. "Calibration of the Volatility in Option Pricing Using the Total Variation Regularization," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-9, March.
    44. Basel M. A. Awartani, 2008. "Forecasting volatility with noisy jumps: an application to the Dow Jones Industrial Average stocks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 267-278.
    45. Kalnina, Ilze & Linton, Oliver, 2007. "Inference about realized volatility using infill subsampling," LSE Research Online Documents on Economics 4411, London School of Economics and Political Science, LSE Library.
    46. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    47. Eric Hillebrand & Marcelo Cunha Medeiros, 2007. "Forecasting realized volatility models:the benefits of bagging and nonlinear specifications," Textos para discussão 547, Department of Economics PUC-Rio (Brazil).
    48. Massimiliano Caporin & Gabriel G. Velo, 2011. "Modeling and forecasting realized range volatility," "Marco Fanno" Working Papers 0128, Dipartimento di Scienze Economiche "Marco Fanno".
    49. Cassola, Nuno & Morana, Claudio, 2010. "Comovements in volatility in the euro money market," Journal of International Money and Finance, Elsevier, vol. 29(3), pages 525-539, April.
    50. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    51. Podolskij, Mark & Vetter, Mathias, 2008. "Bipower-type estimation in a noisy diffusion setting," Technical Reports 2008,24, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    52. Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    53. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    54. Jozef Baruník & Evžen Kocenda & Lukáš Vácha, 2015. "Asymmetric Connectedness on the U.S. Stock Market: Bad and Good Volatility Spillover," CESifo Working Paper Series 5305, CESifo.
    55. Kanaya, Shin, 2016. "Convergence rates of sums of α-mixing triangular arrays : with an application to non-parametric drift function estimation of continuous-time processes," Discussion Paper Series 646, Institute of Economic Research, Hitotsubashi University.
    56. Elder, John & Miao, Hong & Ramchander, Sanjay, 2012. "Impact of macroeconomic news on metal futures," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 51-65.
    57. Kim Christensen & Charlotte Christiansen & Anders M. Posselt, 2019. "The Economic Value of VIX ETPs," CREATES Research Papers 2019-14, Department of Economics and Business Economics, Aarhus University.
    58. Richard Y. Chen & Per A. Mykland, 2015. "Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data," Papers 1512.06159, arXiv.org, revised Oct 2018.
    59. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "High-Frequency Jump Tests: Which Test Should We Use?," Papers 1708.09520, arXiv.org, revised Jan 2020.
    60. Turan Bali, 2007. "Modeling the dynamics of interest rate volatility with skewed fat-tailed distributions," Annals of Operations Research, Springer, vol. 151(1), pages 151-178, April.
    61. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
    62. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2015. "Volatility transmission in global financial markets," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 3-18.
    63. Antonio Naimoli & Giuseppe Storti, 2021. "Forecasting Volatility and Tail Risk in Electricity Markets," JRFM, MDPI, vol. 14(7), pages 1-17, June.
    64. Peter C. B. Phillips & Jun Yu, 2009. "Information Loss in Volatility Measurement with Flat Price Trading," Global COE Hi-Stat Discussion Paper Series gd08-039, Institute of Economic Research, Hitotsubashi University.
    65. Wang, Fangfang, 2014. "Optimal design of Fourier estimator in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 708-722.
    66. Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2021. "Dynamic return and volatility spillovers among S&P 500, crude oil, and gold," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 153-170, January.
    67. Park, Sujin & Linton, Oliver, 2012. "Estimating the quadratic covariation matrix for an asynchronously observed continuous time signal masked by additive noise," LSE Research Online Documents on Economics 119050, London School of Economics and Political Science, LSE Library.
    68. Michel Beine & Jerome Lahaye & Sebastien Laurent & Christopher J. Neely & Franz C. Palm, 2007. "Central bank intervention and exchange rate volatility, its continuous and jump components," Working Papers 2006-031, Federal Reserve Bank of St. Louis.
    69. McMahon, Michael & Ahrens, Maximilian & Erdemlioglu, Deniz & Neely, Christopher J & Yang, Xiye, 2023. "Mind Your Language: Market Responses to Central Bank Speeches," CEPR Discussion Papers 18191, C.E.P.R. Discussion Papers.
    70. Yingying Li & Per A. Mykland, 2007. "Are volatility estimators robust with respect to modeling assumptions?," Papers 0709.0440, arXiv.org.
    71. Peter R. Hansen & Asger Lunde & Valeri Voev, 2010. "Realized Beta GARCH: A Multivariate GARCH Model with Realized Measures of Volatility and CoVolatility," CREATES Research Papers 2010-74, Department of Economics and Business Economics, Aarhus University.
    72. Almut Veraart & Luitgard Veraart, 2012. "Stochastic volatility and stochastic leverage," Annals of Finance, Springer, vol. 8(2), pages 205-233, May.
    73. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
    74. Alexander Schnurr, 2015. "An Ordinal Pattern Approach to Detect and to Model Leverage Effects and Dependence Structures Between Financial Time Series," Papers 1502.07321, arXiv.org.
    75. Peter Reinhard Hansen & Asger Lunde, 2005. "A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 525-554.
    76. Almut E. D. Veraart & Luitgard A. M. Veraart, 2013. "Risk premia in energy markets," CREATES Research Papers 2013-02, Department of Economics and Business Economics, Aarhus University.
    77. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    78. Geon Ho Choe & Kyungsub Lee, 2013. "High moment variations and their application," Papers 1311.4973, arXiv.org.
    79. Maria Elvira Mancino & Simona Sanfelici, 2011. "Estimation of Quarticity with High Frequency Data," Working Papers - Mathematical Economics 2011-06, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, revised Jan 2012.
    80. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    81. Bucci, Andrea, 2019. "Realized Volatility Forecasting with Neural Networks," MPRA Paper 95443, University Library of Munich, Germany.
    82. Jiayuan Zhou & Feiyu Jiang & Ke Zhu & Wai Keung Li, 2019. "Time series models for realized covariance matrices based on the matrix-F distribution," Papers 1903.12077, arXiv.org, revised Jul 2020.
    83. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
    84. Vetter, Mathias, 2010. "Limit theorems for bipower variation of semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 120(1), pages 22-38, January.
    85. Ghysels, Eric & Sinko, Arthur, 2011. "Volatility forecasting and microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 257-271, January.
    86. Fleming, Jeff & Paye, Bradley S., 2011. "High-frequency returns, jumps and the mixture of normals hypothesis," Journal of Econometrics, Elsevier, vol. 160(1), pages 119-128, January.
    87. Abel Rodriguez & Henryk Gzyl & German Molina & Enrique ter Horst, 2009. "Stochastic Volatility Models Including Open, Close, High and Low Prices," Papers 0901.1315, arXiv.org.
    88. Carl Lindberg, 2008. "The estimation of the Barndorff‐Nielsen and Shephard model from daily data based on measures of trading intensity," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(4), pages 277-289, July.
    89. Oliver Linton & Dajing Shang & Yang Yan, 2012. "Efficient estimation of conditional risk measures in a semiparametric GARCH model," CeMMAP working papers 25/12, Institute for Fiscal Studies.
    90. Jianqing Fan & Fang Han & Han Liu & Byron Vickers, 2015. "Robust Inference of Risks of Large Portfolios," Papers 1501.02382, arXiv.org.
    91. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    92. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Tinbergen Institute Discussion Papers 14-037/III, Tinbergen Institute.
    93. Renault, Eric & Werker, Bas J.M., 2011. "Causality effects in return volatility measures with random times," Journal of Econometrics, Elsevier, vol. 160(1), pages 272-279, January.
    94. Ozcan Ceylan, 2015. "Limited information-processing capacity and asymmetric stock correlations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1031-1039, June.
    95. Yu, Jun, 2012. "A semiparametric stochastic volatility model," Journal of Econometrics, Elsevier, vol. 167(2), pages 473-482.
    96. Peter Reinhard Hansen & Zhuo Huang, 2012. "Exponential GARCH Modeling with Realized Measures of Volatility," CREATES Research Papers 2012-44, Department of Economics and Business Economics, Aarhus University.
    97. Andersen, Torben G. & Bollerslev, Tim & Meddahi, Nour, 2011. "Realized volatility forecasting and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 220-234, January.
    98. Jeremy Large, 2007. "Estimating Quadratic Variation When Quoted Prices Change by a Constant Increment," Economics Series Working Papers 340, University of Oxford, Department of Economics.
    99. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2012. "Parametric Inference and Dynamic State Recovery from Option Panels," Global COE Hi-Stat Discussion Paper Series gd12-266, Institute of Economic Research, Hitotsubashi University.
    100. MEDDAHI, Nour, 2001. "A Theoretical Comparison Between Integrated and Realized Volatilies," Cahiers de recherche 2001-26, Universite de Montreal, Departement de sciences economiques.
    101. Tae-Hwy Lee & Huiyu Huang, 2014. "Forecasting Value-at-Risk Using High Frequency Information," Working Papers 201409, University of California at Riverside, Department of Economics.
    102. Müller, Hans-Georg & Sen, Rituparna & Stadtmüller, Ulrich, 2011. "Functional data analysis for volatility," Journal of Econometrics, Elsevier, vol. 165(2), pages 233-245.
    103. Diebold, Francis X. & Strasser, Georg H., 2008. "On the correlation structure of microstructure noise in theory and practice," CFS Working Paper Series 2008/32, Center for Financial Studies (CFS).
    104. Tae-Hwy Lee & Huiyu Huang, 2014. "Forecasting Realized Volatility Using Subsample Averaging," Working Papers 201410, University of California at Riverside, Department of Economics.
    105. Turan G. Bali & Hao Zhou, 2013. "Risk, Uncertainty, and Expected Returns," Koç University-TUSIAD Economic Research Forum Working Papers 1306, Koc University-TUSIAD Economic Research Forum.
    106. Sébastien Laurent & Shuping Shi, 2018. "Volatility Estimation and Jump Detection for drift-diffusion Processes," Working Papers halshs-01944449, HAL.
    107. Helmut Herwartz, 2006. "Econometric analysis of high frequency data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 89-104, March.
    108. Tankov, Peter & Voltchkova, Ekaterina, 2009. "Asymptotic analysis of hedging errors in models with jumps," Stochastic Processes and their Applications, Elsevier, vol. 119(6), pages 2004-2027, June.
    109. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    110. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    111. He, Lidan & Liu, Qiang & Liu, Zhi, 2020. "Edgeworth corrections for spot volatility estimator," Statistics & Probability Letters, Elsevier, vol. 164(C).
    112. Yang-Ho Park, 2013. "Volatility of volatility and tail risk premiums," Finance and Economics Discussion Series 2013-54, Board of Governors of the Federal Reserve System (U.S.).
    113. Ben Ammar, Imen & Hellara, Slaheddine, 2022. "High-frequency trading, stock volatility, and intraday crashes," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 337-344.
    114. Carol Alexander & Emese Lazar, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336, April.
    115. Zhenxiong Li & Marwan Izzeldin & Xingzhi Yao, 2020. "Return predictability of variance differences: A fractionally cointegrated approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1072-1089, July.
    116. Peter C. B. Phillips & Jun Yu, 2005. "Comments on “A selective overview of nonparametric methods in financial econometricsâ€Â," Finance Working Papers 22469, East Asian Bureau of Economic Research.
    117. Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
    118. Nicole Abruzzo & Yang-Ho Park, 2014. "An Empirical Analysis of Futures Margin Changes: Determinants and Policy Implications," Finance and Economics Discussion Series 2014-86, Board of Governors of the Federal Reserve System (U.S.).
    119. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    120. Maria Elvira Mancino & Simone Scotti & Giacomo Toscano, 2020. "Is the variance swap rate affine in the spot variance? Evidence from S&P500 data," Papers 2004.04015, arXiv.org.
    121. Tao, Yubo & Phillips, Peter C.B. & Yu, Jun, 2019. "Random coefficient continuous systems: Testing for extreme sample path behavior," Journal of Econometrics, Elsevier, vol. 209(2), pages 208-237.
    122. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    123. Maghyereh, Aktham & Awartani, Basel & Virk, Nader S., 2022. "Asymmetric risk transmissions between oil, gold and US equities: Recent evidence from the realized variance of the futures prices," Resources Policy, Elsevier, vol. 79(C).
    124. Bekierman Jeremias & Gribisch Bastian, 2016. "Estimating stochastic volatility models using realized measures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 279-300, June.
    125. Köchling, Gerrit & Schmidtke, Philipp & Posch, Peter N., 2020. "Volatility forecasting accuracy for Bitcoin," Economics Letters, Elsevier, vol. 191(C).
    126. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2013. "A nonparametric test of a strong leverage hypothesis," CeMMAP working papers 28/13, Institute for Fiscal Studies.
    127. George M. Constantinides & Anisha Ghosh, 2008. "Asset Pricing Tests with Long Run Risks in Consumption Growth," NBER Working Papers 14543, National Bureau of Economic Research, Inc.
    128. Ulrich Hounyo & Silvia Gonçalves & Nour Meddahi, 2016. "Bootstrapping pre-averaged realized volatility under market microstructure noise," CIRANO Working Papers 2016s-25, CIRANO.
    129. Emanuele Taufer, 2008. "Characteristic function estimation of non-Gaussian Ornstein-Uhlenbeck processes," DISA Working Papers 0805, Department of Computer and Management Sciences, University of Trento, Italy, revised 07 Jul 2008.
    130. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    131. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    132. Jozef Baruník, Evzen Kocenda and Lukáa Vácha, 2015. "Volatility Spillovers Across Petroleum Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    133. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
    134. Lee Kyungsub, 2016. "Probabilistic and statistical properties of moment variations and their use in inference and estimation based on high frequency return data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 19-36, February.
    135. Peter Reinhard Hansen & Guillaume Horel & Asger Lunde & Ilya Archakov, 2015. "A Markov Chain Estimator of Multivariate Volatility from High Frequency Data," CREATES Research Papers 2015-19, Department of Economics and Business Economics, Aarhus University.
    136. Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," Economics Series Working Papers 438, University of Oxford, Department of Economics.
    137. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    138. Audrino, Francesco & Corsi, Fulvio, 2010. "Modeling tick-by-tick realized correlations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2372-2382, November.
    139. Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Janeway Institute Working Papers 2208, Faculty of Economics, University of Cambridge.
    140. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," Global COE Hi-Stat Discussion Paper Series gd08-032, Institute of Economic Research, Hitotsubashi University.
    141. Clements, Adam & Vasnev, Andrey, 2021. "Forecast combination puzzle in the HAR model," Working Papers BAWP-2021-01, University of Sydney Business School, Discipline of Business Analytics.
    142. Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    143. Louzis, Dimitrios & Vouldis, Angelos, 2013. "A financial systemic stress index for Greece," Working Paper Series 1563, European Central Bank.
    144. Vassilios G. Papavassiliou, 2016. "Allowing For Jump Measurements In Volatility: A High-Frequency Financial Data Analysis Of Individual Stocks," Bulletin of Economic Research, Wiley Blackwell, vol. 68(2), pages 124-132, April.
    145. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    146. Yu‐Sheng Lai, 2022. "High‐frequency data and stock–bond investing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1623-1638, December.
    147. Marcelo C. Carvalho & Marco Aurélio S. Freire & Marcelo Cunha Medeiros & Leonardo R. Souza, 2006. "Modeling and Forecasting the Volatility of Brazilian Asset Returns: a Realized Variance Approach," Brazilian Review of Finance, Brazilian Society of Finance, vol. 4(1), pages 55-77.
    148. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    149. Davies, Paul Lyndon, 2006. "Long range financial data and model choice," Technical Reports 2006,21, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    150. Rafael Reisenhofer & Xandro Bayer & Nikolaus Hautsch, 2022. "HARNet: A Convolutional Neural Network for Realized Volatility Forecasting," Papers 2205.07719, arXiv.org.
    151. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    152. Nicolas Himounet, 2021. "Searching for the Nature of Uncertainty: Macroeconomic VS Financial," Working Papers 2021.05, International Network for Economic Research - INFER.
    153. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    154. Chuong Luong & Nikolai Dokuchaev, 2018. "Forecasting of Realised Volatility with the Random Forests Algorithm," JRFM, MDPI, vol. 11(4), pages 1-15, October.
    155. Peters, R. & van der Weide, R., 2012. "Volatility: Expectations and Realizations," CeNDEF Working Papers 12-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    156. Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
    157. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
    158. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
    159. Sattarhoff, Cristina & Lux, Thomas, 2023. "Forecasting the variability of stock index returns with the multifractal random walk model for realized volatilities," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1678-1697.
    160. Gael M. Martin & Andrew Reidy & Jill Wright, 2006. "Assessing the Impact of Market Microstructure Noise and Random Jumps on the Relative Forecasting Performance of Option-Implied and Returns-Based Volatility," Monash Econometrics and Business Statistics Working Papers 10/06, Monash University, Department of Econometrics and Business Statistics.
    161. Al Guindy, Mohamed, 2021. "Cryptocurrency price volatility and investor attention," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 556-570.
    162. Turan G. Bali & Lin Peng, 2006. "Is there a risk–return trade‐off? Evidence from high‐frequency data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1169-1198, December.
    163. Campbell, John Y. & Giglio, Stefano & Polk, Christopher & Turley, Robert, 2018. "An Intertemporal CAPM with stochastic volatility," LSE Research Online Documents on Economics 69634, London School of Economics and Political Science, LSE Library.
    164. Dinghai Xu, 2021. "A study on volatility spurious almost integration effect: A threshold realized GARCH approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4104-4126, July.
    165. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2016. "Decoupling the short- and long-term behavior of stochastic volatility," Papers 1610.00332, arXiv.org, revised Jan 2021.
    166. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2010. "Asymmetry and Long Memory in Volatility Modelling," KIER Working Papers 726, Kyoto University, Institute of Economic Research.
    167. Paolo Gorgi & Siem Jan Koopman, 2020. "Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects," Tinbergen Institute Discussion Papers 20-004/III, Tinbergen Institute.
    168. Liu, Guangqiang & Wang, Yan & Chen, Xiaodan & Zhang, Yifeng & Shang, Yue, 2020. "Forecasting volatility of the Chinese stock markets using TVP HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    169. Nikitopoulos, Christina Sklibosios & Thomas, Alice Carole & Wang, Jianxin, 2023. "The economic impact of daily volatility persistence on energy markets," Journal of Commodity Markets, Elsevier, vol. 30(C).
    170. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    171. Audrino, Francesco & Trojani, Fabio, 2011. "A General Multivariate Threshold GARCH Model With Dynamic Conditional Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 138-149.
    172. Eric Hillebrand & Marcelo C. Medeiros, 2012. "Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models," CREATES Research Papers 2012-30, Department of Economics and Business Economics, Aarhus University.
    173. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    174. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Consistent Inference for Predictive Regressions in Persistent Economic Systems," NBER Working Papers 28568, National Bureau of Economic Research, Inc.
    175. Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
    176. MArcelo Carvalho & MArco Aurelio Freire & Marcelo Cunha Medeiros & Leonardo Souza, 2006. "Modeling and forecasting the volatility of Brazilian asset returns," Textos para discussão 530, Department of Economics PUC-Rio (Brazil).
    177. Apergis, Nicholas & Baruník, Jozef & Lau, Marco Chi Keung, 2017. "Good volatility, bad volatility: What drives the asymmetric connectedness of Australian electricity markets?," Energy Economics, Elsevier, vol. 66(C), pages 108-115.
    178. Phillips, Peter C.B. & Yu, Jun, 2009. "A two-stage realized volatility approach to estimation of diffusion processes with discrete data," Journal of Econometrics, Elsevier, vol. 150(2), pages 139-150, June.
    179. Jun Yu, 2009. "Bias in the Estimation of the Mean Reversion Parameter in Continuous Time Models," Microeconomics Working Papers 23045, East Asian Bureau of Economic Research.
    180. Visser, Marcel P., 2008. "Garch Parameter Estimation Using High-Frequency Data," MPRA Paper 9076, University Library of Munich, Germany.
    181. Masato Ubukata & Toshiaki Watanabe, 2014. "Pricing Nikkei 225 Options Using Realized Volatility," The Japanese Economic Review, Japanese Economic Association, vol. 65(4), pages 431-467, December.
    182. A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
    183. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
    184. Ilze Kalnina & Oliver Linton, 2006. "Estimating Quadratic VariationConsistently in thePresence of Correlated MeasurementError," STICERD - Econometrics Paper Series 509, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    185. Stavros Degiannakis & Alexandra Livada, 2016. "Evaluation of realized volatility predictions from models with leptokurtically and asymmetrically distributed forecast errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 871-892, April.
    186. Horpestad, Jone B. & Lyócsa, Štefan & Molnár, Peter & Olsen, Torbjørn B., 2019. "Asymmetric volatility in equity markets around the world," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 540-554.
    187. Hossein Hassani & Mohammad Reza Yeganegi & Rangan Gupta & Riza Demirer, 2018. "Forecasting Stock Market (Realized) Volatility in the United Kingdom: Is There a Role for Economic Inequality?," Working Papers 201880, University of Pretoria, Department of Economics.
    188. Neil Shephard & Ole E. Barndorff-Nielsen & Asger Lunde, 2006. "Subsampling realised kernels," Economics Series Working Papers 278, University of Oxford, Department of Economics.
    189. Mark Podolskij & Mathias Vetter, 2007. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," CREATES Research Papers 2007-27, Department of Economics and Business Economics, Aarhus University.
    190. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    191. Malik, S. & Pitt, M. K., 2011. "Modelling Stochastic Volatility with Leverage and Jumps: A Simulated Maximum Likelihood Approach via Particle Filtering," Working papers 318, Banque de France.
    192. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    193. Neil Shephard, 2013. "Martingale unobserved component models," Economics Papers 2013-W01, Economics Group, Nuffield College, University of Oxford.
    194. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.
    195. Nikolaus Hautsch & Mark Podolskij, 2013. "Preaveraging-Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 165-183, April.
    196. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    197. Ole Barndorff-Nielsen & Svend Erik Graversen & Jean Jacod & Mark Podolskij & Neil Shephard, 2004. "A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales," Economics Papers 2004-W29, Economics Group, Nuffield College, University of Oxford.
    198. Park, Yang-Ho, 2015. "Volatility-of-volatility and tail risk hedging returns," Journal of Financial Markets, Elsevier, vol. 26(C), pages 38-63.
    199. Yu, Qian & Bajja, Salwa, 2020. "Volatility estimation of general Gaussian Ornstein–Uhlenbeck process," Statistics & Probability Letters, Elsevier, vol. 163(C).
    200. Michael Pitt & Sheheryar Malik & Arnaud Doucet, 2014. "Simulated likelihood inference for stochastic volatility models using continuous particle filtering," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(3), pages 527-552, June.
    201. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    202. Lu Lin & Feng Li & Lixing Zhu & Wolfgang Karl Härdle, 2011. "Mean Volatility Regressions," SFB 649 Discussion Papers SFB649DP2011-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    203. John M. Maheu & Thomas H. McCurdy, 2009. "Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions?," Working Paper series 19_09, Rimini Centre for Economic Analysis.
    204. Francesco Audrino & Simon D. Knaus, 2016. "Lassoing the HAR Model: A Model Selection Perspective on Realized Volatility Dynamics," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1485-1521, December.
    205. Torben G. Andersen & Luca Benzoni, 2010. "Do Bonds Span Volatility Risk in the U.S. Treasury Market? A Specification Test for Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 65(2), pages 603-653, April.
    206. Offer Lieberman & Peter Phillips, 2008. "Refined Inference on Long Memory in Realized Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 254-267.
    207. Hansen, Peter R. & Lunde, Asger, 2014. "Estimating The Persistence And The Autocorrelation Function Of A Time Series That Is Measured With Error," Econometric Theory, Cambridge University Press, vol. 30(1), pages 60-93, February.
    208. Zhu, Xuehong & Zhang, Hongwei & Zhong, Meirui, 2017. "Volatility forecasting using high frequency data: The role of after-hours information and leverage effects," Resources Policy, Elsevier, vol. 54(C), pages 58-70.
    209. Cherif Guermat & Richard D. F. Harris, 2006. "Bias in the estimation of non-linear transformations of the integrated variance of returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 481-494.
    210. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk-realised semivariance," Economics Papers 2008-W02, Economics Group, Nuffield College, University of Oxford.
    211. Federico M. Bandi & Roberto Reno, 2009. "Nonparametric Stochastic Volatility," Global COE Hi-Stat Discussion Paper Series gd08-035, Institute of Economic Research, Hitotsubashi University.
    212. Julien Chevallier & Benoît Sévi, 2012. "On the volatility-volume relationship in energy futures markets using intraday data," Post-Print hal-00988926, HAL.
    213. Audrino, Francesco & Hu, Yujia, 2011. "Volatility Forecasting: Downside Risk, Jumps and Leverage Effect," Economics Working Paper Series 1138, University of St. Gallen, School of Economics and Political Science.
    214. Jui‐Cheng Hung & Hung‐Chun Liu & J. Jimmy Yang, 2023. "Does the tail risk index matter in forecasting downside risk?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3451-3466, July.
    215. Michael McAleer & Marcelo Medeiros, 2008. "Realized Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
    216. Neil Shephard & Dacheng Xiu, 2012. "Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices," Economics Papers 2012-W04, Economics Group, Nuffield College, University of Oxford.
    217. Bucci, Andrea & Ciciretti, Vito, 2022. "Market regime detection via realized covariances," Economic Modelling, Elsevier, vol. 111(C).
    218. Mazzarisi, Piero & Zaoli, Silvia & Campajola, Carlo & Lillo, Fabrizio, 2020. "Tail Granger causalities and where to find them: Extreme risk spillovers vs spurious linkages," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    219. Taesuk Lee & Mico Loretan & Werner Ploberger, 2013. "Rate-optimal tests for jumps in diffusion processes," Statistical Papers, Springer, vol. 54(4), pages 1009-1041, November.
    220. Bissoondoyal-Bheenick, Emawtee & Do, Hung & Hu, Xiaolu & Zhong, Angel, 2022. "Sentiment and stock market connectedness: Evidence from the U.S. – China trade war," International Review of Financial Analysis, Elsevier, vol. 80(C).
    221. Adam Clements & Yin Liao, "undated". "News and network structures in equity market volatility," NCER Working Paper Series 110, National Centre for Econometric Research.
    222. Dassios, Angelos & Qu, Yan & Zhao, Hongbiao, 2018. "Exact simulation for a class of tempered stable," LSE Research Online Documents on Economics 86981, London School of Economics and Political Science, LSE Library.
    223. Yao, Xingzhi & Izzeldin, Marwan & Li, Zhenxiong, 2019. "A novel cluster HAR-type model for forecasting realized volatility," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1318-1331.
    224. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
    225. Song, Shijia & Li, Handong, 2023. "A method for predicting VaR by aggregating generalized distributions driven by the dynamic conditional score," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 203-214.
    226. Jeong, Daehee & Kim, Hwagyun & Park, Joon Y., 2015. "Does ambiguity matter? Estimating asset pricing models with a multiple-priors recursive utility," Journal of Financial Economics, Elsevier, vol. 115(2), pages 361-382.
    227. Sina J. Ogede & Emmanuel O. George & Ibrahim A. Adekunle, 2020. "Exploring the Inflationary Effect of Oil Price Volatility in Africa's Oil Exporting Countries," Research Africa Network Working Papers 20/020, Research Africa Network (RAN).
    228. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2007. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," CREATES Research Papers 2007-22, Department of Economics and Business Economics, Aarhus University.
    229. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    230. Claudio Morana, 2008. "Realized Betas and the Cross-Section of Expected Returns," ICER Working Papers - Applied Mathematics Series 15-2008, ICER - International Centre for Economic Research.
    231. Kevin Sheppard & Wen Xu, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    232. Yu, Jun, 2014. "Econometric Analysis Of Continuous Time Models: A Survey Of Peter Phillips’S Work And Some New Results," Econometric Theory, Cambridge University Press, vol. 30(4), pages 737-774, August.
    233. Tim Bollerslev & Hao Zhou, 2007. "Expected Stock Returns and Variance Risk Premia," CREATES Research Papers 2007-17, Department of Economics and Business Economics, Aarhus University.
    234. Bauwens, Luc & Sucarrat, Genaro, 2010. "General-to-specific modelling of exchange rate volatility: A forecast evaluation," International Journal of Forecasting, Elsevier, vol. 26(4), pages 885-907, October.
    235. Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2013. "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns," CREATES Research Papers 2013-07, Department of Economics and Business Economics, Aarhus University.
    236. Ole E. Barndorff-Nielsen & Neil Shephard & Matthias Winkel, 2005. "Limit theorems for multipower variation in the presence of jumps," OFRC Working Papers Series 2005fe06, Oxford Financial Research Centre.
    237. Michael Weylandt & Yu Han & Katherine B. Ensor, 2019. "Multivariate Modeling of Natural Gas Spot Trading Hubs Incorporating Futures Market Realized Volatility," Papers 1907.10152, arXiv.org.
    238. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Economics Papers 2008-W10, Economics Group, Nuffield College, University of Oxford.
    239. Yuta yamauchi & Yasuhiro Omori, 2019. "Multivariate Stochastic Volatility Model with Realized Volatilities and Pairwise Realized Correlations," CIRJE F-Series CIRJE-F-1117, CIRJE, Faculty of Economics, University of Tokyo.
    240. Wang, Hao & Zhou, Hao & Zhou, Yi, 2013. "Credit default swap spreads and variance risk premia," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3733-3746.
    241. Andrea Beltratti & Claudio Morana, 2006. "Comovements in International Stock Markets," ICER Working Papers 3-2006, ICER - International Centre for Economic Research.
    242. Healy, J.V. & Gregoriou, A. & Hudson, R., 2018. "Test of recent advances in extracting information from option prices," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 292-302.
    243. Matthieu Garcin & Martino Grasselli, 2020. "Long vs Short Time Scales: the Rough Dilemma and Beyond," Papers 2008.07822, arXiv.org, revised Nov 2021.
    244. P Gorgi & P R Hansen & P Janus & S J Koopman, 2019. "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 1-32.
    245. Zheng, Biao & Zhang, Yuquan W. & Yin, Haitao & Geng, Yong, 2021. "The limited role of stock market in financing new energy development in China: An investigation using firms’ high-frequency data," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 651-667.
    246. Sergii Pypko, 2015. "Volatility Forecast in Crises and Expansions," JRFM, MDPI, vol. 8(3), pages 1-26, August.
    247. Vaclav Broz & Evzen Kocenda, 2019. "Mortgage-Related Bank Penalties and Systemic Risk Among U.S. Banks," Working Papers IES 2019/25, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2019.
    248. Kim Christensen & Mark Podolskij & Mathias Vetter, 2009. "Bias-correcting the realized range-based variance in the presence of market microstructure noise," Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
    249. Virk, Nader & Javed, Farrukh & Awartani, Basel, 2021. "A reality check on the GARCH-MIDAS volatility models," Working Papers 2021:2, Örebro University, School of Business.
    250. Manabu Asai & Chia-Lin Chang & Michael McAleer, 2016. "Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers," Documentos de Trabajo del ICAE 2016-15, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    251. Morana, Claudio, 2007. "Multivariate modelling of long memory processes with common components," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 919-934, October.
    252. Degiannakis, Stavros & Livada, Alexandra, 2013. "Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process," MPRA Paper 80449, University Library of Munich, Germany.
    253. Chang, Bo Young & Christoffersen, Peter & Jacobs, Kris, 2013. "Market skewness risk and the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 107(1), pages 46-68.
    254. Dong, Yingjie & Tse, Yiu-Kuen, 2017. "On estimating market microstructure noise variance," Economics Letters, Elsevier, vol. 150(C), pages 59-62.
    255. Elisa Alòs & Jorge A. León & Josep Vives, 2006. "On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility," Economics Working Papers 968, Department of Economics and Business, Universitat Pompeu Fabra.
    256. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
    257. Kevin Sheppard & Wen Xu, 2019. "Factor High-Frequency-Based Volatility (HEAVY) Models," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 33-65.
    258. Francis X. Diebold & Georg H. Strasser, 2008. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," Boston College Working Papers in Economics 693, Boston College Department of Economics, revised 24 Apr 2012.
    259. Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021. "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 179-201.
    260. Tomáš Plíhal, 2021. "Scheduled macroeconomic news announcements and Forex volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1379-1397, December.
    261. Chaker, Selma, 2017. "On high frequency estimation of the frictionless price: The use of observed liquidity variables," Journal of Econometrics, Elsevier, vol. 201(1), pages 127-143.
    262. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    263. Engle, Robert F. & Gallo, Giampiero M., 2006. "A multiple indicators model for volatility using intra-daily data," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 3-27.
    264. Lee Jihyun & Kim Tong S & Lee Hoe Kyung, 2010. "Return-Volatility Relationship in High Frequency Data: Multiscale Horizon Dependency," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-43, December.
    265. Xingzhi Yao & Marwan Izzeldin, 2018. "Forecasting using alternative measures of model‐free option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 199-218, February.
    266. Sancetta, Alessio, 2009. "Nearest neighbor conditional estimation for Harris recurrent Markov chains," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2224-2236, November.
    267. Xin Zhang & Donggyu Kim & Yazhen Wang, 2016. "Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets," Econometrics, MDPI, vol. 4(3), pages 1-26, August.
    268. Harald Kinateder & Vassilios G. Papavassiliou, 2019. "Sovereign bond return prediction with realized higher moments," Open Access publications 10197/11286, Research Repository, University College Dublin.
    269. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    270. Bollerslev, Tim & Meddahi, Nour & Nyawa, Serge, 2019. "High-dimensional multivariate realized volatility estimation," Journal of Econometrics, Elsevier, vol. 212(1), pages 116-136.
    271. Ana-Maria Fuertes & Jose Olmo, 2016. "On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?," JRFM, MDPI, vol. 9(3), pages 1-20, September.
    272. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford.
    273. Christensen, Kim & Kinnebrock, Silja & Podolskij, Mark, 2010. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," Journal of Econometrics, Elsevier, vol. 159(1), pages 116-133, November.
    274. Lin, Tiantian & Liu, Dehong & Zhang, Lili & Lung, Peter, 2019. "The information content of realized volatility of sector indices in China’s stock market," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 625-640.
    275. Liao, Yin & Anderson, Heather M., 2019. "Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
    276. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2021. "Random variate generation for exponential and gamma tilted stable distributions," LSE Research Online Documents on Economics 108593, London School of Economics and Political Science, LSE Library.
    277. Liu, Yifan & Popova, Ivilina, 2023. "Threats to central bank independence and exchange rate volatility: High-frequency identification with Trump’s Fed tweets," Finance Research Letters, Elsevier, vol. 53(C).
    278. Massimiliano Caporin & Michael McAleer, 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," Working Papers in Economics 10/58, University of Canterbury, Department of Economics and Finance.
    279. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2017. "Realized stochastic volatility with general asymmetry and long memory," Journal of Econometrics, Elsevier, vol. 199(2), pages 202-212.
    280. Shelton Peiris & Manabu Asai & Michael McAleer, 2016. "Estimating and forecasting generalized fractional Long memory stochastic volatility models," Documentos de Trabajo del ICAE 2016-08, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    281. Wink Junior, Marcos Vinício & Pereira, Pedro Luiz Valls, 2011. "Modeling and Forecasting of Realized Volatility: Evidence from Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 31(2), December.
    282. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
    283. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    284. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    285. Sibel ?EL?K, 2013. "New Evidence on the Relation between Trading Volume and Volatility," Business and Economic Research, Macrothink Institute, vol. 3(1), pages 176-186, June.
    286. Taufer, Emanuele & Leonenko, Nikolai & Bee, Marco, 2011. "Characteristic function estimation of Ornstein-Uhlenbeck-based stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2525-2539, August.
    287. Abramov, Vyacheslav & Klebaner, Fima, 2006. "Forecasting and testing a non-constant volatility," MPRA Paper 207, University Library of Munich, Germany.
    288. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    289. Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.
    290. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    291. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2012. "International market links and volatility transmission," Journal of Econometrics, Elsevier, vol. 170(1), pages 117-141.
    292. Lars Stentoft, 2008. "Option Pricing using Realized Volatility," CREATES Research Papers 2008-13, Department of Economics and Business Economics, Aarhus University.
    293. Linden, Mikael, 2005. "Estimating the distribution of volatility of realized stock returns and exchange rate changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(2), pages 573-583.
    294. Wu, Xinyu & Hou, Xinmeng, 2020. "Forecasting volatility with component conditional autoregressive range model," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    295. Bo Young Chang & Bruno Feunou, 2013. "Measuring Uncertainty in Monetary Policy Using Implied Volatility and Realized Volatility," Staff Working Papers 13-37, Bank of Canada.
    296. Per Mykland, 2012. "A Gaussian calculus for inference from high frequency data," Annals of Finance, Springer, vol. 8(2), pages 235-258, May.
    297. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Power Variation and Time Change," Economics Papers 2002-W24, Economics Group, Nuffield College, University of Oxford.
    298. Li, Zhenxiong & Yao, Xingzhi & Izzeldin, Marwan, 2023. "On the right jump tail inferred from the VIX market," International Review of Financial Analysis, Elsevier, vol. 86(C).
    299. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "A Feasible Central Limit Theory for Realised Volatility Under Leverage," Economics Papers 2004-W03, Economics Group, Nuffield College, University of Oxford.
    300. Claudio Morana, 2008. "Realized portfolio selection in the euro area," ICER Working Papers - Applied Mathematics Series 10-2008, ICER - International Centre for Economic Research.
    301. Yin Liao & Heather M. Anderson & Farshid Vahid, 2010. "Do Jumps Matter? Forecasting Multivariate Realized Volatility allowing for Common Jumps," Monash Econometrics and Business Statistics Working Papers 11/10, Monash University, Department of Econometrics and Business Statistics.
    302. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
    303. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.
    304. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Spillover effects in oil-related CDS markets during and after the sub-prime crisis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    305. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2015. "Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model," Tinbergen Institute Discussion Papers 15-076/IV/DSF94, Tinbergen Institute.
    306. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    307. Meng, Xiaochun & Taylor, James W., 2018. "An approximate long-memory range-based approach for value at risk estimation," International Journal of Forecasting, Elsevier, vol. 34(3), pages 377-388.
    308. Nikolaus Hautsch & Stefan Voigt, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty," Papers 1709.06296, arXiv.org, revised Jun 2018.
    309. Qianqiu Liu, 2009. "On portfolio optimization: How and when do we benefit from high-frequency data?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 560-582.
    310. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    311. Fukasawa, Masaaki, 2010. "Realized volatility with stochastic sampling," Stochastic Processes and their Applications, Elsevier, vol. 120(6), pages 829-852, June.
    312. Helmut Herwartz & Konstantin A. Kholodilin, 2011. "In-Sample and Out-of-Sample Prediction of Stock Market Bubbles: Cross-Sectional Evidence," Discussion Papers of DIW Berlin 1173, DIW Berlin, German Institute for Economic Research.
    313. Daisuke Nagakura & Toshiaki Watanabe, 2010. "A State Space Approach to Estimating the Integrated Variance under the Existence of Market Microstructure Noise," Global COE Hi-Stat Discussion Paper Series gd09-115, Institute of Economic Research, Hitotsubashi University.
    314. Adam E Clements & Christopher A Coleman-Fenn & Daniel R Smith, 2011. "Forecasting Equicorrelation," NCER Working Paper Series 72, National Centre for Econometric Research, revised 29 Aug 2011.
    315. Michael McAleer & Marcelo C. Medeiros, 2009. "Forecasting Realized Volatility with Linear and Nonlinear Models," CARF F-Series CARF-F-189, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    316. Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Indirect inference with time series observed with error," CREATES Research Papers 2014-57, Department of Economics and Business Economics, Aarhus University.
    317. Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    318. Lidan Grossmass, 2014. "Obtaining and Predicting the Bounds of Realized Correlations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(III), pages 191-226, September.
    319. Jacod, Jean & Li, Yingying & Mykland, Per A. & Podolskij, Mark & Vetter, Mathias, 2007. "Microstructure noise in the continuous case: the pre-averaging approach," Technical Reports 2007,41, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    320. Neil Shephard, 2005. "Stochastic Volatility," Economics Papers 2005-W17, Economics Group, Nuffield College, University of Oxford.
    321. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
    322. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    323. Kim, Donggyu & Kong, Xin-Bing & Li, Cui-Xia & Wang, Yazhen, 2018. "Adaptive thresholding for large volatility matrix estimation based on high-frequency financial data," Journal of Econometrics, Elsevier, vol. 203(1), pages 69-79.
    324. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    325. Rama Cont & Purba Das, 2022. "Rough volatility: fact or artefact?," Papers 2203.13820, arXiv.org, revised Jul 2023.
    326. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting," MPRA Paper 35252, University Library of Munich, Germany.
    327. Chao Zhang & Xingyue Pu & Mihai Cucuringu & Xiaowen Dong, 2023. "Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects," Papers 2308.01419, arXiv.org.
    328. Selma Chaker & Nour Meddahi, 2013. "A Distributional Approach to Realized Volatility," Staff Working Papers 13-49, Bank of Canada.
    329. Martin Keller-Ressel & Johannes Muhle-Karbe, 2013. "Asymptotic and exact pricing of options on variance," Finance and Stochastics, Springer, vol. 17(1), pages 107-133, January.
    330. Robert Azencott & Peng Ren & Ilya Timofeyev, 2017. "Realized volatility and parametric estimation of Heston SDEs," Papers 1706.04566, arXiv.org, revised Mar 2020.
    331. Anne Brix & Asger Lunde, 2015. "Prediction-based estimating functions for stochastic volatility models with noisy data: comparison with a GMM alternative," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(4), pages 433-465, October.
    332. Clément, Emmanuelle & Gloter, Arnaud, 2011. "Limit theorems in the Fourier transform method for the estimation of multivariate volatility," Stochastic Processes and their Applications, Elsevier, vol. 121(5), pages 1097-1124, May.
    333. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    334. Yingying Li & Zhiyuan Zhang & Xinghua Zheng, 2013. "Volatility Inference in the Presence of Both Endogenous Time and Microstructure Noise," Papers 1303.5809, arXiv.org.
    335. Oliver Linton & Dajing Shang & Yang Yan, 2012. "Efficient estimation of conditional risk measures in a semiparametric GARCH model," CeMMAP working papers CWP25/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    336. John Elder, Hong Miao, and Sanjay Ramchander, 2013. "Jumps in Oil Prices: The Role of Economic News," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    337. Alexander Alvarez & Fabien Panloup & Monique Pontier & Nicolas Savy, 2012. "Estimation of the instantaneous volatility," Statistical Inference for Stochastic Processes, Springer, vol. 15(1), pages 27-59, April.
    338. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2006. "The Information Content Of Treasury Bond Options Concerning Future Volatility And Price Jumps," Working Paper 1188, Economics Department, Queen's University.
    339. Jun Yu, 2009. "Econometric Analysis of Continuous Time Models : A Survey of Peter Phillips’ Work and Some New Results," Microeconomics Working Papers 23046, East Asian Bureau of Economic Research.
    340. Hacène Djellout & Hui Jiang, 2018. "Large Deviations Of The Threshold Estimator Of Integrated (Co-)Volatility Vector In The Presence Of Jumps," Post-Print hal-01147189, HAL.
    341. Yacine Ait-Sahalia & Jialin Yu, 2009. "High frequency market microstructure noise estimates and liquidity measures," Papers 0906.1444, arXiv.org.
    342. Jullavut Kittiakaraskun & Yiuman Tse & George H.K. Wang, 2011. "The Impact of Trading Activity by Trader Types on Asymmetric Volatility in Nasdaq-100 Index Futures," Working Papers 0021, College of Business, University of Texas at San Antonio.
    343. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Multipower Variation for Brownian Semistationary Processes," CREATES Research Papers 2009-21, Department of Economics and Business Economics, Aarhus University.
    344. Renò, Roberto, 2008. "Nonparametric Estimation Of The Diffusion Coefficient Of Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 24(5), pages 1174-1206, October.
    345. Liu, Yuntong & Wei, Yu & Wang, Qian & Liu, Yi, 2022. "International stock market risk contagion during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    346. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 154-183.
    347. Almut E. D. Veraart, 2010. "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?," CREATES Research Papers 2010-65, Department of Economics and Business Economics, Aarhus University.
    348. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    349. Bollerslev, Tim & Zhou, Hao, 2006. "Volatility puzzles: a simple framework for gauging return-volatility regressions," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 123-150.
    350. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    351. Fleming, Jeff & Kirby, Chris, 2011. "Long memory in volatility and trading volume," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1714-1726, July.
    352. Shabir A A Saleem & Peter N Smith & Abdullah Yalaman, 2021. "Analysis of systematic risk around firm-specific news in an emerging market using high frequency data," CAMA Working Papers 2021-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    353. Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
    354. Elisa Alòs & Jorge A. León, 2021. "An Intuitive Introduction to Fractional and Rough Volatilities," Mathematics, MDPI, vol. 9(9), pages 1-22, April.
    355. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    356. Li, Jia & Todorov, Viktor & Tauchen, George, 2016. "Inference theory for volatility functional dependencies," Journal of Econometrics, Elsevier, vol. 193(1), pages 17-34.
    357. Lee, O. & Shin, D.W., 2008. "Geometric ergodicity and [beta]-mixing property for a multivariate CARR model," Economics Letters, Elsevier, vol. 100(1), pages 111-114, July.
    358. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    359. Frowin Schulz & Karl Mosler, 2011. "The effect of infrequent trading on detecting price jumps," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 27-58, March.
    360. Gustavo Fruet Dias & Cristina M. Scherrer & Fotis Papailias, 2016. "Volatility Discovery," CREATES Research Papers 2016-07, Department of Economics and Business Economics, Aarhus University.
    361. Julien Chevallier & Benoît Sévi, 2009. "On the Realized Volatility of the ECX CO2 Emissions 2008 Futures Contract: Distribution, Dynamics and Forecasting," Working Papers 2009.113, Fondazione Eni Enrico Mattei.
    362. Kleppe, Tore Selland & Liesenfeld, Roman, 2014. "Efficient importance sampling in mixture frameworks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 449-463.
    363. Bee, Marco & Dupuis, Debbie J. & Trapin, Luca, 2016. "Realizing the extremes: Estimation of tail-risk measures from a high-frequency perspective," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 86-99.
    364. David Heath & Eckhard Platen, 2004. "Understanding the Implied Volatility Surface for Options on a Diversified Index," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 11(1), pages 55-77, March.
    365. Grossmass Lidan & Poon Ser-Huang, 2015. "Estimating dynamic copula dependence using intraday data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 501-529, September.
    366. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
    367. Bekierman, Jeremias & Manner, Hans, 2018. "Forecasting realized variance measures using time-varying coefficient models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 276-287.
    368. Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
    369. Raknerud, Arvid & Skare, Øivind, 2012. "Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein–Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3260-3275.
    370. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    371. Arnerić Josip & Poklepović Tea & Teai Juin Wen, 2018. "Neural Network Approach in Forecasting Realized Variance Using High-Frequency Data," Business Systems Research, Sciendo, vol. 9(2), pages 18-34, July.
    372. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Papers 2306.14004, arXiv.org.
    373. D. Schneller & S. Heiden & M. Heiden & A. Hamid, 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, Verein für Socialpolitik, vol. 19(2), pages 209-236, May.
    374. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    375. Rasmus T. Varneskov & Pierre Perron, 2017. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2017-006, Boston University - Department of Economics.
    376. Tim Bollerslev & Jia Li & Zhipeng Liao, 2021. "Fixed‐k inference for volatility," Quantitative Economics, Econometric Society, vol. 12(4), pages 1053-1084, November.
    377. Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
    378. Scharth, Marcel & Medeiros, Marcelo C., 2009. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," International Journal of Forecasting, Elsevier, vol. 25(2), pages 304-327.
    379. Dinghai Xu & Yuying Li, 2010. "Empirical Evidence of the Leverage Effect in a Stochastic Volatility Model: A Realized Volatility Approach," Working Papers 1002, University of Waterloo, Department of Economics, revised May 2010.
    380. Wilson Ye Chen & Richard H. Gerlach, 2017. "Semiparametric GARCH via Bayesian model averaging," Papers 1708.07587, arXiv.org.
    381. Torben G. Andersen & Oleg Bondarenko, 2007. "Construction and Interpretation of Model-Free Implied Volatility," NBER Working Papers 13449, National Bureau of Economic Research, Inc.
    382. De Luca Giovanni & Gallo Giampiero M., 2004. "Mixture Processes for Financial Intradaily Durations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-20, May.
    383. M. Hashem Pesaran & Bahram Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series 2056, CESifo.
    384. Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 94289, University Library of Munich, Germany.
    385. Jun Yu, 2004. "Asymmetric Response of Volatility: Evidence from Stochastic Volatility Models and Realized Volatility," Working Papers 24-2004, Singapore Management University, School of Economics.
    386. Shirota, Shinichiro & Hizu, Takayuki & Omori, Yasuhiro, 2014. "Realized stochastic volatility with leverage and long memory," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 618-641.
    387. Silja Kinnebrock & Mark Podolskij, 2007. "A Note on the Central Limit Theorem for Bipower Variation of General Functions," OFRC Working Papers Series 2007fe03, Oxford Financial Research Centre.
    388. Linton, Oliver & Whang, Yoon-Jae & Yen, Yu-Min, 2016. "A nonparametric test of a strong leverage hypothesis," Journal of Econometrics, Elsevier, vol. 194(1), pages 153-186.
    389. Adam Aleksander Majewski & Giacomo Bormetti & Fulvio Corsi, 2014. "Smile from the Past: A general option pricing framework with multiple volatility and leverage components," Papers 1404.3555, arXiv.org.
    390. Choi, Kyongwook & Yu, Wei-Choun & Zivot, Eric, 2010. "Long memory versus structural breaks in modeling and forecasting realized volatility," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 857-875, September.
    391. Nima Nonejad, 2013. "Long Memory and Structural Breaks in Realized Volatility: An Irreversible Markov Switching Approach," CREATES Research Papers 2013-26, Department of Economics and Business Economics, Aarhus University.
    392. Fan, Jianqing & Kim, Donggyu, 2019. "Structured volatility matrix estimation for non-synchronized high-frequency financial data," Journal of Econometrics, Elsevier, vol. 209(1), pages 61-78.
    393. Fig-Talamanca, Gianna, 2009. "Testing volatility autocorrelation in the constant elasticity of variance stochastic volatility model," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2201-2218, April.
    394. Patton, Andrew J. & Sheppard, Kevin, 2009. "Optimal combinations of realised volatility estimators," International Journal of Forecasting, Elsevier, vol. 25(2), pages 218-238.
    395. Xinwei Feng & Lidan He & Zhi Liu, 2022. "Large Deviation Principles of Realized Laplace Transform of Volatility," Journal of Theoretical Probability, Springer, vol. 35(1), pages 186-208, March.
    396. Dooyeon Cho & Seunghwa Rho, 2022. "On asymmetric volatility effects in currency markets," Empirical Economics, Springer, vol. 62(5), pages 2149-2177, May.
    397. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    398. Werner, Thomas & Stapf, Jelena, 2003. "How wacky is the DAX? The changing structure of German stock market volatility," Discussion Paper Series 1: Economic Studies 2003,18, Deutsche Bundesbank.
    399. Walter Distaso & Basel Awartani & Valentina Corradi, 2004. "Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average," Econometric Society 2004 Australasian Meetings 273, Econometric Society.
    400. Vica Tendenan & Richard Gerlach & Chao Wang, 2020. "Tail risk forecasting using Bayesian realized EGARCH models," Papers 2008.05147, arXiv.org, revised Aug 2020.
    401. Piero Mazzarisi & Silvia Zaoli & Carlo Campajola & Fabrizio Lillo, 2020. "Tail Granger causalities and where to find them: extreme risk spillovers vs. spurious linkages," Papers 2005.01160, arXiv.org, revised May 2021.
    402. Chan, Choon Chat & Fong, Wai Mun, 2006. "Realized volatility and transactions," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2063-2085, July.
    403. Marwan Izzeldin, 2007. "Trading volume and the number of trades," Working Papers 584864, Lancaster University Management School, Economics Department.
    404. Tingguo Zheng & Tao Song, 2014. "A Realized Stochastic Volatility Model With Box-Cox Transformation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 593-605, October.
    405. Ye, Xu-Guo & Lin, Jin-Guan & Zhao, Yan-Yong & Hao, Hong-Xia, 2015. "Two-step estimation of the volatility functions in diffusion models with empirical applications," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 135-159.
    406. Svetlana Borovkova & Diego Mahakena, 2015. "News, volatility and jumps: the case of natural gas futures," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1217-1242, July.
    407. Nonejad, Nima, 2018. "Déjà vol oil? Predicting S&P 500 equity premium using crude oil price volatility: Evidence from old and recent time-series data," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 260-270.
    408. Stavros Degiannakis & Andreas Andrikopoulos & Timotheos Angelidis & Christos Floros, 2013. "Return dispersion, stock market liquidity and aggregate economic activity," Working Papers 166, Bank of Greece.
    409. Olivier Damette & Beum-Jo Park, 2015. "Tobin Tax and Volatility: A Threshold Quantile Autoregressive Regression Framework," Review of International Economics, Wiley Blackwell, vol. 23(5), pages 996-1022, November.
    410. Mingmian Cheng & Norman R. Swanson, 2019. "Fixed and Long Time Span Jump Tests: New Monte Carlo and Empirical Evidence," Econometrics, MDPI, vol. 7(1), pages 1-32, March.
    411. Lin Peng & Turan G. Bali, 2006. "Is there a risk-return trade-off? Evidence from high-frequency data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1169-1198.
    412. Virbickaitė, Audronė & Frey, Christoph & Macedo, Demian N., 2020. "Bayesian sequential stock return prediction through copulas," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    413. Yang Gao & Henry Leung & Stephen Satchell, 2018. "A critique of momentum strategies," Journal of Asset Management, Palgrave Macmillan, vol. 19(5), pages 341-350, September.
    414. Yudong Wang & Zhiyuan Pan & Chongfeng Wu, 2017. "Time‐Varying Parameter Realized Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 566-580, August.
    415. Manabu Asai, 2023. "Estimation of Realized Asymmetric Stochastic Volatility Models Using Kalman Filter," Econometrics, MDPI, vol. 11(3), pages 1-14, July.
    416. Fang, Yan & Ielpo, Florian & Sévi, Benoît, 2012. "Empirical bias in intraday volatility measures," Finance Research Letters, Elsevier, vol. 9(4), pages 231-237.
    417. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01442618, HAL.
    418. Li, Wenqi, 2021. "COVID-19 and asymmetric volatility spillovers across global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    419. Asger Lunde & Anne Floor Brix, 2013. "Estimating Stochastic Volatility Models using Prediction-based Estimating Functions," CREATES Research Papers 2013-23, Department of Economics and Business Economics, Aarhus University.
    420. Wu, Feng & Myers, Robert J. & Guan, Zhengfei & Wang, Zhiguang, 2015. "Risk-adjusted implied volatility and its performance in forecasting realized volatility in corn futures prices," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 260-274.
    421. Oomen, Roel C. A., 2004. "Modelling realized variance when returns are serially correlated [Modellierung realisierter Varianz bei autokorrelierten Erträgen]," Discussion Papers, Research Unit: Market Processes and Governance SP II 2004-11, WZB Berlin Social Science Center.
    422. Daniel Preve & Anders Eriksson & Jun Yu, 2009. "Forecasting Realized Volatility Using A Nonnegative Semiparametric Model," Finance Working Papers 23049, East Asian Bureau of Economic Research.
    423. Charles S. Bos & Paweł Janus & Siem Jan Koopman, 2012. "Spot Variance Path Estimation and Its Application to High-Frequency Jump Testing," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 354-389, 2012 06.
    424. Dimitrios Dadakas & Christos Karpetis & Athanasios Fassas & Erotokritos Varelas, 2016. "Sectoral Differences in the Choice of the Time Horizon during Estimation of the Unconditional Stock Beta," IJFS, MDPI, vol. 4(4), pages 1-13, December.
    425. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    426. MEDDAHI, Nour, 2002. "ARMA Representation of Integrated and Realized Variances," Cahiers de recherche 2002-20, Universite de Montreal, Departement de sciences economiques.
    427. Hossein Hassani & Mohammad Reza Yeganegi & Rangan Gupta & Riza Demirer, 2022. "Forecasting stock market (realized) volatility in the United Kingdom: Is there a role of inequality?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2146-2152, April.
    428. He, Feng & Wang, Ziwei & Yin, Libo, 2020. "Asymmetric volatility spillovers between international economic policy uncertainty and the U.S. stock market," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    429. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    430. M. Dashti Moghaddam & Jiong Liu & R. A. Serota, 2021. "Implied and realized volatility: A study of distributions and the distribution of difference," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2581-2594, April.
    431. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Normal modified stable processes," Economics Papers 2001-W6, Economics Group, Nuffield College, University of Oxford.
    432. Michael Creel, 2021. "Inference Using Simulated Neural Moments," Econometrics, MDPI, vol. 9(4), pages 1-15, September.
    433. Donggyu Kim, 2016. "Statistical Inference for Unified Garch–Itô Models with High-Frequency Financial Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 513-532, July.
    434. Shu, Huisheng & Jiang, Ziwei & Zhang, Xuekang, 2023. "Parameter estimation for integrated Ornstein–Uhlenbeck processes with small Lévy noises," Statistics & Probability Letters, Elsevier, vol. 199(C).
    435. Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.
    436. Oikonomou, Ioannis & Stancu, Andrei & Symeonidis, Lazaros & Wese Simen, Chardin, 2019. "The information content of short-term options," Journal of Financial Markets, Elsevier, vol. 46(C).
    437. Kooli, Maher & Zhou, Xiaozhou, 2020. "IPO flipping activity in China and its implications," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    438. Julien Chevallier & Benoît Sévi, 2011. "On the volatility-volume relationship in energy futures markets using intraday data," Working Papers hal-04140997, HAL.
    439. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
    440. Du, Du, 2011. "General equilibrium pricing of options with habit formation and event risks," Journal of Financial Economics, Elsevier, vol. 99(2), pages 400-426, February.
    441. Zhang, Lan & Mykland, Per A. & Aït-Sahalia, Yacine, 2011. "Edgeworth expansions for realized volatility and related estimators," Journal of Econometrics, Elsevier, vol. 160(1), pages 190-203, January.
    442. Reckling, Dennis, 2016. "Variance risk premia in CO2 markets: A political perspective," Energy Policy, Elsevier, vol. 94(C), pages 345-354.
    443. Ahmed, Walid M.A., 2020. "Is there a risk-return trade-off in cryptocurrency markets? The case of Bitcoin," Journal of Economics and Business, Elsevier, vol. 108(C).
    444. Robert Azencott & Yutheeka Gadhyan & Roland Glowinski, 2014. "Option Pricing Accuracy for Estimated Heston Models," Papers 1404.4014, arXiv.org, revised Jul 2015.
    445. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2014. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Monash Econometrics and Business Statistics Working Papers 30/14, Monash University, Department of Econometrics and Business Statistics.
    446. Simon Clinet & Yoann Potiron, 2021. "Estimation for high-frequency data under parametric market microstructure noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
    447. Bollerslev, Tim & Osterrieder, Daniela & Sizova, Natalia & Tauchen, George, 2013. "Risk and return: Long-run relations, fractional cointegration, and return predictability," Journal of Financial Economics, Elsevier, vol. 108(2), pages 409-424.
    448. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    449. Ulrich Hounyo & Bezirgen Veliyev, 2015. "Validity of Edgeworth expansions for realized volatility estimators," CREATES Research Papers 2015-21, Department of Economics and Business Economics, Aarhus University.
    450. Fei Chen & Francis X. Diebold & Frank Schorfheide, 2012. "A Markov-Switching Multi-Fractal Inter-Trade Duration Model, with Application to U.S. Equities," NBER Working Papers 18078, National Bureau of Economic Research, Inc.
    451. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2004. "Regular and Modified Kernel-Based Estimators of Integrated Variance: The Case with Independent Noise," OFRC Working Papers Series 2004fe20, Oxford Financial Research Centre.
    452. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
    453. Elena Andreou & Eric Ghysels, 2002. "Tests for Breaks in the Conditional Co-movements of Asset Returns," CIRANO Working Papers 2002s-59, CIRANO.
    454. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," Journal of Econometrics, Elsevier, vol. 193(2), pages 367-389.
    455. Fulvio Corsi & Stefano Peluso & Francesco Audrino, 2015. "Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 377-397, April.
    456. Eduardo Rossi & Paolo Santucci de Magistris, 2012. "Estimation of long memory in integrated variance," DEM Working Papers Series 017, University of Pavia, Department of Economics and Management.
    457. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    458. Kalnina, Ilze & Linton, Oliver, 2006. "Estimating quadratic variation consistently in the presence of correlated measurement error," LSE Research Online Documents on Economics 4413, London School of Economics and Political Science, LSE Library.
    459. Proietti, Tommaso, 2014. "Exponential Smoothing, Long Memory and Volatility Prediction," MPRA Paper 57230, University Library of Munich, Germany.
    460. Hautsch, Nikolaus & Kyj, Lada M. & Hautsch, Nikolaus, 2009. "A blocking and regularization approach to high dimensional realized covariance estimation," CFS Working Paper Series 2009/20, Center for Financial Studies (CFS).
    461. Ole Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2002. "Some recent developments in stochastic volatility modelling," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 11-23.
    462. Liu, Zhenya & Lu, Shanglin & Li, Bo & Wang, Shixuan, 2023. "Time series momentum and reversal: Intraday information from realized semivariance," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 54-77.
    463. Xie, Haibin & Yu, Chengtan, 2020. "Realized GARCH models: Simpler is better," Finance Research Letters, Elsevier, vol. 33(C).
    464. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    465. Garland Durham, 2004. "Likelihood-based estimation and specification analysis of one- and two-factor SV models with leverage effects," Econometric Society 2004 North American Summer Meetings 294, Econometric Society.
    466. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.
    467. Emiliano Pagnotta, 2016. "Chasing Private Information," 2016 Meeting Papers 1673, Society for Economic Dynamics.
    468. Zhang, Chuanhai & Liu, Zhi & Liu, Qiang, 2021. "Jumps at ultra-high frequency: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    469. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    470. Ghosh, Anisha & Linton, Oliver, 2009. "Consistent estimation of the risk-return tradeoff in the presence of measurement error," UC3M Working papers. Economics we094928, Universidad Carlos III de Madrid. Departamento de Economía.
    471. Yushu Li & Hyunjoo Kim Karlsson, 2023. "Investigating the Asymmetric Behavior of Oil Price Volatility Using Support Vector Regression," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1765-1790, April.
    472. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.
    473. Pogorelova, Polina & Peresetsky, Anatoly, 2020. "Extracting the global stochastic trend from non-synchronous data on the volatility of financial indices," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 53-71.
    474. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, Department of Economics and Business Economics, Aarhus University.
    475. Richard Y. Chen, 2019. "The Fourier Transform Method for Volatility Functional Inference by Asynchronous Observations," Papers 1911.02205, arXiv.org.
    476. Natalia Bailey & M. Hashem Pesaran & L. Vanessa Smith, 2014. "A Multiple Testing Approach to the Regularisation of Large Sample Correlation Matrices," CESifo Working Paper Series 4834, CESifo.
    477. BEINE, Michel & BOS, Charles S. & LAURENT, Sébastien, 2006. "The impact of Central Bank FX interventions on currency components," LIDAM Reprints CORE 1980, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    478. Jihyun Kim & Nour Meddahi, 2020. "Volatility Regressions with Fat Tails," Post-Print hal-03142647, HAL.
    479. Ole E. Barndorff-Nielsen & Almut E. D. Veraart, 2009. "Stochastic volatility of volatility in continuous time," CREATES Research Papers 2009-25, Department of Economics and Business Economics, Aarhus University.
    480. Atak, Alev & Kapetanios, George, 2013. "A factor approach to realized volatility forecasting in the presence of finite jumps and cross-sectional correlation in pricing errors," Economics Letters, Elsevier, vol. 120(2), pages 224-228.
    481. Reschenhofer, Erhard & Mangat, Manveer Kaur & Stark, Thomas, 2020. "Volatility forecasts, proxies and loss functions," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 133-153.
    482. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    483. Hiroki Masuda & Takayuki Morimoto, 2012. "Optimal Weight For Realized Variance Based On Intermittent High-Frequency Data," The Japanese Economic Review, Japanese Economic Association, vol. 63(4), pages 497-527, December.
    484. Markus Pelger, 2020. "Understanding Systematic Risk: A High‐Frequency Approach," Journal of Finance, American Finance Association, vol. 75(4), pages 2179-2220, August.
    485. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
    486. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    487. Bollerslev, Tim & Todorov, Viktor, 2014. "Time-varying jump tails," Journal of Econometrics, Elsevier, vol. 183(2), pages 168-180.
    488. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.
    489. Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
    490. Gianluca Cubadda & Barbara Guardabascio & Alain Hecq, 2016. "A Vector Heterogeneous Autoregressive Index Model for Realized Volatily Measures," CEIS Research Paper 391, Tor Vergata University, CEIS, revised 23 Jul 2016.
    491. Antoine Lejay & Paolo Pigato, 2019. "A Threshold Model For Local Volatility: Evidence Of Leverage And Mean Reversion Effects On Historical Data," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-24, June.
    492. Christensen, Kim & Thyrsgaard, Martin & Veliyev, Bezirgen, 2019. "The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing," Journal of Econometrics, Elsevier, vol. 212(2), pages 556-583.
    493. Sizova, Natalia, 2011. "Integrated variance forecasting: Model based vs. reduced form," Journal of Econometrics, Elsevier, vol. 162(2), pages 294-311, June.
    494. Zheng, Biao & Zhang, Yuquan & Chen, Yufeng, 2021. "Asymmetric connectedness and dynamic spillovers between renewable energy and rare earth markets in China: Evidence from firms’ high-frequency data," Resources Policy, Elsevier, vol. 71(C).
    495. Pesaran, B. & Pesaran, M.H., 2007. "Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," Cambridge Working Papers in Economics 0734, Faculty of Economics, University of Cambridge.
    496. J. Piplack & M. Beine & B. Candelon, 2009. "Comovements of Returns and Volatility in International Stock Markets: A High-Frequency Approach," Working Papers 09-10, Utrecht School of Economics.
    497. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2011. "The Merit of High-Frequency Data in Portfolio Allocation," SFB 649 Discussion Papers SFB649DP2011-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    498. Sévi, Benoît, 2013. "An empirical analysis of the downside risk-return trade-off at daily frequency," Economic Modelling, Elsevier, vol. 31(C), pages 189-197.
    499. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    500. Amirreza Attarzadeh & Mehmet Balcilar, 2022. "On the Dynamic Connectedness of the Stock, Oil, Clean Energy, and Technology Markets," Energies, MDPI, vol. 15(5), pages 1-18, March.
    501. Fruet Dias, Gustavo & Papailias, Fotis & Scherrer, Cristina, 2023. "An econometric analysis of volatility discovery," LSE Research Online Documents on Economics 121363, London School of Economics and Political Science, LSE Library.
    502. Kim, Donggyu & Wang, Yazhen & Zou, Jian, 2016. "Asymptotic theory for large volatility matrix estimation based on high-frequency financial data," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3527-3577.
    503. Vít Bubák & Filip Žikeš, 2009. "Distribution and Dynamics of Central-European Exchange Rates: Evidence from Intraday Data," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(4), pages 334-359, Oktober.
    504. Andrea Cipollini & Jerry Coakley & Hyunchul Lee, 2015. "The European sovereign debt market: from integration to segmentation," The European Journal of Finance, Taylor & Francis Journals, vol. 21(2), pages 111-128, January.
    505. Fernandes, Marcelo & de Sa Mota, Bernardo & Rocha, Guilherme, 2005. "A multivariate conditional autoregressive range model," Economics Letters, Elsevier, vol. 86(3), pages 435-440, March.
    506. Fan, Jianqing & Fan, Yingying & Jiang, Jiancheng, 2007. "Dynamic Integration of Time- and State-Domain Methods for Volatility Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 618-631, June.
    507. Shu, Yin & Feng, Qianmei & Liu, Hao, 2019. "Using degradation-with-jump measures to estimate life characteristics of lithium-ion battery," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    508. Cai, Wenwu & Lu, Jing, 2019. "Investors’ financial attention frequency and trading activity," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    509. Djellout, Hacène & Guillin, Arnaud & Samoura, Yacouba, 2017. "Estimation of the realized (co-)volatility vector: Large deviations approach," Stochastic Processes and their Applications, Elsevier, vol. 127(9), pages 2926-2960.
    510. Ole E. Barndorff-Nielsen & David G. Pollard & Neil Shephard, 2010. "Discrete-valued Levy processes and low latency financial econometrics," Economics Papers 2010-W04, Economics Group, Nuffield College, University of Oxford.
    511. Xianfei Hui & Baiqing Sun & Hui Jiang & Yan Zhou, 2022. "Modeling dynamic volatility under uncertain environment with fuzziness and randomness," Papers 2204.12657, arXiv.org, revised Oct 2022.
    512. Chourdakis, Kyriakos & Dotsis, George, 2011. "Maximum likelihood estimation of non-affine volatility processes," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 533-545, June.
    513. Schmidt, Anatoly B., 2009. "Detrending the realized volatility in the global FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(9), pages 1887-1892.
    514. Ysusi Carla, 2007. "Multipower Variation Under Market Microstructure Effects," Working Papers 2007-13, Banco de México.
    515. Tao, Minjing & Wang, Yahzen & Yao, Qiwei & Zou, Jian, 2011. "Large volatility matrix inference via combining low-frequency and high-frequency approaches," LSE Research Online Documents on Economics 39321, London School of Economics and Political Science, LSE Library.
    516. Bent Jesper Christensen & Morten Ørregaard Nielsen, 2007. "The Effect of Long Memory in Volatility on Stock Market Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 684-700, November.
    517. Jonathan R. Stroud & Michael S. Johannes, 2014. "Bayesian Modeling and Forecasting of 24-Hour High-Frequency Volatility," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1368-1384, December.
    518. Asger Lunde & Kasper V. Olesen, 2014. "Modeling and Forecasting the Distribution of Energy Forward Returns - Evidence from the Nordic Power Exchange," CREATES Research Papers 2013-19, Department of Economics and Business Economics, Aarhus University.
    519. Griffin, J.E. & Steel, M.F.J., 2006. "Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility," Journal of Econometrics, Elsevier, vol. 134(2), pages 605-644, October.
    520. Markus Bibinger & Moritz Jirak & Mathias Vetter, 2015. "Nonparametric change-point analysis of volatility," SFB 649 Discussion Papers SFB649DP2015-008, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    521. Malec, Peter & Schienle, Melanie, 2014. "Nonparametric kernel density estimation near the boundary," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 57-76.
    522. Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2018. "Model Complexity and Out-of-Sample Performance: Evidence from S&P 500 Index Returns," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 1-29.
    523. Vortelinos, Dimitrios I. & Thomakos, Dimitrios D., 2013. "Nonparametric realized volatility estimation in the international equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 34-45.
    524. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "Dynamic asset price jumps and the performance of high frequency tests and measures," Monash Econometrics and Business Statistics Working Papers 14/17, Monash University, Department of Econometrics and Business Statistics.
    525. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2015. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-979, CIRJE, Faculty of Economics, University of Tokyo.
    526. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Estimating quadratic variation using realised volatility," Economics Papers 2001-W20, Economics Group, Nuffield College, University of Oxford, revised 01 Nov 2001.
    527. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
    528. Bibinger, Markus, 2012. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," Stochastic Processes and their Applications, Elsevier, vol. 122(6), pages 2411-2453.
    529. Taylor, James W., 2004. "Volatility forecasting with smooth transition exponential smoothing," International Journal of Forecasting, Elsevier, vol. 20(2), pages 273-286.
    530. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
    531. Rotfuß, Waldemar, 2009. "Intraday price formation and volatility in the European Union emissions trading scheme: an introductory analysis," ZEW Discussion Papers 09-018, ZEW - Leibniz Centre for European Economic Research.
    532. Bent Jesper Christensen & Morten Ø. Nielsen, 2005. "The Implied-realized Volatility Relation With Jumps In Underlying Asset Prices," Working Paper 1186, Economics Department, Queen's University.
    533. Kyungsub Lee & Byoung Ki Seo, 2019. "Performance of tail hedged portfolio with third moment variation swap," Papers 1908.05105, arXiv.org.
    534. Peter Reinhard Hansen & Zhuo (Albert) Huang & Howard Howan Shek, "undated". "Realized GARCH: A Complete Model of Returns and Realized Measures of Volatility," CREATES Research Papers 2010-13, Department of Economics and Business Economics, Aarhus University.
    535. Ingmar Nolte & Valeri Voev, 2011. "Least Squares Inference on Integrated Volatility and the Relationship Between Efficient Prices and Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 94-108, April.
    536. Hwang, Eunju & Shin, Dong Wan, 2013. "Stationary bootstrapping realized volatility," Statistics & Probability Letters, Elsevier, vol. 83(9), pages 2045-2051.
    537. Yacine Ait-Sahalia & Per A. Mykland & Lan Zhang, 2005. "Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise," NBER Working Papers 11380, National Bureau of Economic Research, Inc.
    538. Fernando Baltazar-Larios & Michael Sørensen, 2010. "Maximum likelihood estimation for integrated diffusion processes," CREATES Research Papers 2010-33, Department of Economics and Business Economics, Aarhus University.
    539. Adam D. Bull, 2015. "Semimartingale detection and goodness-of-fit tests," Papers 1506.00088, arXiv.org, revised Jun 2016.
    540. Bouri, Elie & Lau, Chi Keung Marco & Saeed, Tareq & Wang, Shixuan & Zhao, Yuqian, 2021. "On the intraday return curves of Bitcoin: Predictability and trading opportunities," International Review of Financial Analysis, Elsevier, vol. 76(C).
    541. Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.
    542. Bollerslev, Tim & Zhang, Benjamin Y. B., 2003. "Measuring and modeling systematic risk in factor pricing models using high-frequency data," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 533-558, December.
    543. DeMiguel, Victor & Plyakha, Yuliya & Uppal, Raman & Vilkov, Grigory, 2013. "Improving Portfolio Selection Using Option-Implied Volatility and Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(6), pages 1813-1845, December.
    544. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO.
    545. Caio Ibsen Rodrigues de Almeida & Samy Dana, 2005. "Stochastic Volatility and Option Pricing in the Brazilian Stock Marke," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 4(2), pages 169-206, August.
    546. Dovonon, Prosper & Gonçalves, Sílvia & Meddahi, Nour, 2013. "Bootstrapping realized multivariate volatility measures," Journal of Econometrics, Elsevier, vol. 172(1), pages 49-65.
    547. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    548. Martens, M.P.E. & van Dijk, D.J.C., 2006. "Measuring volatility with the realized range," Econometric Institute Research Papers EI 2006-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    549. Jeffrey R. Russell & Federico M. Bandi, 2004. "Microstructure noise, realized volatility, and optimal sampling," Econometric Society 2004 Latin American Meetings 220, Econometric Society.
    550. Avouyi-Dovi, S. & Idier, J., 2010. "Central bank liquidity and market liquidity: the role of collateral provision on the French government debt securities market," Working papers 278, Banque de France.
    551. Elisa Alòs & Jorge León & Josep Vives, 2007. "On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility," Finance and Stochastics, Springer, vol. 11(4), pages 571-589, October.
    552. Potiron, Yoann & Mykland, Per A., 2017. "Estimation of integrated quadratic covariation with endogenous sampling times," Journal of Econometrics, Elsevier, vol. 197(1), pages 20-41.
    553. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
    554. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
    555. Dimitrios Bakas & Athanasios Triantafyllou, 2017. "The Impact of Uncertainty Shocks on the Volatility of Commodity Prices," Working Paper series 17-31, Rimini Centre for Economic Analysis.
    556. Kalnina, Ilze, 2011. "Subsampling high frequency data," Journal of Econometrics, Elsevier, vol. 161(2), pages 262-283, April.
    557. Adam Clements & Yin Liao, 2013. "The dynamics of co-jumps, volatility and correlation," NCER Working Paper Series 91, National Centre for Econometric Research.
    558. Pesaran, Bahram & Pesaran, M. Hashem, 2010. "Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash," Economic Modelling, Elsevier, vol. 27(6), pages 1398-1416, November.
    559. Lindström, Erik & Ströjby, Jonas & Brodén, Mats & Wiktorsson, Magnus & Holst, Jan, 2008. "Sequential calibration of options," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2877-2891, February.
    560. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "How accurate is the asymptotic approximation to the distribution of realised volatility?," Economics Papers 2001-W16, Economics Group, Nuffield College, University of Oxford.
    561. Claudio Morana, 2007. "Estimating, Filtering and Forecasting Realized Betas," ICER Working Papers - Applied Mathematics Series 6-2007, ICER - International Centre for Economic Research.
    562. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2012. "A nonparametric test of the leverage hypothesis," CeMMAP working papers CWP24/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    563. Mario Bonino & Matteo Camelia & Paolo Pigato, 2016. "A multivariate model for financial indices and an algorithm for detection of jumps in the volatility," Working Papers hal-01408495, HAL.
    564. Viktor Todorov & Yang Zhang, 2022. "Information gains from using short‐dated options for measuring and forecasting volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 368-391, March.
    565. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    566. Chen, Richard Y. & Mykland, Per A., 2017. "Model-free approaches to discern non-stationary microstructure noise and time-varying liquidity in high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 79-103.
    567. Jui-Cheng Hung & Tien-Wei Lou & Yi-Hsien Wang & Jun-De Lee, 2013. "Evaluating and improving GARCH-based volatility forecasts with range-based estimators," Applied Economics, Taylor & Francis Journals, vol. 45(28), pages 4041-4049, October.
    568. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2020. "Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    569. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2012. "A nonparametric test of the leverage hypothesis," CeMMAP working papers 24/12, Institute for Fiscal Studies.
    570. Beine, Michel & Laurent, Sébastien & Palm, Franz C., 2009. "Central bank FOREX interventions assessed using realized moments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 112-127, February.
    571. Long H. Vo, 2017. "Estimating Financial Volatility with High-Frequency Returns," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 2(2), pages 84-114, October.
    572. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    573. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    574. Markus Bibinger & Mathias Vetter, 2015. "Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 707-743, August.
    575. Ryan Shackleton & Sonali Das & Rangan Gupta, 2023. "Comparing Risk Profiles of International Stock Markets as Functional Data: COVID-19 versus the Global Financial Crisis," Working Papers 202328, University of Pretoria, Department of Economics.
    576. Zheng, Tingguo & Xiao, Han & Chen, Rong, 2015. "Generalized ARMA models with martingale difference errors," Journal of Econometrics, Elsevier, vol. 189(2), pages 492-506.
    577. Bent Jesper Christensen & Morten Ø. Nielsen, "undated". "Semiparametric Analysis of Stationary Fractional Cointegration and the Implied-Realized Volatility Relation in High-Frequency Options Data," Economics Working Papers 2001-4, Department of Economics and Business Economics, Aarhus University.
    578. Barletta, Andrea & Santucci de Magistris, Paolo & Violante, Francesco, 2019. "A non-structural investigation of VIX risk neutral density," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 1-20.
    579. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.
    580. Almeida e Santos Nogueira, R.J. & Basturk, N. & Kaymak, U. & Costa Sousa, J.M., 2013. "Estimation of flexible fuzzy GARCH models for conditional density estimation," ERIM Report Series Research in Management ERS-2013-013-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    581. Bertrand Maillet & Jean-Philippe Médecin & Thierry Michel, 2009. "High Watermarks of Market Risks," Post-Print halshs-00425585, HAL.
    582. O’Sullivan, Conall & Papavassiliou, Vassilios G., 2020. "On the term structure of liquidity in the European sovereign bond market," Journal of Banking & Finance, Elsevier, vol. 114(C).
    583. Julien Chevallier, 2010. "Modelling the convenience yield in carbon prices using daily and realized measures," Working Papers halshs-00463921, HAL.
    584. Song, Ziyu & Gong, Xiaomin & Zhang, Cheng & Yu, Changrui, 2023. "Investor sentiment based on scaled PCA method: A powerful predictor of realized volatility in the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 528-545.
    585. Peter C. B. Phillips & Jun Yu, 2006. "A Two-Stage Realized Volatility Approach to Estimation of Diffusion Processes with Discrete," Macroeconomics Working Papers 22472, East Asian Bureau of Economic Research.
    586. Aleksey Kolokolov & Giulia Livieri & Davide Pirino, 2022. "Testing for Endogeneity of Irregular Sampling Schemes," CEIS Research Paper 547, Tor Vergata University, CEIS, revised 19 Dec 2022.
    587. Latini, Luca & Piccirilli, Marco & Vargiolu, Tiziano, 2019. "Mean-reverting no-arbitrage additive models for forward curves in energy markets," Energy Economics, Elsevier, vol. 79(C), pages 157-170.
    588. Pan, Zhiyuan & Shuai, Jiangyu & Liang, Zhilei & Sun, Xianchao, 2022. "Jump dynamics, spillover effect and option valuation," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    589. Bollerslev, Tim & Medeiros, Marcelo C. & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "From zero to hero: Realized partial (co)variances," Journal of Econometrics, Elsevier, vol. 231(2), pages 348-360.
    590. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    591. Özbekler, Ali Gencay & Kontonikas, Alexandros & Triantafyllou, Athanasios, 2020. "Volatility Forecasting in European Government Bond Markets," Essex Finance Centre Working Papers 27362, University of Essex, Essex Business School.
    592. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.
    593. Abdelhakim Aknouche & Bader Almohaimeed & Stefanos Dimitrakopoulos, 2022. "Periodic autoregressive conditional duration," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 5-29, January.
    594. Antonis Demos, 2023. "Estimation of Asymmetric Stochastic Volatility in Mean Models," DEOS Working Papers 2309, Athens University of Economics and Business.
    595. Cordis, Adriana S. & Kirby, Chris, 2014. "Discrete stochastic autoregressive volatility," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 160-178.
    596. Alexander Schnurr, 2014. "An ordinal pattern approach to detect and to model leverage effects and dependence structures between financial time series," Statistical Papers, Springer, vol. 55(4), pages 919-931, November.
    597. Shoji, Isao, 2013. "Filtering for partially observed diffusion and its applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 4966-4976.
    598. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2021. "The impact of hedging on risk-averse agents’ output decisions," Economic Modelling, Elsevier, vol. 104(C).
    599. Lee, Hyunchul & Cho, Seung Mo, 2017. "What drives dynamic comovements of stock markets in the Pacific Basin region?: A quantile regression approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 314-327.
    600. Zhiyuan Liu & M. Dashti Moghaddam & R. A. Serota, 2017. "Distributions of Historic Market Data - Stock Returns," Papers 1711.11003, arXiv.org, revised Dec 2017.
    601. Li, Yingying & Zhang, Zhiyuan & Zheng, Xinghua, 2013. "Volatility inference in the presence of both endogenous time and microstructure noise," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2696-2727.
    602. Majewski, A. A. & Bormetti, G. & Corsi, F., 2013. "Smile from the Past: A general option pricing framework with multiple volatility and leverage components," Working Papers 13/11, Department of Economics, City University London.
    603. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
    604. Warusawitharana, Missaka, 2018. "Time-varying volatility and the power law distribution of stock returns," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 123-141.
    605. Pérez-Rodríguez, Jorge V. & Andrada-Félix, Julián & Rachinger, Heiko, 2021. "Testing the forward volatility unbiasedness hypothesis in exchange rates under long-range dependence," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    606. Chow, Ying-Foon & Lam, James T.K. & Yeung, Hinson S., 2009. "Realized volatility of index constituent stocks in Hong Kong," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2809-2818.
    607. M. Dashti Moghaddam & Zhiyuan Liu & R. A. Serota, 2018. "Distributions of Historic Market Data -- Implied and Realized Volatility," Papers 1804.05279, arXiv.org.
    608. Szczepocki Piotr, 2020. "Application of iterated filtering to stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck process," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 173-187, June.
    609. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
    610. Haselmann, Rainer & Herwartz, Helmut, 2010. "The introduction of the Euro and its effects on portfolio decisions," Journal of International Money and Finance, Elsevier, vol. 29(1), pages 94-110, February.
    611. Yu‐Sheng Lai, 2018. "Estimation of the optimal futures hedge ratio for equity index portfolios using a realized beta generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1370-1390, November.
    612. Evžen Kočenda, 2017. "Survey of volatility and spillovers on financial markets," Working Papers 363, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
    613. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    614. Dutta, Anupam & Knif, Johan & Kolari, James W. & Pynnonen, Seppo, 2018. "A robust and powerful test of abnormal stock returns in long-horizon event studies," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 1-24.
    615. Markus Bibinger & Per A. Mykland, 2016. "Inference for Multi-dimensional High-frequency Data with an Application to Conditional Independence Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1078-1102, December.
    616. Christoffersen, Peter & Feunou, Bruno & Jacobs, Kris & Meddahi, Nour, 2014. "The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 663-697, June.
    617. François-Éric Racicot & Raymond Théoret & Alain Coën, 2008. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 112-124, February.
    618. Bolko, Anine E. & Christensen, Kim & Pakkanen, Mikko S. & Veliyev, Bezirgen, 2023. "A GMM approach to estimate the roughness of stochastic volatility," Journal of Econometrics, Elsevier, vol. 235(2), pages 745-778.
    619. Ole E. Barndorff-Nielsen & Neil Shephard, 2008. "Modelling and measuring volatility," OFRC Working Papers Series 2008fe31, Oxford Financial Research Centre.
    620. Masato Ubukata & Toshiaki Watanabe, 2014. "Market variance risk premiums in Japan for asset predictability," Empirical Economics, Springer, vol. 47(1), pages 169-198, August.
    621. Almut E. D. Veraart, 2008. "Impact of time–inhomogeneous jumps and leverage type effects on returns and realised variances," CREATES Research Papers 2008-57, Department of Economics and Business Economics, Aarhus University.
    622. Ying Chen & Wolfgang Härdle & Uta Pigorsch, 2009. "Localized Realized Volatility Modelling," SFB 649 Discussion Papers SFB649DP2009-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    623. Subbotin, Alexandre, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 15(3), pages 94-138.
    624. Matthieu Garcin & Martino Grasselli, 2022. "Long versus short time scales: the rough dilemma and beyond," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 257-278, June.
    625. Nima Nonejad, 2022. "New Findings Regarding the Out-of-Sample Predictive Impact of the Price of Crude Oil on the United States Industrial Production," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(1), pages 1-35, March.
    626. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    627. Dinghai Xu, 2010. "A Threshold Stochastic Volatility Model with Realized Volatility," Working Papers 1003, University of Waterloo, Department of Economics, revised May 2010.
    628. Blanka Horvath & Antoine Jacquier & Aitor Muguruza & Andreas Sojmark, 2017. "Functional central limit theorems for rough volatility," Papers 1711.03078, arXiv.org, revised Nov 2023.
    629. Ruijun Bu & Degui Li & Oliver Linton & Hanchao Wang, 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Working Papers 202212, University of Liverpool, Department of Economics.
    630. Sean D. Campbell & Canlin Li, 2004. "Alternative estimates of the presidential premium," Finance and Economics Discussion Series 2004-69, Board of Governors of the Federal Reserve System (U.S.).
    631. Yunting Liu, 2022. "The Short-Run and Long-Run Components of Idiosyncratic Volatility and Stock Returns," Management Science, INFORMS, vol. 68(2), pages 1573-1589, February.
    632. Aït-Sahalia, Yacine & Mancini, Loriano, 2008. "Out of sample forecasts of quadratic variation," Journal of Econometrics, Elsevier, vol. 147(1), pages 17-33, November.
    633. Sattarhoff, Cristina & Lux, Thomas, 2021. "Forecasting the Variability of Stock Index Returns with the Multifractal Random Walk Model for Realized Volatilities," Economics Working Papers 2021-02, Christian-Albrechts-University of Kiel, Department of Economics.
    634. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Aug 2018.
    635. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    636. Aganin, Artem & Peresetsky, Anatoly, 2018. "Volatility of ruble exchange rate: Oil and sanctions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 52, pages 5-21.
    637. Ulrich Hounyo, 2013. "Bootstrapping realized volatility and realized beta under a local Gaussianity assumption," CREATES Research Papers 2013-30, Department of Economics and Business Economics, Aarhus University.
    638. Peter C.B. Phillips & Jun Yu, 2007. "Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance," Cowles Foundation Discussion Papers 1597, Cowles Foundation for Research in Economics, Yale University.
    639. Xie, Haibin & Qi, Nan & Wang, Shouyang, 2019. "A new variant of RealGARCH for volatility modeling," Finance Research Letters, Elsevier, vol. 28(C), pages 438-443.
    640. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    641. Ruobing Liu & Jianhui Yang & Chuan-Yang Ruan, 2019. "The Impact of Macroeconomic News on Chinese Futures," IJFS, MDPI, vol. 7(4), pages 1-14, October.
    642. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "The Memory of Volatility," Hannover Economic Papers (HEP) dp-601, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    643. Filip Zikes, 2017. "Measuring Transaction Costs in the Absence of Timestamps," Finance and Economics Discussion Series 2017-045, Board of Governors of the Federal Reserve System (U.S.).
    644. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    645. Benth, Fred Espen & Schroers, Dennis & Veraart, Almut E.D., 2022. "A weak law of large numbers for realised covariation in a Hilbert space setting," Stochastic Processes and their Applications, Elsevier, vol. 145(C), pages 241-268.
    646. Josh Stillwagon, 2013. "Does the Consumption CAPM Help in Accounting for Expected Currency Returns?," Working Papers 1317, Trinity College, Department of Economics.
    647. Behrendt, Simon & Schweikert, Karsten, 2021. "A Note on Adaptive Group Lasso for Structural Break Time Series," Econometrics and Statistics, Elsevier, vol. 17(C), pages 156-172.
    648. Manabu Asai & Mike K. P. So, 2021. "Quasi‐maximum likelihood estimation of conditional autoregressive Wishart models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 271-294, May.
    649. Andersen, Torben G. & Todorov, Viktor & Ubukata, Masato, 2021. "Tail risk and return predictability for the Japanese equity market," Journal of Econometrics, Elsevier, vol. 222(1), pages 344-363.
    650. Nima Nonejad, 2021. "Should crude oil price volatility receive more attention than the price of crude oil? An empirical investigation via a large‐scale out‐of‐sample forecast evaluation of US macroeconomic data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 769-791, August.
    651. Wang, Chengyang & Nishiyama, Yoshihiko, 2015. "Volatility forecast of stock indices by model averaging using high-frequency data," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 324-337.
    652. Chao Zhang & Yihuang Zhang & Mihai Cucuringu & Zhongmin Qian, 2022. "Volatility forecasting with machine learning and intraday commonality," Papers 2202.08962, arXiv.org, revised Feb 2023.
    653. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    654. Markus Bibinger & Lars Winkelmann, 2014. "Common price and volatility jumps in noisy high-frequency data," SFB 649 Discussion Papers SFB649DP2014-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    655. Gianluca Cubadda & Alain Hecq & Antonio Riccardo, 2018. "Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector," CEIS Research Paper 445, Tor Vergata University, CEIS, revised 30 Oct 2018.
    656. Dudley Gilder & Leonidas Tsiaras, 2020. "Volatility forecasts embedded in the prices of crude‐oil options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1127-1159, July.
    657. Creal, Drew D., 2008. "Analysis of filtering and smoothing algorithms for Lévy-driven stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2863-2876, February.
    658. Heejoon Han & Shen Zhang, 2012. "Non‐stationary non‐parametric volatility model," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 204-225, June.
    659. Espen Bernton & Pierre E. Jacob & Mathieu Gerber & Christian P. Robert, 2019. "Approximate Bayesian computation with the Wasserstein distance," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(2), pages 235-269, April.
    660. Nonejad, Nima, 2019. "Forecasting aggregate equity return volatility using crude oil price volatility: The role of nonlinearities and asymmetries," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    661. Anh, V.V. & Leonenko, N.N. & Sakhno, L.M., 2007. "Statistical inference using higher-order information," Journal of Multivariate Analysis, Elsevier, vol. 98(4), pages 706-742, April.
    662. Ma, Chaoqun & Mi, Xianhua & Cai, Zongwu, 2020. "Nonlinear and time-varying risk premia," China Economic Review, Elsevier, vol. 62(C).
    663. Katsuyuki Takahashi & Isao Shoji, 2011. "An empirical analysis of the volatility of the Japanese stock price index: a non-parametric approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1381-1394, June.
    664. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    665. Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
    666. Bent Jesper Christensen & Mads Markvart Kjær & Bezirgen Veliyev, 2021. "The incremental information in the yield curve about future interest rate risk," CREATES Research Papers 2021-11, Department of Economics and Business Economics, Aarhus University.
    667. Bahman Angoshtari & Thaleia Zariphopoulou & Xun Yu Zhou, 2016. "Predictable Forward Performance Processes: The Binomial Case," Papers 1611.04494, arXiv.org, revised Mar 2019.
    668. Mykland, Per A. & Zhang, Lan & Chen, Dachuan, 2019. "The algebra of two scales estimation, and the S-TSRV: High frequency estimation that is robust to sampling times," Journal of Econometrics, Elsevier, vol. 208(1), pages 101-119.
    669. David Heath & Eckhard Platen, 2003. "Pricing of index options under a minimal market model with log-normal scaling," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 442-450.
    670. Papantonis Ioannis & Tzavalis Elias & Agapitos Orestis & Rompolis Leonidas S., 2023. "Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 171-198, April.
    671. Bandi, Federico M. & Russell, Jeffrey R., 2011. "Market microstructure noise, integrated variance estimators, and the accuracy of asymptotic approximations," Journal of Econometrics, Elsevier, vol. 160(1), pages 145-159, January.
    672. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    673. Mike So & Rui Xu, 2013. "Forecasting Intraday Volatility and Value-at-Risk with High-Frequency Data," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 20(1), pages 83-111, March.
    674. Taylor, Nick, 2017. "Realised variance forecasting under Box-Cox transformations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 770-785.
    675. Siem Jan Koopman & Marcel Scharth, 2011. "The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures," Tinbergen Institute Discussion Papers 11-132/4, Tinbergen Institute.
    676. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
    677. Qi Wang & Zerong Wang, 2021. "VIX futures and its closed‐form pricing through an affine GARCH model with realized variance," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 135-156, January.
    678. Jianlei Han & Martina Linnenluecke & Zhangxin Liu & Zheyao Pan & Tom Smith, 2019. "A general equilibrium approach to pricing volatility risk," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-18, April.
    679. Robert Azencott & Peng Ren & Ilya Timofeyev, 2020. "Realised volatility and parametric estimation of Heston SDEs," Finance and Stochastics, Springer, vol. 24(3), pages 723-755, July.
    680. Bertille Antoine & Eric Renault, 2017. "On the relevance of weaker instruments," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 928-945, October.
    681. Alemany, Nuria & Aragó, Vicent & Salvador, Enrique, 2020. "The distribution of index futures realised volatility under seasonality and microstructure noise," Economic Modelling, Elsevier, vol. 93(C), pages 398-414.
    682. Paye, Bradley S., 2012. "‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables," Journal of Financial Economics, Elsevier, vol. 106(3), pages 527-546.
    683. Andrea Bucci & Giulio Palomba & Eduardo Rossi, 2019. "Does macroeconomics help in predicting stock markets volatility comovements? A nonlinear approach," Working Papers 440, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    684. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
    685. Li, Shaoyu & Zheng, Tingguo, 2017. "Modeling spot rate using a realized stochastic volatility model with level effect and dynamic drift☆," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 200-221.
    686. Damien Lynch & Nikolaos Panigirtzoglou, 2004. "Option Implied and Realised Measures of Variance," Money Macro and Finance (MMF) Research Group Conference 2004 94, Money Macro and Finance Research Group.
    687. Vortelinos, Dimitrios I., 2010. "The properties of realized correlation: Evidence from the French, German and Greek equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 273-290, August.
    688. Gkillas Konstantinos & Gupta Rangan & Vortelinos Dimitrios I., 2023. "Uncertainty and realized jumps in the pound-dollar exchange rate: evidence from over one century of data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(1), pages 25-47, February.
    689. Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
    690. Julien Chevallier, 2011. "Detecting Instability in the Volatility of Carbon Prices," Post-Print hal-00991957, HAL.
    691. Takayuki Morimoto & Yoshinori Kawasaki, 2017. "Forecasting Financial Market Volatility Using a Dynamic Topic Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(3), pages 149-167, September.
    692. Worapree Maneesoonthorn & Gael M Martin & Catherine S Forbes, 2018. "Dynamic price jumps: The performance of high frequency tests and measures, and the robustness of inference," Monash Econometrics and Business Statistics Working Papers 17/18, Monash University, Department of Econometrics and Business Statistics.
    693. Zu, Yang & Peter Boswijk, H., 2014. "Estimating spot volatility with high-frequency financial data," Journal of Econometrics, Elsevier, vol. 181(2), pages 117-135.
    694. Mohamed Doukali & Xiaojun Song & Abderrahim Taamouti, 2022. "Value-at Risk under Measurement Error," Working Papers 202209, University of Liverpool, Department of Economics.
    695. Todorov, Viktor & Tauchen, George & Grynkiv, Iaryna, 2011. "Realized Laplace transforms for estimation of jump diffusive volatility models," Journal of Econometrics, Elsevier, vol. 164(2), pages 367-381, October.
    696. Bannouh, K. & van Dijk, D.J.C. & Martens, M.P.E., 2008. "Range-based covariance estimation using high-frequency data: The realized co-range," Econometric Institute Research Papers EI 2007-53, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    697. Park, Sujin & Hong, Seok Young & Linton, Oliver, 2016. "Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error," Journal of Econometrics, Elsevier, vol. 191(2), pages 325-347.
    698. Vladimír Holý & Petra Tomanová, 2023. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 463-485, June.
    699. Imma Valentina Curato & Simona Sanfelici, 2019. "Stochastic leverage effect in high-frequency data: a Fourier based analysis," Papers 1910.06660, arXiv.org, revised Mar 2021.
    700. Flavia Barsotti & Simona Sanfelici, 2012. "Microstructure effect on firm’s volatility risk," Working Papers - Mathematical Economics 2012-05, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    701. Zhang, Lan, 2011. "Estimating covariation: Epps effect, microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 33-47, January.
    702. Diego Amaya & Peter Christoffersen & Kris Jacobs & Aurelio Vasquez, 2013. "Does Realized Skewness Predict the Cross-Section of Equity Returns?," CREATES Research Papers 2013-41, Department of Economics and Business Economics, Aarhus University.
    703. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2005. "Forecasting Exchange Rate Volatility In The Presence Of Jumps," Working Paper 1187, Economics Department, Queen's University.
    704. Josh Stillwagon, 2013. "The Excess Returns Puzzle in Currency Markets: Clues on Moving Forward," Working Papers 1313, Trinity College, Department of Economics.
    705. Shephard, Neil & Xiu, Dacheng, 2017. "Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading," Journal of Econometrics, Elsevier, vol. 201(1), pages 19-42.
    706. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.
    707. Ole E. Barndorff-Nielsen & Svend Erik Graversen & Neil Shephard, 2003. "Power variation & stochastic volatility: a review and some new results," Economics Papers 2003-W19, Economics Group, Nuffield College, University of Oxford.
    708. Elena Andreou & Eric Ghysels, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," CIRANO Working Papers 2004s-25, CIRANO.
    709. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    710. Majewski, Adam A. & Bormetti, Giacomo & Corsi, Fulvio, 2015. "Smile from the past: A general option pricing framework with multiple volatility and leverage components," Journal of Econometrics, Elsevier, vol. 187(2), pages 521-531.
    711. Fang, Libing & Qian, Yichuo & Chen, Ying & Yu, Honghai, 2018. "How does stock market volatility react to NVIX? Evidence from developed countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 490-499.
    712. Wei‐Shao Wu & Sandy Suardi, 2021. "Economic Uncertainty and Bank Lending," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(8), pages 2037-2069, December.
    713. Jean Jacod & Yingying Li & Per A. Mykland & Mark Podolskij & Mathias Vetter, 2007. "Microstructure Noise in the Continuous Case: The Pre-Averaging Approach - JLMPV-9," CREATES Research Papers 2007-43, Department of Economics and Business Economics, Aarhus University.
    714. Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.
    715. Ranaldo, Angelo & de Magistris, Paolo Santucci, 2022. "Liquidity in the global currency market," Journal of Financial Economics, Elsevier, vol. 146(3), pages 859-883.
    716. Piyachart Phiromswad & Pattanaporn Chatjuthamard & Sirimon Treepongkaruna & Sabin Srivannaboon, 2021. "Jumps and Cojumps analyses of major and minor cryptocurrencies," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-9, February.
    717. Imma Valentina Curato, 2013. "Fourier estimation of stochastic leverage using high frequency data," Working Papers - Mathematical Economics 2013-04, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    718. Gonçalves, Sílvia & Meddahi, Nour, 2011. "Box-Cox transforms for realized volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 129-144, January.
    719. Kim Christensen & Mikkel Slot Nielsen & Mark Podolskij, 2021. "High-dimensional estimation of quadratic variation based on penalized realized variance," Papers 2103.03237, arXiv.org.
    720. Julien Chevallier & Benoît Sévi, 2009. "On the realized volatility of the ECX CO2 emissions 2008 futures contract: distribution, dynamics and forecasting," Working Papers hal-04140871, HAL.
    721. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    722. Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
    723. Neil Shephard & Kevin Sheppard, 2012. "Efficient and feasible inference for the components of financial variation using blocked multipower variation," Economics Series Working Papers 593, University of Oxford, Department of Economics.
    724. Lee Kai Ming & Koopman Siem Jan, 2004. "Estimating Stochastic Volatility Models: A Comparison of Two Importance Samplers," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-17, May.
    725. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(4), pages 445-463, October.
    726. Michael Schröder, 2015. "Discrete-Time Approximation of Functionals in Models of Ornstein–Uhlenbeck Type, with Applications to Finance," Methodology and Computing in Applied Probability, Springer, vol. 17(2), pages 285-313, June.
    727. Ji, Qiang & Bouri, Elie & Kristoufek, Ladislav & Lucey, Brian, 2021. "Realised volatility connectedness among Bitcoin exchange markets," Finance Research Letters, Elsevier, vol. 38(C).
    728. Haselmann, Rainer & Herwartz, Helmut, 2008. "Portfolio performance and the Euro: Prospects for new potential EMU members," Journal of International Money and Finance, Elsevier, vol. 27(2), pages 314-330, March.
    729. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    730. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 29-56, Winter.
    731. Jian Chen & Xiaoquan Liu, 2010. "The model-free measures and the volatility spread," Applied Economics Letters, Taylor & Francis Journals, vol. 17(18), pages 1829-1833.
    732. T. Bazhenov & D. Fantazzini, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISIS, vol. 12(1).
    733. Zhang, Hanyu & Dufour, Alfonso, 2019. "Modeling intraday volatility of European bond markets: A data filtering application," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 131-146.
    734. Marcel Prokopczuk & Yingying Wu, 2013. "Estimating term structure models with the Kalman filter," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 4, pages 97-113, Edward Elgar Publishing.
    735. Brockman, Paul & Guo, Tao & Vivero, Maria Gabriela & Yu, Wayne, 2022. "Is idiosyncratic risk priced? The international evidence," Journal of Empirical Finance, Elsevier, vol. 66(C), pages 121-136.
    736. Viktor Bezborodov & Luca Persio & Yuliya Mishura, 2019. "Option Pricing with Fractional Stochastic Volatility and Discontinuous Payoff Function of Polynomial Growth," Methodology and Computing in Applied Probability, Springer, vol. 21(1), pages 331-366, March.
    737. Lorenzo Camponovo & Yukitoshi Matsushita & Taisuke Otsu, 2015. "Nonparametric likelihood for volatility under high frequency data," STICERD - Econometrics Paper Series /2015/581, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    738. Jong Jun Park & Kyungsub Lee, 2019. "Computational method for probability distribution on recursive relationships in financial applications," Papers 1908.04959, arXiv.org.
    739. Eleonora Iachini & Stefano Nobili, 2014. "An indicator of systemic liquidity risk in the Italian financial markets," Questioni di Economia e Finanza (Occasional Papers) 217, Bank of Italy, Economic Research and International Relations Area.
    740. Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.
    741. Rafiq, Shuddhasawtta & Salim, Ruhul & Bloch, Harry, 2009. "Impact of crude oil price volatility on economic activities: An empirical investigation in the Thai economy," Resources Policy, Elsevier, vol. 34(3), pages 121-132, September.
    742. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Density Estimators for Daily Volatility Based on the Use of Realized Measures," Departmental Working Papers 200620, Rutgers University, Department of Economics.
    743. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02505861, HAL.
    744. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
    745. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    746. Gordon R. Richards, 2004. "A fractal forecasting model for financial time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(8), pages 586-601.
    747. David E. Allen & Michael McAleer, 2020. "Do We Need Stochastic Volatility and Generalised Autoregressive Conditional Heteroscedasticity? Comparing Squared End-Of-Day Returns on FTSE," Risks, MDPI, vol. 8(1), pages 1-20, February.
    748. Yin Liao, 2012. "Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction," CAMA Working Papers 2012-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    749. Haselmann, Rainer & Helmut, Herwartz, 2005. "The Introduction of the Euro and its Effects on Investment Decisions," Economics Working Papers 2005-15, Christian-Albrechts-University of Kiel, Department of Economics.
    750. Macaro, Christian, 2010. "Bayesian non-parametric signal extraction for Gaussian time series," Journal of Econometrics, Elsevier, vol. 157(2), pages 381-395, August.
    751. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    752. Elezovic, Suad, 2009. "Functional modelling of volatility in the Swedish limit order book," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2107-2118, April.
    753. Yeh, Jin-Huei & Wang, Jying-Nan, 2010. "Correcting microstructure comovement biases for integrated covariance," Finance Research Letters, Elsevier, vol. 7(3), pages 184-191, September.
    754. Kalnina, Ilze & Linton, Oliver, 2008. "Estimating quadratic variation consistently in the presence of endogenous and diurnal measurement error," Journal of Econometrics, Elsevier, vol. 147(1), pages 47-59, November.
    755. Corsi, Fulvio & Fusari, Nicola & La Vecchia, Davide, 2013. "Realizing smiles: Options pricing with realized volatility," Journal of Financial Economics, Elsevier, vol. 107(2), pages 284-304.
    756. Taylor, Nicholas, 2007. "A note on the importance of overnight information in risk management models," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 161-180, January.
    757. Greeshma Balabhadra & El Mehdi Ainasse & Pawel Polak, 2023. "High-Frequency Volatility Estimation with Fast Multiple Change Points Detection," Papers 2303.10550, arXiv.org, revised Mar 2023.
    758. Pierre Chausse & Dinghai Xu, 2012. "GMM Estimation of a Stochastic Volatility Model with Realized Volatility: A Monte Carlo Study," Working Papers 1203, University of Waterloo, Department of Economics, revised May 2012.
    759. Yuta Yamauchi & Yasuhiro Omori, 2018. "Multivariate Stochastic Volatility Model with Realized Volatilities and Pairwise Realized Correlations," Papers 1809.09928, arXiv.org, revised Mar 2019.
    760. P. Brockwell, 2014. "Recent results in the theory and applications of CARMA processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(4), pages 647-685, August.
    761. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    762. Prateek Sharma & Swati Sharma, 2015. "Forecasting gains of robust realized variance estimators: evidence from European stock markets," Economics Bulletin, AccessEcon, vol. 35(1), pages 61-69.
    763. Shrestha, Prabal & Arslan-Ayaydin, Özgür & Thewissen, James & Torsin, Wouter, 2021. "Institutions, regulations and initial coin offerings: An international perspective," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 102-120.
    764. Qiankun Zhou & Jun Yu, 2012. "Asymptotic Distributions of the Least Squares Estimator for Diffusion Processes," Working Papers 11-2012, Singapore Management University, School of Economics.
    765. Torben G. Andersen & Rasmus T. Varneskov, 2018. "Consistent Inference for Predictive Regressions in Persistent VAR Economies," CREATES Research Papers 2018-09, Department of Economics and Business Economics, Aarhus University.
    766. Badshah, Ihsan & Bekiros, Stelios & Lucey, Brian M. & Uddin, Gazi Salah, 2018. "Asymmetric linkages among the fear index and emerging market volatility indices," Emerging Markets Review, Elsevier, vol. 37(C), pages 17-31.
    767. Bissoondoyal-Bheenick, Emawtee & Brooks, Robert & Do, Hung Xuan & Smyth, Russell, 2020. "Exploiting the heteroskedasticity in measurement error to improve volatility predictions in oil and biofuel feedstock markets," Energy Economics, Elsevier, vol. 86(C).
    768. Jianqing Fan & Jingjin Zhang & Ke Yu, 2008. "Asset Allocation and Risk Assessment with Gross Exposure Constraints for Vast Portfolios," Papers 0812.2604, arXiv.org.
    769. Kleppe, Tore Selland & Liesenfeld, Roman, 2011. "Efficient high-dimensional importance sampling in mixture frameworks," Economics Working Papers 2011-11, Christian-Albrechts-University of Kiel, Department of Economics.
    770. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2014. "Realized volatility models and alternative Value-at-Risk prediction strategies," Economic Modelling, Elsevier, vol. 40(C), pages 101-116.
    771. A. Amendola & V. Candila, 2016. "Evaluation of volatility predictions in a VaR framework," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 695-709, May.
    772. Cem Cakmakli & Verda Ozturk, 2021. "Economic Value of Modeling the Joint Distribution of Returns and Volatility: Leverage Timing," Koç University-TUSIAD Economic Research Forum Working Papers 2110, Koc University-TUSIAD Economic Research Forum.
    773. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2023. "Shot-noise cojumps: exact simulation and option pricing," LSE Research Online Documents on Economics 111537, London School of Economics and Political Science, LSE Library.
    774. Qianjie Geng & Xianfeng Hao & Yudong Wang, 2024. "Forecasting the volatility of crude oil futures: A time‐dependent weighted least squares with regularization constraint," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 309-325, March.
    775. Henker, Thomas & Husodo, Zaäfri A., 2010. "Noise and efficient variance in the Indonesia Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 18(2), pages 199-216, April.
    776. Bandi, Federico M. & Perron, Benoît, 2008. "Long-run risk-return trade-offs," Journal of Econometrics, Elsevier, vol. 143(2), pages 349-374, April.
    777. Juan M. Londono, 2011. "The variance risk premium around the world," International Finance Discussion Papers 1035, Board of Governors of the Federal Reserve System (U.S.).
    778. Wang, Ziwei & Li, Youwei & He, Feng, 2020. "Asymmetric volatility spillovers between economic policy uncertainty and stock markets: Evidence from China," Research in International Business and Finance, Elsevier, vol. 53(C).
    779. David Edmund Allen, 2020. "Stochastic Volatility and GARCH: Do Squared End-of-Day Returns Provide Similar Information?," JRFM, MDPI, vol. 13(9), pages 1-25, September.
    780. Bandi, Federico M. & Russell, Jeffrey R. & Yang, Chen, 2008. "Realized volatility forecasting and option pricing," Journal of Econometrics, Elsevier, vol. 147(1), pages 34-46, November.
    781. Peter Feldhütter & Christian Heyerdahl-Larsen & Philipp Illeditsch, 2018. "Risk Premia and Volatilities in a Nonlinear Term Structure Model [Quadratic term structure models: theory and evidence]," Review of Finance, European Finance Association, vol. 22(1), pages 337-380.
    782. Liu, Guangying & Zhang, Xinsheng, 2011. "Power variation of fractional integral processes with jumps," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 962-972, August.
    783. Li, Yingying & Liu, Guangying & Zhang, Zhiyuan, 2022. "Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps," Journal of Econometrics, Elsevier, vol. 229(2), pages 422-451.
    784. Michel Beine & Sébastien Laurent & Franz Palm, 2007. "Central bank intervention in the foreign exchange markets assessed using realized moments," ULB Institutional Repository 2013/10407, ULB -- Universite Libre de Bruxelles.
    785. Caporin, Massimiliano & Velo, Gabriel G., 2015. "Realized range volatility forecasting: Dynamic features and predictive variables," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 98-112.
    786. Elisa Al`os & David Garc'ia-Lorite & Aitor Muguruza, 2018. "On smile properties of volatility derivatives and exotic products: understanding the VIX skew," Papers 1808.03610, arXiv.org.
    787. Wu, Peng & Muzy, Jean-François & Bacry, Emmanuel, 2022. "From rough to multifractal volatility: The log S-fBM model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    788. Vladimir Petrov & Anton Golub & Richard Olsen, 2019. "Instantaneous Volatility Seasonality of High-Frequency Markets in Directional-Change Intrinsic Time," JRFM, MDPI, vol. 12(2), pages 1-31, April.
    789. Liu, Chun & Maheu, John M., 2012. "Intraday dynamics of volatility and duration: Evidence from Chinese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 20(3), pages 329-348.
    790. Jiang, Wei & Ruan, Qingsong & Li, Jianfeng & Li, Ye, 2018. "Modeling returns volatility: Realized GARCH incorporating realized risk measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 249-258.
    791. Sergey S. Stepanov, 2009. "Resilience of Volatility," Papers 0911.5048, arXiv.org.
    792. Andrada-Félix, Julián & Fernández-Rodríguez, Fernando & Fuertes, Ana-Maria, 2016. "Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?," International Journal of Forecasting, Elsevier, vol. 32(3), pages 695-715.
    793. Müller, Christian, 2015. "Radical uncertainty: Sources, manifestations and implications," Economics Discussion Papers 2015-41, Kiel Institute for the World Economy (IfW Kiel).
    794. Morelli, Giacomo & Santucci de Magistris, Paolo, 2019. "Volatility tail risk under fractionality," Journal of Banking & Finance, Elsevier, vol. 108(C).
    795. Yacine Ait-Sahalia & Per A. Mykland, 2003. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," NBER Working Papers 9611, National Bureau of Economic Research, Inc.
    796. Markus Bibinger & Mathias Vetter, 2013. "Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps," SFB 649 Discussion Papers SFB649DP2013-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    797. Todorov, Viktor, 2011. "Econometric analysis of jump-driven stochastic volatility models," Journal of Econometrics, Elsevier, vol. 160(1), pages 12-21, January.
    798. Neil Shephard & Silja Kinnebrock & Ole E. Barndorff-Neilsen, 2008. "Measuring downside risk - realised semivariance," Economics Series Working Papers 382, University of Oxford, Department of Economics.
    799. N. Chopin & P. E. Jacob & O. Papaspiliopoulos, 2013. "SMC-super-2: an efficient algorithm for sequential analysis of state space models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(3), pages 397-426, June.
    800. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.
    801. Adamantios Ntakaris & Giorgio Mirone & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Feature Engineering for Mid-Price Prediction with Deep Learning," Papers 1904.05384, arXiv.org, revised Jun 2019.
    802. Grané, Aurea & Veiga, Helena, 2007. "The effect of realised volatility on stock returns risk estimates," DES - Working Papers. Statistics and Econometrics. WS ws076316, Universidad Carlos III de Madrid. Departamento de Estadística.
    803. Aitor Ciarreta & Peru Muniainy & Ainhoa Zarraga, 2017. "Modelling Realized Volatility in Electricity Spot Prices: New insights and Application to the Japanese Electricity Market," ISER Discussion Paper 0991, Institute of Social and Economic Research, Osaka University.
    804. Jia, Zhanliang & Cui, Meilan & Li, Handong, 2012. "Research on the relationship between the multifractality and long memory of realized volatility in the SSECI," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 740-749.
    805. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    806. Palandri, Alessandro, 2015. "Do negative and positive equity returns share the same volatility dynamics?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 486-505.
    807. Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
    808. Lan Zhang, 2012. "Implied and realized volatility: empirical model selection," Annals of Finance, Springer, vol. 8(2), pages 259-275, May.
    809. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Realised power variation and stochastic volatility models," Economics Papers 2001-W18, Economics Group, Nuffield College, University of Oxford.
    810. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
    811. Jacod, Jean & Mykland, Per A., 2015. "Microstructure noise in the continuous case: Approximate efficiency of the adaptive pre-averaging method," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2910-2936.
    812. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Sivaprasad, Sheeja, 2021. "The impact of Covid-19 on G7 stock markets volatility: Evidence from a ST-HAR model," International Review of Financial Analysis, Elsevier, vol. 74(C).
    813. Adam E Clements & Yin Liao, 2013. "Modeling and forecasting realized volatility: getting the most out of the jump component," NCER Working Paper Series 93, National Centre for Econometric Research.
    814. Ma, Feng & Wei, Yu & Huang, Dengshi & Chen, Yixiang, 2014. "Which is the better forecasting model? A comparison between HAR-RV and multifractality volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 171-180.
    815. B. Jungbacker & S.J. Koopman, 2005. "Model-based Measurement of Actual Volatility in High-Frequency Data," Tinbergen Institute Discussion Papers 05-002/4, Tinbergen Institute.
    816. Clements, A. & Silvennoinen, A., 2013. "Volatility timing: How best to forecast portfolio exposures," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 108-115.
    817. Seema REHMAN & Saqib SHARIF & Wali ULLAH, 2021. "Higher Realized Moments and Stock Return Predictability," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 48-70, December.
    818. Fuertes, Ana-Maria & Izzeldin, Marwan & Kalotychou, Elena, 2009. "On forecasting daily stock volatility: The role of intraday information and market conditions," International Journal of Forecasting, Elsevier, vol. 25(2), pages 259-281.
    819. Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
    820. Peter Reinhard Hansen & Guillaume Horel, 2009. "Quadratic Variation by Markov Chains," CREATES Research Papers 2009-13, Department of Economics and Business Economics, Aarhus University.
    821. Tian, Xiao & Duong, Huu Nhan & Kalev, Petko S., 2019. "Information content of the limit order book for crude oil futures price volatility," Energy Economics, Elsevier, vol. 81(C), pages 584-597.
    822. Yuta Yamauchi & Yasuhiro Omori, 2016. "Multivariate Stochastic Volatility Model with Realized Volatilities and Pairwise Realized Correlations ," CIRJE F-Series CIRJE-F-1029, CIRJE, Faculty of Economics, University of Tokyo.
    823. Ho‐Chuan (River) Huang & Chien‐Chung Nieh, 2004. "Realize the Realized Stock Index Volatility," Asian Economic Journal, East Asian Economic Association, vol. 18(1), pages 59-80, March.
    824. Markus Bibinger & Per A. Mykland, 2013. "Inference for Multi-Dimensional High-Frequency Data: Equivalence of Methods, Central Limit Theorems, and an Application to Conditional Independence Testing," SFB 649 Discussion Papers SFB649DP2013-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    825. Horta, Eduardo & Ziegelmann, Flavio, 2018. "Dynamics of financial returns densities: A functional approach applied to the Bovespa intraday index," International Journal of Forecasting, Elsevier, vol. 34(1), pages 75-88.
    826. Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
    827. Qi Xu & Ying Wang, 2021. "Managing volatility in commodity momentum," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 758-782, May.
    828. Alain Hecq & Marie Ternes & Ines Wilms, 2023. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Papers 2301.10592, arXiv.org.
    829. Maria Elvira Mancino & Maria Cristina Recchioni, 2015. "Fourier Spot Volatility Estimator: Asymptotic Normality and Efficiency with Liquid and Illiquid High-Frequency Data," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-33, September.
    830. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    831. Rasmus Tangsgaard Varneskov, 2011. "Generalized Flat-Top Realized Kernel Estimation of Ex-Post Variation of Asset Prices Contaminated by Noise," CREATES Research Papers 2011-31, Department of Economics and Business Economics, Aarhus University.
    832. Kim Christensen & Mikkel Slot Nielsen & Mark Podolskij, 2023. "High-dimensional estimation of quadratic variation based on penalized realized variance," Statistical Inference for Stochastic Processes, Springer, vol. 26(2), pages 331-359, July.
    833. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    834. Dey, Asim K. & Hoque, G.M. Toufiqul & Das, Kumer P. & Panovska, Irina, 2022. "Impacts of COVID-19 local spread and Google search trend on the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    835. Wu, Xinyu & Hou, Xinmeng, 2019. "Forecasting realized variance using asymmetric HAR model with time-varying coefficients," Finance Research Letters, Elsevier, vol. 30(C), pages 89-95.
    836. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2016. "Common trends in global volatility," Journal of International Money and Finance, Elsevier, vol. 67(C), pages 194-214.
    837. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
    838. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility Regressions with Fat Tails," TSE Working Papers 20-1097, Toulouse School of Economics (TSE).
    839. Goddard, John & Kita, Arben & Wang, Qingwei, 2015. "Investor attention and FX market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 79-96.
    840. Abanto-Valle, C.A. & Bandyopadhyay, D. & Lachos, V.H. & Enriquez, I., 2010. "Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2883-2898, December.
    841. Richard Hawkes & Paresh Date, 2007. "Medium‐term horizon volatility forecasting: A comparative study," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 23(6), pages 465-481, November.
    842. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
    843. Tingguo Zheng & Han Xiao & Rong Chen, 2021. "Generalized Autoregressive Moving Average Models with GARCH Errors," Papers 2105.05532, arXiv.org.
    844. Chen, Yufeng & Li, Wenqi & Qu, Fang, 2019. "Dynamic asymmetric spillovers and volatility interdependence on China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 825-838.
    845. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    846. Stelzer Robert & Wittlinger Marc & Tosstorff Thomas, 2015. "Moment based estimation of supOU processes and a related stochastic volatility model," Statistics & Risk Modeling, De Gruyter, vol. 32(1), pages 1-24, April.
    847. Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
    848. Tingguo Zheng & Han Xiao & Rong Chen, 2022. "Generalized autoregressive moving average models with GARCH errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 125-146, January.
    849. Tong Fang & Deyu Miao & Zhi Su & Libo Yin, 2023. "Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 872-904, July.
    850. Nima Nonejad, 2013. "A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory," CREATES Research Papers 2013-24, Department of Economics and Business Economics, Aarhus University.
    851. Masato Ubukata, 2019. "Jump tail risk premium and predicting US and Japanese credit spreads," Empirical Economics, Springer, vol. 57(1), pages 79-104, July.
    852. Sujin Park & Oliver Linton, 2012. "Estimating the Quadratic Covariation Matrix for an Asynchronously Observed Continuous Time Signal Masked by Additive Noise," FMG Discussion Papers dp703, Financial Markets Group.
    853. Díaz, Fernando & Henríquez, Pablo A. & Winkelried, Diego, 2022. "Stock market volatility and the COVID-19 reproductive number," Research in International Business and Finance, Elsevier, vol. 59(C).
    854. Diop, Assane & Jacod, Jean & Todorov, Viktor, 2013. "Central Limit Theorems for approximate quadratic variations of pure jump Itô semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 123(3), pages 839-886.
    855. Huang, Chuangxia & Zhao, Xian & Deng, Yunke & Yang, Xiaoguang & Yang, Xin, 2022. "Evaluating influential nodes for the Chinese energy stocks based on jump volatility spillover network," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 81-94.
    856. Qiang Liu & Zhi Liu, 2022. "Estimating spot volatility under infinite variation jumps with dependent market microstructure noise," Papers 2205.15738, arXiv.org, revised Feb 2023.
    857. Umberto Triacca & Fulvia Focker, 2014. "Estimating overnight volatility of asset returns by using the generalized dynamic factor model approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 235-254, October.
    858. Malgorzata Doman, 2010. "Liquidity and Market Microstructure Noise: Evidence from the Pekao Data," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 5-14.
    859. Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
    860. Jian Zhou, 2017. "Forecasting REIT volatility with high-frequency data: a comparison of alternative methods," Applied Economics, Taylor & Francis Journals, vol. 49(26), pages 2590-2605, June.
    861. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    862. Hung, Jui-Cheng, 2015. "Evaluation of realized multi-power variations in minimum variance hedging," Economic Modelling, Elsevier, vol. 51(C), pages 672-679.
    863. Louzis, Dimitrios P. & Vouldis, Angelos T., 2012. "A methodology for constructing a financial systemic stress index: An application to Greece," Economic Modelling, Elsevier, vol. 29(4), pages 1228-1241.
    864. Hao Wang & Hao Zhou & Yi Zhou, 2011. "Credit default swap spreads and variance risk premia," Finance and Economics Discussion Series 2011-02, Board of Governors of the Federal Reserve System (U.S.).
    865. Ulrich Hounyo & Rasmus T. Varneskov, 2015. "A Local Stable Bootstrap for Power Variations of Pure-Jump Semimartingales and Activity Index Estimation," CREATES Research Papers 2015-26, Department of Economics and Business Economics, Aarhus University.
    866. Stavros Degiannakis & George Filis & Renatas Kizys, 2013. "Oil price shocks and stock market volatility: evidence from European data," Working Papers 161, Bank of Greece.
    867. Xin-Bing Kong, 2017. "On the number of common factors with high-frequency data," Biometrika, Biometrika Trust, vol. 104(2), pages 397-410.
    868. Durham, Garland B., 2006. "Monte Carlo methods for estimating, smoothing, and filtering one- and two-factor stochastic volatility models," Journal of Econometrics, Elsevier, vol. 133(1), pages 273-305, July.
    869. Curato, Imma Valentina, 2019. "Estimation of the stochastic leverage effect using the Fourier transform method," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3207-3238.
    870. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    871. Peter C.B. Phillips & Jun Yu, 2005. "A Two-Stage Realized Volatility Approach to the Estimation for Diffusion Processes from Discrete Observations," Cowles Foundation Discussion Papers 1523, Cowles Foundation for Research in Economics, Yale University.
    872. Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
    873. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
    874. Daniel J Lewis, 2021. "Identifying Shocks via Time-Varying Volatility [First Order Autoregressive Processes and Strong Mixing]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(6), pages 3086-3124.
    875. Peter C. B. Phillips & Jun Yu, 2005. "Comments on “A Selective Overview of Nonparametric Methods in Financial Econometrics” by Jianqing Fan," Working Papers 08-2005, Singapore Management University, School of Economics.
    876. Didit Budi Nugroho & Takayuki Morimoto, 2019. "Incorporating Realized Quarticity into a Realized Stochastic Volatility Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(4), pages 495-528, December.
    877. Stojanović, Vladica S. & Popović, Biljana Č. & Milovanović, Gradimir V., 2016. "The Split-SV model," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 560-581.
    878. Huang, Wenqian & Ranaldo, Angelo & Schrimpf, Andreas & Somogyi, Fabricius, 2022. "Constrained Dealers and Market Efficiency," VfS Annual Conference 2022 (Basel): Big Data in Economics 264054, Verein für Socialpolitik / German Economic Association.
    879. Flavia Barsotti & Simona Sanfelici, 2016. "Market Microstructure Effects on Firm Default Risk Evaluation," Econometrics, MDPI, vol. 4(3), pages 1-31, July.
    880. Liu, Guangqiang & Wei, Yu & Chen, Yongfei & Yu, Jiang & Hu, Yang, 2018. "Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 288-297.
    881. Feng, Jiabao & Wang, Yudong & Yin, Libo, 2017. "Oil volatility risk and stock market volatility predictability: Evidence from G7 countries," Energy Economics, Elsevier, vol. 68(C), pages 240-254.
    882. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay & Villupuram, Sriram, 2014. "Currency jumps, cojumps and the role of macro news," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 42-62.
    883. Clements, A.E. & Liao, Y., 2020. "Firm-specific information and systemic risk," Economic Modelling, Elsevier, vol. 90(C), pages 480-493.
    884. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    885. Matei, Marius, 2011. "Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 116-141, June.
    886. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    887. Chevallier, Julien, 2013. "Variance risk-premia in CO2 markets," Economic Modelling, Elsevier, vol. 31(C), pages 598-605.
    888. M. Dashti Moghaddam & Zhiyuan Liu & R. A. Serota, 2019. "Distribution of Historic Market Data ¨C Implied and Realized Volatility," Applied Economics and Finance, Redfame publishing, vol. 6(5), pages 104-130, September.
    889. Byounghyun Jeon & Sung Won Seo & Jun Sik Kim, 2020. "Uncertainty and the volatility forecasting power of option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1109-1126, July.
    890. Jeroen V.K. Rombouts & Lars Stentoft & Francesco Violante, 2017. "Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability," CREATES Research Papers 2017-10, Department of Economics and Business Economics, Aarhus University.
    891. Bachmair, K., 2023. "The Effects of the LIBOR Scandal on Volatility and Liquidity in LIBOR Futures Markets," Cambridge Working Papers in Economics 2303, Faculty of Economics, University of Cambridge.
    892. Vasyl Golosnoy & Yarema Okhrin, 2015. "Using information quality for volatility model combinations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1055-1073, June.
    893. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    894. Mensi, Walid & Nekhili, Ramzi & Vo, Xuan Vinh & Suleman, Tahir & Kang, Sang Hoon, 2021. "Asymmetric volatility connectedness among U.S. stock sectors," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    895. Behfar, Stefan Kambiz, 2016. "Long memory behavior of returns after intraday financial jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 716-725.
    896. Asger Lunde & Peter Reinhard Hansen, 2004. "Realized Variance and IID Market Microstructure Noise," Econometric Society 2004 North American Summer Meetings 526, Econometric Society.
    897. Giulia Livieri & Maria Elvira Mancino & Stefano Marmi, 2019. "Asymptotic results for the Fourier estimator of the integrated quarticity," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 471-502, December.
    898. Fulvio Corsi & Francesco Audrino, 2007. "Realized Correlation Tick-by-Tick," University of St. Gallen Department of Economics working paper series 2007 2007-02, Department of Economics, University of St. Gallen.
    899. Per Aslak Mykland & Lan Zhang, 2006. "ANOVA for diffusions and It\^{o} processes," Papers math/0611274, arXiv.org.
    900. Smile Dube, 2019. "GARCH Modelling of Conditional Correlations and Volatility of Exchange rates in BRICS Countries," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(1), pages 1-7.
    901. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
    902. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
    903. He, Feng & Ma, Feng & Wang, Ziwei & Yang, Bohan, 2021. "Asymmetric volatility spillover between oil-importing and oil-exporting countries' economic policy uncertainty and China's energy sector," International Review of Financial Analysis, Elsevier, vol. 75(C).
    904. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2020. "Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction," Energy Economics, Elsevier, vol. 92(C).
    905. Konstantinos Gkillas & Christoforos Konstantatos & Costas Siriopoulos, 2021. "Uncertainty Due to Infectious Diseases and Stock–Bond Correlation," Econometrics, MDPI, vol. 9(2), pages 1-18, April.
    906. Bouri, Elie & Iqbal, Najaf & Klein, Tony, 2022. "Climate policy uncertainty and the price dynamics of green and brown energy stocks," Finance Research Letters, Elsevier, vol. 47(PB).
    907. Eric Hillebrand & Marcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
    908. Anke D. Leroux & Vance L. Martin & Kathryn A. St. John, 2022. "Modeling time varying risk of natural resource assets: Implications of climate change," Quantitative Economics, Econometric Society, vol. 13(1), pages 225-257, January.
    909. Hacène Djellout & Arnaud Guillin & Yacouba Samoura, 2017. "Large Deviations Of The Realized (Co-)Volatility Vector," Post-Print hal-01082903, HAL.
    910. Diep Duong & Norman R. Swanson, 2011. "Volatility in Discrete and Continuous Time Models: A Survey with New Evidence on Large and Small Jumps," Departmental Working Papers 201117, Rutgers University, Department of Economics.
    911. Chen, Haiqiang & Gu, Ming & Ni, Bo, 2023. "How price limit affects the market efficiency in a short-sale constrained market? Evidence from a quasi-natural experiment," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 22-39.
    912. Ysusi Carla, 2006. "Estimating Integrated Volatility Using Absolute High-Frequency Returns," Working Papers 2006-13, Banco de México.
    913. Jonathan Haynes & Daniel Schmitt & Lukas Grimm, 2019. "Estimating stochastic volatility: the rough side to equity returns," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 449-469, December.
    914. Kyungsub Lee, 2013. "Probabilistic and statistical properties of moment variations and their use in inference and estimation based on high frequency return data," Papers 1311.5036, arXiv.org, revised Jul 2015.
    915. Peng Wu & Jean-Franc{c}ois Muzy & Emmanuel Bacry, 2022. "From Rough to Multifractal volatility: the log S-fBM model," Papers 2201.09516, arXiv.org, revised Jul 2022.
    916. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.
    917. Loïc Maréchal, 2021. "Do economic variables forecast commodity futures volatility?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1735-1774, November.
    918. Rachid Belfadli & Khalifa Es-Sebaiy & Fatima-Ezzahra Farah, 2023. "Volatility Estimation of Gaussian Ornstein–Uhlenbeck Processes of the Second Kind," Journal of Theoretical Probability, Springer, vol. 36(1), pages 1-17, March.

Articles

  1. Ole E. Barndorff-Nielsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2014. "Integer-valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 693-724, September.
    See citations under working paper version above.
  2. Barndorff-Nielsen, Ole E. & Benth, Fred Espen & Pedersen, Jan & Veraart, Almut E.D., 2014. "On stochastic integration for volatility modulated Lévy-driven Volterra processes," Stochastic Processes and their Applications, Elsevier, vol. 124(1), pages 812-847.

    Cited by:

    1. Almut E. D. Veraart & Luitgard A. M. Veraart, 2013. "Risk premia in energy markets," CREATES Research Papers 2013-02, Department of Economics and Business Economics, Aarhus University.
    2. Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Indirect inference with time series observed with error," CREATES Research Papers 2014-57, Department of Economics and Business Economics, Aarhus University.
    3. Bender, Christian & Knobloch, Robert & Oberacker, Philip, 2015. "A generalised Itō formula for Lévy-driven Volterra processes," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2989-3022.
    4. Mark Podolskij, 2014. "Ambit fields: survey and new challenges," CREATES Research Papers 2014-51, Department of Economics and Business Economics, Aarhus University.
    5. Ole E. Barndorff-Nielsen & Orimar Sauri & Benedykt Szozda, 2017. "Selfdecomposable Fields," Journal of Theoretical Probability, Springer, vol. 30(1), pages 233-267, March.
    6. Mark Podolskij & Nopporn Thamrongrat, 2015. "A weak limit theorem for numerical approximation of Brownian semi-stationary processes," CREATES Research Papers 2015-53, Department of Economics and Business Economics, Aarhus University.
    7. Ole E. Barndorff-Nielsen, 2016. "Assessing Gamma kernels and BSS/LSS processes," CREATES Research Papers 2016-09, Department of Economics and Business Economics, Aarhus University.
    8. Feng, Chengxiao & Tan, Jie & Jiang, Zhenyu & Chen, Shuang, 2020. "A generalized European option pricing model with risk management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

  3. Ole E. Barndorff-Nielsen & David G. Pollard & Neil Shephard, 2012. "Integer-valued L�vy processes and low latency financial econometrics," Quantitative Finance, Taylor & Francis Journals, vol. 12(4), pages 587-605, January.

    Cited by:

    1. Mikkel Bennedsen & Asger Lunde & Neil Shephard & Almut E. D. Veraart, 2021. "Inference and forecasting for continuous-time integer-valued trawl processes," Papers 2107.03674, arXiv.org, revised Feb 2023.
    2. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    3. Jonas Hallgren & Timo Koski, 2016. "Testing for Causality in Continuous Time Bayesian Network Models of High-Frequency Data," Papers 1601.06651, arXiv.org.
    4. Ole E. Barndorff-Nielsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2014. "Integer-valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 693-724, September.
    5. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2015. "Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model," Tinbergen Institute Discussion Papers 15-076/IV/DSF94, Tinbergen Institute.
    6. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised Sep 2023.
    7. Zhang, Huiming & Liu, Yunxiao & Li, Bo, 2014. "Notes on discrete compound Poisson model with applications to risk theory," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 325-336.
    8. Zhanyu Chen & Kai Zhang & Hongbiao Zhao, 2022. "A Skellam market model for loan prime rate options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 525-551, March.
    9. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    10. Paul Doukhan, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 447-450, September.
    11. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    12. Baena-Mirabete, S. & Puig, P., 2020. "Computing probabilities of integer-valued random variables by recurrence relations," Statistics & Probability Letters, Elsevier, vol. 161(C).
    13. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    14. Shota Gugushvili & Ester Mariucci & Frank van der Meulen, 2020. "Decompounding discrete distributions: A nonparametric Bayesian approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(2), pages 464-492, June.
    15. Aknouche, Abdelhakim & Gouveia, Sonia & Scotto, Manuel, 2023. "Random multiplication versus random sum: auto-regressive-like models with integer-valued random inputs," MPRA Paper 119518, University Library of Munich, Germany, revised 18 Dec 2023.
    16. Michael Grabchak, 2022. "Discrete Tempered Stable Distributions," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 1877-1890, September.
    17. Fry, John & Serbera, Jean-Philippe, 2017. "Modelling and mitigation of Flash Crashes," MPRA Paper 82457, University Library of Munich, Germany.
    18. Siem Jan Koopman & Rutger Lit & André Lucas, 2014. "The Dynamic Skellam Model with Applications," Tinbergen Institute Discussion Papers 14-032/IV/DSF73, Tinbergen Institute, revised 06 Jul 2015.
    19. Xiaofei Hu & Beth Andrews, 2021. "Integer‐valued asymmetric garch modeling," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 737-751, September.
    20. Mikkel Bennedsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2021. "Inference and forecasting for continuous-time integer-valued trawl processes and their use in financial economics," CREATES Research Papers 2021-12, Department of Economics and Business Economics, Aarhus University.

  4. Ole E. Barndorff-Nielsen & Almut E. D. Veraart, 2012. "Stochastic Volatility of Volatility and Variance Risk Premia," Journal of Financial Econometrics, Oxford University Press, vol. 11(1), pages 1-46, December.

    Cited by:

    1. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model," CREATES Research Papers 2013-03, Department of Economics and Business Economics, Aarhus University.
    2. Valentin Courgeau & Almut E. D. Veraart, 2022. "Likelihood theory for the graph Ornstein-Uhlenbeck process," Statistical Inference for Stochastic Processes, Springer, vol. 25(2), pages 227-260, July.
    3. Martin Diviš, 2017. "Options valuation included jumps in intervention period [Oceňování opcí se zahrnutím skoků v období intervencí]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2017(3), pages 19-38.
    4. Ding, Y., 2021. "Conditional Heteroskedasticity in the Volatility of Asset Returns," Cambridge Working Papers in Economics 2179, Faculty of Economics, University of Cambridge.
    5. Müller, Janis & Posch, Peter N., 2019. "Consumption volatility ambiguity and risk premium’s time-variation," Finance Research Letters, Elsevier, vol. 29(C), pages 336-339.
    6. Bercu, Bernard & Proïa, Frédéric & Savy, Nicolas, 2014. "On Ornstein–Uhlenbeck driven by Ornstein–Uhlenbeck processes," Statistics & Probability Letters, Elsevier, vol. 85(C), pages 36-44.
    7. Kostopoulos, Dimitrios & Meyer, Steffen & Uhr, Charline, 2020. "Ambiguity and investor behavior," SAFE Working Paper Series 297, Leibniz Institute for Financial Research SAFE.
    8. Xin Zang & Jun Ni & Jing-Zhi Huang & Lan Wu, 2017. "Double-jump diffusion model for VIX: evidence from VVIX," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 227-240, February.
    9. Ding, Y., 2021. "Conditional Heteroskedasticity in the Volatility of Asset Returns," Janeway Institute Working Papers 2111, Faculty of Economics, University of Cambridge.
    10. Cuchiero, Christa & Teichmann, Josef, 2015. "Fourier transform methods for pathwise covariance estimation in the presence of jumps," Stochastic Processes and their Applications, Elsevier, vol. 125(1), pages 116-160.
    11. Li, Wenhui & Ockenfels, Peter & Wilde, Christian, 2021. "The effect of ambiguity on price formation and trading behavior in financial markets," SAFE Working Paper Series 326, Leibniz Institute for Financial Research SAFE.
    12. Ole E. Barndorff-Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2013. "Modelling energy spot prices by volatility modulated L\'{e}vy-driven Volterra processes," Papers 1307.6332, arXiv.org.
    13. Kostopoulos, Dimitrios & Meyer, Steffen & Uhr, Charline, 2022. "Ambiguity about volatility and investor behavior," Journal of Financial Economics, Elsevier, vol. 145(1), pages 277-296.
    14. Giulia Livieri & Maria Elvira Mancino & Stefano Marmi, 2019. "Asymptotic results for the Fourier estimator of the integrated quarticity," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 471-502, December.

  5. Barndorff-Nielsen, Ole E. & Hansen, Peter Reinhard & Lunde, Asger & Shephard, Neil, 2011. "Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Journal of Econometrics, Elsevier, vol. 162(2), pages 149-169, June.
    See citations under working paper version above.
  6. Barndorff-Nielsen, Ole E. & Hansen, Peter Reinhard & Lunde, Asger & Shephard, Neil, 2011. "Subsampling realised kernels," Journal of Econometrics, Elsevier, vol. 160(1), pages 204-219, January.
    See citations under working paper version above.
  7. Barndorff-Nielsen, Ole E. & Corcuera, José Manuel & Podolskij, Mark, 2009. "Power variation for Gaussian processes with stationary increments," Stochastic Processes and their Applications, Elsevier, vol. 119(6), pages 1845-1865, June.
    See citations under working paper version above.
  8. O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 1-32, November.

    Cited by:

    1. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    2. Dette, Holger & Golosnoy, Vasyl & Kellermann, Janosch, 2022. "Correcting Intraday Periodicity Bias in Realized Volatility Measures," Econometrics and Statistics, Elsevier, vol. 23(C), pages 36-52.
    3. Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    4. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    5. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
    6. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    7. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    8. Heejoon Han & Myung D. Park & Shen Zhang, 2015. "A Multiplicative Error Model with Heterogeneous Components for Forecasting Realized Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 209-219, April.
    9. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    10. Huang, Wen & Huang, Zhuo & Matei, Marius & Wang, Tianyi, 2012. "Price Volatility Forecast for Agricultural Commodity Futures： The Role of High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 83-103, December.
    11. Jianqing Fan & Yingying Li & Ke Yu, 2012. "Vast Volatility Matrix Estimation Using High-Frequency Data for Portfolio Selection," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 412-428, March.
    12. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    13. Rasmus Tangsgaard Varneskov, 2011. "Flat-Top Realized Kernel Estimation of Quadratic Covariation with Non-Synchronous and Noisy Asset Prices," CREATES Research Papers 2011-35, Department of Economics and Business Economics, Aarhus University.
    14. Tse, Yiu-Kuen & Dong, Yingjie, 2014. "Intraday periodicity adjustments of transaction duration and their effects on high-frequency volatility estimation," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 352-361.
    15. Xu, Jiawen & Perron, Pierre, 2014. "Forecasting return volatility: Level shifts with varying jump probability and mean reversion," International Journal of Forecasting, Elsevier, vol. 30(3), pages 449-463.
    16. Kim Christensen & Charlotte Christiansen & Anders M. Posselt, 2019. "The Economic Value of VIX ETPs," CREATES Research Papers 2019-14, Department of Economics and Business Economics, Aarhus University.
    17. Vacca, Gianmarco & Zoia, Maria Grazia & Bagnato, Luca, 2022. "Forecasting in GARCH models with polynomially modified innovations," International Journal of Forecasting, Elsevier, vol. 38(1), pages 117-141.
    18. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    19. Ballinari, Daniele & Audrino, Francesco & Sigrist, Fabio, 2022. "When does attention matter? The effect of investor attention on stock market volatility around news releases," International Review of Financial Analysis, Elsevier, vol. 82(C).
    20. Christensen, Kim & Oomen, Roel & Renò, Roberto, 2022. "The drift burst hypothesis," Journal of Econometrics, Elsevier, vol. 227(2), pages 461-497.
    21. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    22. Wang, Fangfang, 2014. "Optimal design of Fourier estimator in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 708-722.
    23. Peter R. Hansen & Asger Lunde & Valeri Voev, 2010. "Realized Beta GARCH: A Multivariate GARCH Model with Realized Measures of Volatility and CoVolatility," CREATES Research Papers 2010-74, Department of Economics and Business Economics, Aarhus University.
    24. Wang, Jiqian & Lu, Xinjie & He, Feng & Ma, Feng, 2020. "Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    25. Heejoon Han & Myung D. Park, 2013. "Comparison of Realized Measure and Implied Volatility in Forecasting Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 522-533, September.
    26. Fleming, Jeff & Paye, Bradley S., 2011. "High-frequency returns, jumps and the mixture of normals hypothesis," Journal of Econometrics, Elsevier, vol. 160(1), pages 119-128, January.
    27. Barbara Będowska-Sójka, 2021. "Is liquidity wasted? The zero-returns on the Warsaw Stock Exchange," Annals of Operations Research, Springer, vol. 297(1), pages 37-51, February.
    28. Ding, Hui & Huang, Yisu & Wang, Jiqian, 2023. "Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    29. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    30. Fangfang Wang, 2016. "An Unbiased Measure of Integrated Volatility in the Frequency Domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 147-164, March.
    31. Peter Reinhard Hansen & Zhuo Huang, 2012. "Exponential GARCH Modeling with Realized Measures of Volatility," CREATES Research Papers 2012-44, Department of Economics and Business Economics, Aarhus University.
    32. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    33. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
    34. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    35. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    36. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    37. Ulrich Hounyo & Silvia Gonçalves & Nour Meddahi, 2016. "Bootstrapping pre-averaged realized volatility under market microstructure noise," CIRANO Working Papers 2016s-25, CIRANO.
    38. Dovonon, Prosper & Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping high-frequency jump tests," IDEI Working Papers 870, Institut d'Économie Industrielle (IDEI), Toulouse.
    39. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    40. Bollerslev, Tim & Patton, Andrew J. & Zhang, Haozhe, 2022. "Equity clusters through the lens of realized semicorrelations," Economics Letters, Elsevier, vol. 211(C).
    41. Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
    42. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    43. Li, Jia & Todorov, Viktor & Tauchen, George & Chen, Rui, 2017. "Mixed-scale jump regressions with bootstrap inference," Journal of Econometrics, Elsevier, vol. 201(2), pages 417-432.
    44. Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    45. Laurent Ferrara & Clément Marsilli & Juan-Pablo Ortega, 2014. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Post-Print hal-01385941, HAL.
    46. Kim Christensen & Roel Oomen & Mark Podolskij, 2011. "Fact or friction: Jumps at ultra high frequency," CREATES Research Papers 2011-19, Department of Economics and Business Economics, Aarhus University.
    47. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    48. Yuta Koike, 2014. "An estimator for the cumulative co-volatility of asynchronously observed semimartingales with jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 460-481, June.
    49. Winkelmann, Lars & Yao, Wenying, 2021. "Tests for jumps in yield spreads," Discussion Papers 2021/15, Free University Berlin, School of Business & Economics.
    50. Tim Bollerslev & Jia Li & Yuan Xue, 2016. "Volume, Volatility and Public News Announcements," CREATES Research Papers 2016-19, Department of Economics and Business Economics, Aarhus University.
    51. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    52. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2016. "Decoupling the short- and long-term behavior of stochastic volatility," Papers 1610.00332, arXiv.org, revised Jan 2021.
    53. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," Papers 1608.01895, arXiv.org, revised Mar 2018.
    54. Besma Hkiri & Juncal Cunado & Mehmet Balcilar & Rangan Gupta, 2019. "Time-Varying Relationship between Conventional and Unconventional Monetary Policies and Risk Aversion: International Evidence from Time- and Frequency-Domains," Working Papers 201965, University of Pretoria, Department of Economics.
    55. Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(11), pages 1141-1152, November.
    56. Roxana Halbleib & Valeri Voev, 2012. "Forecasting Covariance Matrices: A Mixed Frequency Approach," Working Paper Series of the Department of Economics, University of Konstanz 2012-30, Department of Economics, University of Konstanz.
    57. Varneskov, Rasmus & Voev, Valeri, 2013. "The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 83-95.
    58. Ilya Archakov & Peter Reinhard Hansen & Asger Lunde, 2020. "A Multivariate Realized GARCH Model," Papers 2012.02708, arXiv.org.
    59. Yu‐Sheng Lai, 2019. "Flexible covariance dynamics, high‐frequency data, and optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1529-1548, December.
    60. Jacod, Jean & Klüppelberg, Claudia & Müller, Gernot, 2017. "Testing for non-correlation between price and volatility jumps," Journal of Econometrics, Elsevier, vol. 197(2), pages 284-297.
    61. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2014. "Is Volatility Clustering of Asset Returns Asymmetric?," Working Papers 050, Ryerson University, Department of Economics.
    62. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    63. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    64. Hansen, Peter R. & Lunde, Asger, 2014. "Estimating The Persistence And The Autocorrelation Function Of A Time Series That Is Measured With Error," Econometric Theory, Cambridge University Press, vol. 30(1), pages 60-93, February.
    65. Julien Chevallier & Benoît Sévi, 2012. "On the Stochastic Properties of Carbon Futures Prices," Working Papers halshs-00720166, HAL.
    66. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    67. Jiang, George J. & Zhu, Kevin X., 2017. "Information Shocks and Short-Term Market Underreaction," Journal of Financial Economics, Elsevier, vol. 124(1), pages 43-64.
    68. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
    69. Bannouh, Karim & Martens, Martin & van Dijk, Dick, 2013. "Forecasting volatility with the realized range in the presence of noise and non-trading," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 535-551.
    70. Ole E. Barndorff-Nielsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2014. "Integer-valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 693-724, September.
    71. De Lira Salvatierra, Irving & Patton, Andrew J., 2015. "Dynamic copula models and high frequency data," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 120-135.
    72. Kevin Sheppard & Wen Xu, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    73. Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2013. "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns," CREATES Research Papers 2013-07, Department of Economics and Business Economics, Aarhus University.
    74. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Economics Papers 2008-W10, Economics Group, Nuffield College, University of Oxford.
    75. Chao Liang & Yongan Xu & Zhonglu Chen & Xiafei Li, 2023. "Forecasting China's stock market volatility with shrinkage method: Can Adaptive Lasso select stronger predictors from numerous predictors?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3689-3699, October.
    76. Hollstein, Fabian & Wese Simen, Chardin, 2020. "Variance risk: A bird’s eye view," Journal of Econometrics, Elsevier, vol. 215(2), pages 517-535.
    77. Manh Cuong Dong & Cathy W. S. Chen & Manabu Asai, 2023. "Bayesian non‐linear quantile effects on modelling realized kernels," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 981-995, January.
    78. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    79. Moawia Alghalith & Christos Floros & Konstantinos Gkillas, 2020. "Estimating Stochastic Volatility under the Assumption of Stochastic Volatility of Volatility," Risks, MDPI, vol. 8(2), pages 1-15, April.
    80. Leopoldo Catania & Mads Sandholdt, 2019. "Bitcoin at High Frequency," JRFM, MDPI, vol. 12(1), pages 1-20, February.
    81. Kevin Sheppard & Wen Xu, 2019. "Factor High-Frequency-Based Volatility (HEAVY) Models," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 33-65.
    82. Tomáš Plíhal, 2021. "Scheduled macroeconomic news announcements and Forex volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1379-1397, December.
    83. Shuping Shi & Jun Yu, 2023. "Volatility Puzzle: Long Memory or Antipersistency," Management Science, INFORMS, vol. 69(7), pages 3861-3883, July.
    84. Tianlun Fei & Xiaoquan Liu & Conghua Wen, 2023. "Forecasting stock return volatility: Realized volatility‐type or duration‐based estimators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1594-1621, November.
    85. Jim Griffin & Jia Liu & John M. Maheu, 2021. "Bayesian Nonparametric Estimation of Ex Post Variance [Out of Sample Forecasts of Quadratic Variation]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 823-859.
    86. Apostolos Kourtis & Raphael N. Markellos & Lazaros Symeonidis, 2016. "An International Comparison of Implied, Realized, and GARCH Volatility Forecasts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(12), pages 1164-1193, December.
    87. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    88. Martin Tegnér & Rolf Poulsen, 2018. "Volatility Is Log-Normal—But Not for the Reason You Think," Risks, MDPI, vol. 6(2), pages 1-16, April.
    89. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    90. Markus Bibinger & Christopher J. Neely & Lars Winkelmann, 2017. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," Working Papers 2017-12, Federal Reserve Bank of St. Louis.
    91. Johanna F. Ziegel & Fabian Kruger & Alexander Jordan & Fernando Fasciati, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Papers 1705.04537, arXiv.org.
    92. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    93. Markus Bibinger & Nikolaus Hautsch & Peter Malec & Markus Reiss, 2014. "Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence," Cambridge Working Papers in Economics 1464, Faculty of Economics, University of Cambridge.
    94. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
    95. Lilian de Menezes & Marianna Russo & Giovanni Urga, 2016. "Identifying Drivers of Liquidity in the NBP Month-ahead Market," EcoMod2016 9570, EcoMod.
    96. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    97. Nikolaus Hautsch & Stefan Voigt, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty," Papers 1709.06296, arXiv.org, revised Jun 2018.
    98. Roger Buckland & Julian Williams & Janice Beecher, 2015. "Risk and regulation in water utilities: a cross-country comparison of evidence from the CAPM," Journal of Regulatory Economics, Springer, vol. 47(2), pages 117-145, April.
    99. Becker, Janis & Leschinski, Christian & Sibbertsen, Philipp, 2019. "Robust Multivariate Local Whittle Estimation and Spurious Fractional Cointegration," Hannover Economic Papers (HEP) dp-660, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    100. Dräger, Lena & Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The Long Memory of Equity Volatility and the Macroeconomy: International Evidence," Hannover Economic Papers (HEP) dp-667, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    101. George Kapetanios & Michael Neumann & George Skiadopoulos, 2014. "Jumps in Option Prices and Their Determinants: Real-time Evidence from the E-mini S&P 500 Option Market," Working Papers 730, Queen Mary University of London, School of Economics and Finance.
    102. David Ardia & Cl'ement Aymard & Tolga Cenesizoglu, 2023. "Fast and Furious: A High-Frequency Analysis of Robinhood Users' Trading Behavior," Papers 2307.11012, arXiv.org.
    103. Marius Matei & Xari Rovira & Núria Agell, 2019. "Bivariate Volatility Modeling with High-Frequency Data," Econometrics, MDPI, vol. 7(3), pages 1-15, September.
    104. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Long Memory of Equity Volatility: International Evidence," Hannover Economic Papers (HEP) dp-614, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    105. Chao Liang & Yan Li & Feng Ma & Yaojie Zhang, 2022. "Forecasting international equity market volatility: A new approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1433-1457, November.
    106. Zhang, Chuanhai & Ma, Huan & Liao, Xiaosai, 2023. "Futures trading activity and the jump risk of spot market: Evidence from the bitcoin market," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    107. Gianluca De Nard & Robert F. Engle & Olivier Ledoit & Michael Wolf, 2020. "Large dynamic covariance matrices: enhancements based on intraday data," ECON - Working Papers 356, Department of Economics - University of Zurich, revised Jan 2022.
    108. Będowska-Sójka, Barbara, 2020. "Do aggressive orders affect liquidity? An evidence from an emerging market," Research in International Business and Finance, Elsevier, vol. 54(C).
    109. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
    110. Gustavo Fruet Dias & Cristina M. Scherrer & Fotis Papailias, 2016. "Volatility Discovery," CREATES Research Papers 2016-07, Department of Economics and Business Economics, Aarhus University.
    111. Będowska-Sójka, Barbara & Echaust, Krzysztof, 2020. "What is the best proxy for liquidity in the presence of extreme illiquidity?," Emerging Markets Review, Elsevier, vol. 43(C).
    112. Bekierman, Jeremias & Manner, Hans, 2018. "Forecasting realized variance measures using time-varying coefficient models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 276-287.
    113. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
    114. Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 94289, University Library of Munich, Germany.
    115. Linton, Oliver & Whang, Yoon-Jae & Yen, Yu-Min, 2016. "A nonparametric test of a strong leverage hypothesis," Journal of Econometrics, Elsevier, vol. 194(1), pages 153-186.
    116. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised Sep 2023.
    117. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
    118. Ilze Kalnina, 2023. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 538-549, April.
    119. Vica Tendenan & Richard Gerlach & Chao Wang, 2020. "Tail risk forecasting using Bayesian realized EGARCH models," Papers 2008.05147, arXiv.org, revised Aug 2020.
    120. Filimonov, Vladimir & Sornette, Didier, 2015. "Power law scaling and “Dragon-Kings” in distributions of intraday financial drawdowns," Chaos, Solitons & Fractals, Elsevier, vol. 74(C), pages 27-45.
    121. Hiroyuki Kawakatsu, 2021. "Information in daily data volatility measurements," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1642-1656, April.
    122. Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024. "Doubly multiplicative error models with long- and short-run components," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    123. Andre Lucas & Anne Opschoor & Luca Rossini, 2021. "Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution," Tinbergen Institute Discussion Papers 21-010/III, Tinbergen Institute, revised 11 Jul 2023.
    124. Guido Russi, 2012. "Estimating the Leverage Effect Using High Frequency Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 1-24, February.
    125. Bahcivan, Hulusi & Karahan, Cenk C., 2022. "High frequency correlation dynamics and day-of-the-week effect: A score-driven approach in an emerging market stock exchange," International Review of Financial Analysis, Elsevier, vol. 80(C).
    126. Gustavo F. Dias & Marcelo Fernandes & Cristina M. Scherrer, 2021. "Price Discovery in a Continuous-Time Setting [Price Discovery and Common Factor Models]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 985-1008.
    127. Charles S. Bos & Pawel Janus, 2013. "A Quantile-based Realized Measure of Variation: New Tests for Outlying Observations in Financial Data," Tinbergen Institute Discussion Papers 13-155/III, Tinbergen Institute.
    128. Gkillas, Konstantinos & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2022. "Spillovers in Higher-Order Moments of Crude Oil, Gold, and Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 398-406.
    129. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    130. Alexander Koch & Toan Luu Duc Huynh & Mei Wang, 2024. "News sentiment and international equity markets during BREXIT period: A textual and connectedness analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 5-34, January.
    131. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    132. Chao Liang & Yi Zhang & Yaojie Zhang, 2022. "Forecasting the volatility of the German stock market: New evidence," Applied Economics, Taylor & Francis Journals, vol. 54(9), pages 1055-1070, February.
    133. Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022. "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, vol. 28(C).
    134. Ranjan R. Chakravarty & Sudhanshu Pani, 2021. "A Data Paradigm to Operationalise Expanded Filtration: Realized Volatilities and Kernels from Non-Synchronous NASDAQ Quotes and Trades," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 617-652, December.
    135. Dimpfl, Thomas & Schweikert, Karsten, 2023. "Information shares for markets with partially overlapping trading hours," Journal of Banking & Finance, Elsevier, vol. 154(C).
    136. Becker, Janis & Leschinski, Christian, 2018. "Estimating the Volatility of Asset Pricing Factors," Hannover Economic Papers (HEP) dp-631, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    137. Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
    138. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.
    139. Heejoon Han, 2016. "Quantile Dependence between Stock Markets and its Application in Volatility Forecasting," Papers 1608.07193, arXiv.org.
    140. Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2012. "Jump robust daily covariance estimation by disentangling variance and correlation components," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 2993-3005.
    141. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    142. Zhang, Chuanhai & Liu, Zhi & Liu, Qiang, 2021. "Jumps at ultra-high frequency: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    143. Mishra Anuj & Ramanathan Thekke Variyam, 2017. "Nonstationary autoregressive conditional duration models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-22, September.
    144. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.
    145. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018.
    146. Li, Zeming & Sakkas, Athanasios & Urquhart, Andrew, 2022. "Intraday time series momentum: Global evidence and links to market characteristics," Journal of Financial Markets, Elsevier, vol. 57(C).
    147. Markus Bibinger & Markus Reiss & Nikolaus Hautsch & Peter Malec, 2014. "Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence," SFB 649 Discussion Papers SFB649DP2014-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    148. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.
    149. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
    150. Liu, Keyan & Zhou, Jianan & Dong, Dayong, 2021. "Improving stock price prediction using the long short-term memory model combined with online social networks," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    151. Peter Reinhard Hansen & Zhuo (Albert) Huang & Howard Howan Shek, "undated". "Realized GARCH: A Complete Model of Returns and Realized Measures of Volatility," CREATES Research Papers 2010-13, Department of Economics and Business Economics, Aarhus University.
    152. Ingmar Nolte & Valeri Voev, 2011. "Least Squares Inference on Integrated Volatility and the Relationship Between Efficient Prices and Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 94-108, April.
    153. Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.
    154. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    155. Grønborg, Niels S. & Lunde, Asger & Olesen, Kasper V. & Vander Elst, Harry, 2022. "Realizing correlations across asset classes," Journal of Financial Markets, Elsevier, vol. 59(PA).
    156. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2012. "A nonparametric test of the leverage hypothesis," CeMMAP working papers CWP24/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    157. Hounyo, Ulrich & Varneskov, Rasmus T., 2020. "Inference for local distributions at high sampling frequencies: A bootstrap approach," Journal of Econometrics, Elsevier, vol. 215(1), pages 1-34.
    158. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    159. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Memory of Stock Return Volatility: Asset Pricing Implications," Hannover Economic Papers (HEP) dp-613, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    160. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    161. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, vol. 21(3), pages 915-958.
    162. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    163. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2012. "A nonparametric test of the leverage hypothesis," CeMMAP working papers 24/12, Institute for Fiscal Studies.
    164. Wei Lin & Gloria González‐Rivera, 2019. "Extreme returns and intensity of trading," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1121-1140, November.
    165. Dong Hwan Oh & Andrew J. Patton, 2015. "High-Dimensional Copula-Based Distributions with Mixed Frequency Data," Finance and Economics Discussion Series 2015-50, Board of Governors of the Federal Reserve System (U.S.).
    166. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    167. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    168. Adrian Fernandez‐Perez & Bart Frijns & Ilnara Gafiatullina & Alireza Tourani‐Rad, 2018. "Determinants of intraday price discovery in VIX exchange traded notes," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(5), pages 535-548, May.
    169. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Wang, Jianqiong, 2020. "Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models," Energy, Elsevier, vol. 212(C).
    170. Fengler, M.R. & Mammen, E. & Vogt, M., 2015. "Specification and structural break tests for additive models with applications to realized variance data," Journal of Econometrics, Elsevier, vol. 188(1), pages 196-218.
    171. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
    172. Yu‐Sheng Lai, 2018. "Estimation of the optimal futures hedge ratio for equity index portfolios using a realized beta generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1370-1390, November.
    173. Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
    174. Kirill Dragun & Kris Boudt & Orimar Sauri & Steven Vanduffel, 2021. "Beta-Adjusted Covariance Estimation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1010, Ghent University, Faculty of Economics and Business Administration.
    175. Sutton, Maxwell & Vasnev, Andrey L. & Gerlach, Richard, 2019. "Mixed interval realized variance: A robust estimator of stock price volatility," Econometrics and Statistics, Elsevier, vol. 11(C), pages 43-62.
    176. Bodilsen, Simon & Eriksen, Jonas N. & Grønborg, Niels S., 2021. "Asset pricing and FOMC press conferences," Journal of Banking & Finance, Elsevier, vol. 128(C).
    177. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
    178. Zhang, Chuanhai & Zhang, Zhengjun & Xu, Mengyu & Peng, Zhe, 2023. "Good and bad self-excitation: Asymmetric self-exciting jumps in Bitcoin returns," Economic Modelling, Elsevier, vol. 119(C).
    179. Giorgio Mirone, 2017. "Inference from the futures: ranking the noise cancelling accuracy of realized measures," CREATES Research Papers 2017-24, Department of Economics and Business Economics, Aarhus University.
    180. Giorgio Mirone, 2018. "Cross-sectional noise reduction and more efficient estimation of Integrated Variance," CREATES Research Papers 2018-18, Department of Economics and Business Economics, Aarhus University.
    181. Enilov, Martin & Mensi, Walid & Stankov, Petar, 2023. "Does safe haven exist? Tail risks of commodity markets during COVID-19 pandemic," Journal of Commodity Markets, Elsevier, vol. 29(C).
    182. Ulrich Hounyo, 2013. "Bootstrapping realized volatility and realized beta under a local Gaussianity assumption," CREATES Research Papers 2013-30, Department of Economics and Business Economics, Aarhus University.
    183. Bollerslev, Tim & Li, Sophia Zhengzi & Todorov, Viktor, 2016. "Roughing up beta: Continuous versus discontinuous betas and the cross section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 120(3), pages 464-490.
    184. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "The Memory of Volatility," Hannover Economic Papers (HEP) dp-601, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    185. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2011. "A Functional Filtering and Neighborhood Truncation Approach to Integrated Quarticity Estimation," NBER Working Papers 17152, National Bureau of Economic Research, Inc.
    186. Robert F. Engle & Martin Klint Hansen & Asger Lunde, 2012. "And Now, The Rest of the News: Volatility and Firm Specific News Arrival," CREATES Research Papers 2012-56, Department of Economics and Business Economics, Aarhus University.
    187. Behrendt, Simon & Schweikert, Karsten, 2021. "A Note on Adaptive Group Lasso for Structural Break Time Series," Econometrics and Statistics, Elsevier, vol. 17(C), pages 156-172.
    188. Wang, Chengyang & Nishiyama, Yoshihiko, 2015. "Volatility forecast of stock indices by model averaging using high-frequency data," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 324-337.
    189. Gianluca Cubadda & Alain Hecq & Antonio Riccardo, 2018. "Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector," CEIS Research Paper 445, Tor Vergata University, CEIS, revised 30 Oct 2018.
    190. Heejoon Han & Shen Zhang, 2012. "Non‐stationary non‐parametric volatility model," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 204-225, June.
    191. Noss, Joseph & Pedace, Lucas & Tobek, Ondrej & Linton, Oliver & Crowley-Reidy, Liam, 2017. "The October 2016 sterling flash episode: when liquidity disappeared from one of the world’s most liquid markets," Bank of England working papers 687, Bank of England.
    192. Likun Lei & Yaojie Zhang & Yu Wei & Yi Zhang, 2021. "Forecasting the volatility of Chinese stock market: An international volatility index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1336-1350, January.
    193. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2021. "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Discussion paper series HIAS-E-104, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    194. Alemany, Nuria & Aragó, Vicent & Salvador, Enrique, 2020. "The distribution of index futures realised volatility under seasonality and microstructure noise," Economic Modelling, Elsevier, vol. 93(C), pages 398-414.
    195. Johnson, James A. & Medeiros, Marcelo C. & Paye, Bradley S., 2022. "Jumps in stock prices: New insights from old data," Journal of Financial Markets, Elsevier, vol. 60(C).
    196. Gkillas Konstantinos & Gupta Rangan & Vortelinos Dimitrios I., 2023. "Uncertainty and realized jumps in the pound-dollar exchange rate: evidence from over one century of data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(1), pages 25-47, February.
    197. Gu, Tiantian & Venkateswaran, Anand & Erath, Marc, 2023. "Impact of fiscal stimulus on volatility: A cross-country analysis," Research in International Business and Finance, Elsevier, vol. 65(C).
    198. Denisa Georgiana Banulescu & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2013. "High-Frequency Risk Measures," Working Papers halshs-00859456, HAL.
    199. Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
    200. Nabil Bouamara & Kris Boudt & S'ebastien Laurent & Christopher J. Neely, 2023. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Papers 2309.15705, arXiv.org.
    201. Bian, Siyu & Serra, Teresa & Garcia, Philip & Irwin, Scott, 2022. "New evidence on market response to public announcements in the presence of microstructure noise," European Journal of Operational Research, Elsevier, vol. 298(2), pages 785-800.
    202. Anzarut, Michelle & Mena, Ramsés H., 2019. "A Harris process to model stochastic volatility," Econometrics and Statistics, Elsevier, vol. 10(C), pages 151-169.
    203. Vladimír Holý & Petra Tomanová, 2023. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 463-485, June.
    204. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    205. Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.
    206. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    207. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," CREATES Research Papers 2016-21, Department of Economics and Business Economics, Aarhus University.
    208. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    209. Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
    210. Walid Abass Mohammed, 2021. "Volatility Spillovers among Developed and Developing Countries: The Global Foreign Exchange Markets," JRFM, MDPI, vol. 14(6), pages 1-30, June.
    211. Zhang, Hanyu & Dufour, Alfonso, 2019. "Modeling intraday volatility of European bond markets: A data filtering application," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 131-146.
    212. Chiranjit Dutta & Nalini Ravishanker & Sumanta Basu, 2022. "Modeling Multivariate Positive-Valued Time Series Using R-INLA," Papers 2206.05374, arXiv.org, revised Jul 2022.
    213. Jan Novotný & Giovanni Urga, 2018. "Testing for Co-jumps in Financial Markets," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 118-128.
    214. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    215. Qiang Liu & Zhi Liu & Chuanhai Zhang, 2020. "Heteroscedasticity test of high-frequency data with jumps and microstructure noise," Papers 2010.07659, arXiv.org.
    216. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    217. Fengler, Matthias R. & Mammen, Enno & Vogt, Michael, 2013. "Additive modeling of realized variance: tests for parametric specifications and structural breaks," Economics Working Paper Series 1332, University of St. Gallen, School of Economics and Political Science.
    218. Wong, Patrick, 2023. "Explaining intraday crude oil returns with higher order risk-neutral moments," Journal of Commodity Markets, Elsevier, vol. 31(C).
    219. Pierre Bajgrowicz & Olivier Scaillet & Adrien Treccani, 2016. "Jumps in High-Frequency Data: Spurious Detections, Dynamics, and News," Management Science, INFORMS, vol. 62(8), pages 2198-2217, August.
    220. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    221. Gustavo Fruet Dias & Marcelo Fernandes & Cristina M. Scherrer, 2016. "Component shares in continuous time," CREATES Research Papers 2016-25, Department of Economics and Business Economics, Aarhus University.
    222. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    223. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    224. Greeshma Balabhadra & El Mehdi Ainasse & Pawel Polak, 2023. "High-Frequency Volatility Estimation with Fast Multiple Change Points Detection," Papers 2303.10550, arXiv.org, revised Mar 2023.
    225. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    226. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    227. H. Rangika Iroshani Peiris & Chao Wang & Richard Gerlach & Minh-Ngoc Tran, 2024. "Semi-parametric financial risk forecasting incorporating multiple realized measures," Papers 2402.09985, arXiv.org.
    228. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    229. Nabil Bouamara & S'ebastien Laurent & Shuping Shi, 2023. "Sequential Cauchy Combination Test for Multiple Testing Problems with Financial Applications," Papers 2303.13406, arXiv.org, revised Jun 2023.
    230. Ahmed, Shamima & Alshater, Muneer M. & Ammari, Anis El & Hammami, Helmi, 2022. "Artificial intelligence and machine learning in finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 61(C).
    231. Prateek Sharma & Swati Sharma, 2015. "Forecasting gains of robust realized variance estimators: evidence from European stock markets," Economics Bulletin, AccessEcon, vol. 35(1), pages 61-69.
    232. Jiang, Hao & Li, Sophia Zhengzi & Wang, Hao, 2021. "Pervasive underreaction: Evidence from high-frequency data," Journal of Financial Economics, Elsevier, vol. 141(2), pages 573-599.
    233. Frömmel, Michael & Han, Xing & Kratochvil, Stepan, 2014. "Modeling the daily electricity price volatility with realized measures," Energy Economics, Elsevier, vol. 44(C), pages 492-502.
    234. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    235. Jonathan Chassot & Michael Creel, 2023. "Constructing Efficient Simulated Moments Using Temporal Convolutional Networks," Working Papers 1412, Barcelona School of Economics.
    236. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    237. Rasika Yatigammana & Shelton Peiris & Richard Gerlach & David Edmund Allen, 2018. "Modelling and Forecasting Stock Price Movements with Serially Dependent Determinants," Risks, MDPI, vol. 6(2), pages 1-22, May.
    238. Adamantios Ntakaris & Giorgio Mirone & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Feature Engineering for Mid-Price Prediction with Deep Learning," Papers 1904.05384, arXiv.org, revised Jun 2019.
    239. Chen, Cathy W.S. & Watanabe, Toshiaki & Lin, Edward M.H., 2023. "Bayesian estimation of realized GARCH-type models with application to financial tail risk management," Econometrics and Statistics, Elsevier, vol. 28(C), pages 30-46.
    240. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    241. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    242. Yang, Ke & Tian, Fengping & Chen, Langnan & Li, Steven, 2017. "Realized volatility forecast of agricultural futures using the HAR models with bagging and combination approaches," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 276-291.
    243. Yu‐Sheng Lai, 2021. "Generalized autoregressive score model with high‐frequency data for optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 2023-2045, December.
    244. Lam, Clifford & Feng, Phoenix, 2018. "A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data," LSE Research Online Documents on Economics 88375, London School of Economics and Political Science, LSE Library.
    245. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    246. Christina Sklibosios Nikitopoulos & Alice Carole Thomas & Jianxin Wang, 2024. "Hedging pressure and oil volatility: Insurance versus liquidity demands," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 252-280, February.
    247. Song, Junmo & Baek, Changryong, 2019. "Detecting structural breaks in realized volatility," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 58-75.
    248. Lam, Clifford & Feng, Phoenix, 2018. "A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data," Journal of Econometrics, Elsevier, vol. 206(1), pages 226-257.
    249. Maria Elvira Mancino & Maria Cristina Recchioni, 2015. "Fourier Spot Volatility Estimator: Asymptotic Normality and Efficiency with Liquid and Illiquid High-Frequency Data," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-33, September.
    250. Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
    251. Qinkai Chen & Christian-Yann Robert, 2021. "Multivariate Realized Volatility Forecasting with Graph Neural Network," Papers 2112.09015, arXiv.org, revised Dec 2021.
    252. Keren Shen & Jianfeng Yao & Wai Keung Li, 2016. "On the Surprising Explanatory Power of Higher Realized Moments in Practice," Papers 1604.07969, arXiv.org.
    253. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    254. Nima Nonejad, 2013. "A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory," CREATES Research Papers 2013-24, Department of Economics and Business Economics, Aarhus University.
    255. Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020. "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 1-12.
    256. Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
    257. Jian Zhou, 2017. "Forecasting REIT volatility with high-frequency data: a comparison of alternative methods," Applied Economics, Taylor & Francis Journals, vol. 49(26), pages 2590-2605, June.
    258. Ikeda, Shin S., 2016. "A bias-corrected estimator of the covariation matrix of multiple security prices when both microstructure effects and sampling durations are persistent and endogenous," Journal of Econometrics, Elsevier, vol. 193(1), pages 203-214.
    259. Curato, Imma Valentina & Mancino, Maria Elvira & Recchioni, Maria Cristina, 2018. "Spot volatility estimation using the Laplace transform," Econometrics and Statistics, Elsevier, vol. 6(C), pages 22-43.
    260. Dias, Gustavo Fruet & Fernandes, Marcelo & Scherrer, Cristina Mabel, 2017. "Improving on daily measures of price discovery," Textos para discussão 444, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    261. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    262. Mohammad Jahan-Parvar & Filip Zikes, 2019. "When do low-frequency measures really measure transaction costs?," Finance and Economics Discussion Series 2019-051, Board of Governors of the Federal Reserve System (U.S.).
    263. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    264. Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
    265. Qiao, Gaoxiu & Jiang, Gongyue & Yang, Jiyu, 2022. "VIX term structure forecasting: New evidence based on the realized semi-variances," International Review of Financial Analysis, Elsevier, vol. 82(C).
    266. Juho Kanniainen & Ye Yue, 2019. "The Arrival of News and Return Jumps in Stock Markets: A Nonparametric Approach," Papers 1901.02691, arXiv.org.
    267. Siem Jan Koopman & Rutger Lit & André Lucas, 2014. "The Dynamic Skellam Model with Applications," Tinbergen Institute Discussion Papers 14-032/IV/DSF73, Tinbergen Institute, revised 06 Jul 2015.
    268. Bugge, Sebastian A. & Guttormsen, Haakon J. & Molnár, Peter & Ringdal, Martin, 2016. "Implied volatility index for the Norwegian equity market," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 133-141.
    269. Rennekamp, Kristina M. & Sethuraman, Mani & Steenhoven, Blake A., 2022. "Engagement in earnings conference calls," Journal of Accounting and Economics, Elsevier, vol. 74(1).
    270. Su, Fei & Zhang, Jingjing, 2018. "Global price discovery in the Australian dollar market and its determinants," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 35-55.
    271. Xinyue He & Teresa Serra, 2022. "Are price limits cooling off agricultural futures markets?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(5), pages 1724-1746, October.
    272. Vladimir Filimonov & Didier Sornette, 2014. "Power law scaling and "Dragon-Kings" in distributions of intraday financial drawdowns," Papers 1407.5037, arXiv.org, revised Apr 2015.
    273. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
    274. Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017. "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, vol. 67(C), pages 136-145.
    275. Konstantinos Gkillas & Christoforos Konstantatos & Costas Siriopoulos, 2021. "Uncertainty Due to Infectious Diseases and Stock–Bond Correlation," Econometrics, MDPI, vol. 9(2), pages 1-18, April.
    276. Yu‐Sheng Lai, 2023. "Optimal futures hedging by using realized semicovariances: The information contained in signed high‐frequency returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(5), pages 677-701, May.
    277. Vladim'ir Hol'y & Petra Tomanov'a, 2018. "Estimation of Ornstein-Uhlenbeck Process Using Ultra-High-Frequency Data with Application to Intraday Pairs Trading Strategy," Papers 1811.09312, arXiv.org, revised Jul 2022.
    278. Jonathan Haynes & Daniel Schmitt & Lukas Grimm, 2019. "Estimating stochastic volatility: the rough side to equity returns," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 449-469, December.
    279. Plíhal, Tomáš & Lyócsa, Štefan, 2021. "Modeling realized volatility of the EUR/USD exchange rate: Does implied volatility really matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 811-829.
    280. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.

  9. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise," Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
    See citations under working paper version above.
  10. Ole E. Barndorff‐Nielsen, 2007. "Random Graph Dynamics by Rick Durrett," International Statistical Review, International Statistical Institute, vol. 75(3), pages 428-428, December.

    Cited by:

    1. Shriram Ashok Kumar & Maliha Tasnim & Zohvin Singh Basnyat & Faezeh Karimi & Kaveh Khalilpour, 2022. "Resilience Analysis of Australian Electricity and Gas Transmission Networks," Sustainability, MDPI, vol. 14(6), pages 1-20, March.

  11. Ole E. Barndorff‐Nielsen & Alexander M. Lindner, 2007. "Lévy Copulas: Dynamics and Transforms of Upsilon Type," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(2), pages 298-316, June.

    Cited by:

    1. Esmaeili, Habib & Klüppelberg, Claudia, 2011. "Parametric estimation of a bivariate stable Lévy process," Journal of Multivariate Analysis, Elsevier, vol. 102(5), pages 918-930, May.
    2. Barndorff-Nielsen, Ole E. & Maejima, Makoto, 2008. "Semigroups of Upsilon transformations," Stochastic Processes and their Applications, Elsevier, vol. 118(12), pages 2334-2343, December.

  12. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 1-30.
    See citations under working paper version above.
  13. Barndorff-Nielsen, Ole E. & Graversen, Svend Erik & Jacod, Jean & Shephard, Neil, 2006. "Limit Theorems For Bipower Variation In Financial Econometrics," Econometric Theory, Cambridge University Press, vol. 22(4), pages 677-719, August.
    See citations under working paper version above.
  14. Ole E. Barndorff-Nielsen & Makoto Maejima & Ken-iti Sato, 2006. "Infinite Divisibility for Stochastic Processes and Time Change," Journal of Theoretical Probability, Springer, vol. 19(2), pages 411-446, June.

    Cited by:

    1. Michele Azzone & Roberto Baviera, 2023. "Is (independent) subordination relevant in option pricing?," Papers 2307.08628, arXiv.org, revised Oct 2023.
    2. Shai Covo, 2011. "Two-Parameter Lévy Processes Along Decreasing Paths," Journal of Theoretical Probability, Springer, vol. 24(1), pages 150-169, March.
    3. Ole E. Barndorff-Nielsen & Orimar Sauri & Benedykt Szozda, 2017. "Selfdecomposable Fields," Journal of Theoretical Probability, Springer, vol. 30(1), pages 233-267, March.

  15. Barndorff-Nielsen, Ole E. & Shephard, Neil, 2006. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 217-252.
    See citations under working paper version above.
  16. Barndorff-Nielsen, Ole E. & Thorbjørnsen, Steen, 2006. "Regularizing mappings of Lévy measures," Stochastic Processes and their Applications, Elsevier, vol. 116(3), pages 423-446, March.

    Cited by:

    1. Barndorff-Nielsen, Ole E. & Maejima, Makoto, 2008. "Semigroups of Upsilon transformations," Stochastic Processes and their Applications, Elsevier, vol. 118(12), pages 2334-2343, December.

  17. Barndorff-Nielsen, Ole E. & Shephard, Neil & Winkel, Matthias, 2006. "Limit theorems for multipower variation in the presence of jumps," Stochastic Processes and their Applications, Elsevier, vol. 116(5), pages 796-806, May.
    See citations under working paper version above.
  18. Ole Eiler Barndorff‐Nielsen & Robert Stelzer, 2005. "Absolute Moments of Generalized Hyperbolic Distributions and Approximate Scaling of Normal Inverse Gaussian Lévy Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(4), pages 617-637, December.

    Cited by:

    1. Alexeev Vitali & Ignatieva Katja & Liyanage Thusitha, 2021. "Dependence Modelling in Insurance via Copulas with Skewed Generalised Hyperbolic Marginals," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
    2. Scott, David J & Würtz, Diethelm & Dong, Christine & Tran, Thanh Tam, 2009. "Moments of the generalized hyperbolic distribution," MPRA Paper 19081, University Library of Munich, Germany.
    3. Andreas Behr, Ulrich Pötter, "undated". "Downward Wage Rigidity in Europe: A New Flexible Parametric Approach and Empirical Results," Working Papers 201159, Institute of Spatial and Housing Economics, Munster Universitary.
    4. Katja Ignatieva & Natalia Ponomareva, 2017. "Commodity currencies and commodity prices: modelling static and time-varying dependence," Applied Economics, Taylor & Francis Journals, vol. 49(15), pages 1491-1512, March.
    5. Puente-Ajovin, Miguel & Ramos, Arturo, 2015. "An improvement over the normal distribution for log-growth rates of city sizes: Empirical evidence for France, Germany, Italy and Spain," MPRA Paper 67471, University Library of Munich, Germany.
    6. Arturo Ramos, 2017. "Are the log-growth rates of city sizes distributed normally? Empirical evidence for the USA," Empirical Economics, Springer, vol. 53(3), pages 1109-1123, November.
    7. Ramos, Arturo, 2015. "Are the log-growth rates of city sizes normally distributed? Empirical evidence for the US," MPRA Paper 65584, University Library of Munich, Germany.
    8. Gwo Dong Lin & Chin-Yuan Hu, 2021. "Formulas of Absolute Moments," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 476-495, February.
    9. Ignatieva, Katja & Landsman, Zinoviy, 2019. "Conditional tail risk measures for the skewed generalised hyperbolic family," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 98-114.
    10. Wan-Lun Wang & Ahad Jamalizadeh & Tsung-I Lin, 2020. "Finite mixtures of multivariate scale-shape mixtures of skew-normal distributions," Statistical Papers, Springer, vol. 61(6), pages 2643-2670, December.
    11. Luo, Min & Kontosakos, Vasileios E. & Pantelous, Athanasios A. & Zhou, Jian, 2019. "Cryptocurrencies: Dust in the wind?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1063-1079.
    12. Roman V. Ivanov, 2023. "The Semi-Hyperbolic Distribution and Its Applications," Stats, MDPI, vol. 6(4), pages 1-21, October.
    13. Philipp M. Möller, 2018. "Drawdown Measures And Return Moments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(07), pages 1-42, November.
    14. Ignatieva, Katja & Landsman, Zinoviy, 2015. "Estimating the tails of loss severity via conditional risk measures for the family of symmetric generalised hyperbolic distributions," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 172-186.
    15. Johannes Muhle-Karbe & Marcel Nutz, 2010. "Small-Time Asymptotics of Option Prices and First Absolute Moments," Papers 1006.2294, arXiv.org, revised Jun 2011.
    16. Behr, Andreas & Pötter, Ulrich, 2005. "Downward wage rigidity in Europe: A new flexible parametric approach and empirical results," Beiträge zur angewandten Wirtschaftsforschung 14, University of Münster, Center of Applied Economic Research Münster (CAWM).
    17. Andreas Behr & Ulrich Pötter, 2010. "Downward Wage Rigidity in Europe: A New Flexible Parametric Approach and Empirical Results," German Economic Review, Verein für Socialpolitik, vol. 11(2), pages 169-187, May.

  19. O. Barndorff-Nielsen & P. Blæsild & J. Schmiegel, 2004. "A parsimonious and universal description of turbulent velocity increments," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 41(3), pages 345-363, October.

    Cited by:

    1. Korolev, V.Yu. & Chertok, A.V. & Korchagin, A.Yu. & Zeifman, A.I., 2015. "Modeling high-frequency order flow imbalance by functional limit theorems for two-sided risk processes," Applied Mathematics and Computation, Elsevier, vol. 253(C), pages 224-241.
    2. Scott, David J & Würtz, Diethelm & Dong, Christine & Tran, Thanh Tam, 2009. "Moments of the generalized hyperbolic distribution," MPRA Paper 19081, University Library of Munich, Germany.
    3. Vindel, Jose M. & Trincado, Estrella, 2010. "The timing of information transmission in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5749-5758.
    4. Gravanis, E. & Akylas, E. & Michailides, C. & Livadiotis, G., 2021. "Superstatistics and isotropic turbulence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    5. Ole E. Barndorff-Nielsen & Makoto Maejima & Ken-iti Sato, 2006. "Infinite Divisibility for Stochastic Processes and Time Change," Journal of Theoretical Probability, Springer, vol. 19(2), pages 411-446, June.
    6. Ole E. Barndorff-Nielsen, 2016. "Assessing Gamma kernels and BSS/LSS processes," CREATES Research Papers 2016-09, Department of Economics and Business Economics, Aarhus University.

  20. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics," Econometrica, Econometric Society, vol. 72(3), pages 885-925, May.

    Cited by:

    1. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    2. Mattiussi, V. & Iori, G., 2006. "Currency futures volatility during the 1997 East Asian crisis: an application of Fourier analysis," Working Papers 06/09, Department of Economics, City University London.
    3. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    4. Gianluca Cubadda & Alain Hecq, 2021. "Reduced Rank Regression Models in Economics and Finance," CEIS Research Paper 525, Tor Vergata University, CEIS, revised 08 Nov 2021.
    5. Ferland, Rene & Lalancette, Simon, 2006. "Dynamics of realized volatilities and correlations: An empirical study," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2109-2130, July.
    6. Kolokolov, Aleksey & Livieri, Giulia & Pirino, Davide, 2020. "Statistical inferences for price staleness," Journal of Econometrics, Elsevier, vol. 218(1), pages 32-81.
    7. Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
    8. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    9. Anna Cieslak & Pavol Povala, 2016. "Information in the Term Structure of Yield Curve Volatility," Journal of Finance, American Finance Association, vol. 71(3), pages 1393-1436, June.
    10. Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020. "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, vol. 216(1), pages 86-105.
    11. Silja Kinnebrock & Mark Podolskij, 2008. "An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models," CREATES Research Papers 2008-23, Department of Economics and Business Economics, Aarhus University.
    12. Turan G. Bali & Robert F. Engle & Yi Tang, 2013. "Dynamic Conditional Beta is Alive and Well in the Cross-Section of Daily Stock Returns," Koç University-TUSIAD Economic Research Forum Working Papers 1305, Koc University-TUSIAD Economic Research Forum.
    13. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    14. Yu-Hua Zeng & Shou-Lei Wang & Yu-Fei Yang, 2014. "Calibration of the Volatility in Option Pricing Using the Total Variation Regularization," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-9, March.
    15. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    16. Dovonon, Prosper & Taamouti, Abderrahim & Williams, Julian, 2022. "Testing the eigenvalue structure of spot and integrated covariance," Journal of Econometrics, Elsevier, vol. 229(2), pages 363-395.
    17. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    18. Rasmus Tangsgaard Varneskov, 2011. "Flat-Top Realized Kernel Estimation of Quadratic Covariation with Non-Synchronous and Noisy Asset Prices," CREATES Research Papers 2011-35, Department of Economics and Business Economics, Aarhus University.
    19. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    20. Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
    21. Andersen, Torben G. & Riva, Raul & Thyrsgaard, Martin & Todorov, Viktor, 2023. "Intraday cross-sectional distributions of systematic risk," Journal of Econometrics, Elsevier, vol. 235(2), pages 1394-1418.
    22. Maria Elvira Mancino & Simona Sanfelici, 2011. "Estimation of Quarticity with High Frequency Data," Working Papers - Mathematical Economics 2011-06, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, revised Jan 2012.
    23. Jiayuan Zhou & Feiyu Jiang & Ke Zhu & Wai Keung Li, 2019. "Time series models for realized covariance matrices based on the matrix-F distribution," Papers 1903.12077, arXiv.org, revised Jul 2020.
    24. Johannes W. Fedderke, 2020. "The South African – United States Sovereign Bond Spread and its Association with Macroeconomic Fundamentals," Working Papers 830, Economic Research Southern Africa.
    25. Qu, Hui & Wang, Tianyang & Zhang, Yi & Sun, Pengfei, 2019. "Dynamic hedging using the realized minimum-variance hedge ratio approach – Examination of the CSI 300 index futures," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    26. Ozcan Ceylan, 2015. "Limited information-processing capacity and asymmetric stock correlations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1031-1039, June.
    27. Helmut Herwartz, 2006. "Econometric analysis of high frequency data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 89-104, March.
    28. Isao Ishida & Michael McAleer & Kosuke Oya, 2011. "Estimating the Leverage Parameter of Continuous-time Stochastic Volatility Models Using High Frequency S&P 500 and VIX," Working Papers in Economics 11/11, University of Canterbury, Department of Economics and Finance.
    29. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    30. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    31. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    32. Jiang, Liang & Wang, Xiaohu & Yu, Jun, 2018. "New distribution theory for the estimation of structural break point in mean," Journal of Econometrics, Elsevier, vol. 205(1), pages 156-176.
    33. Riza Demirer & Konstantinos Gkillas & Christos Kountzakis & Amaryllis Mavragani, 2020. "Risk Appetite and Jumps in Realized Correlation," Mathematics, MDPI, vol. 8(12), pages 1-11, December.
    34. Bollerslev, Tim & Patton, Andrew J. & Zhang, Haozhe, 2022. "Equity clusters through the lens of realized semicorrelations," Economics Letters, Elsevier, vol. 211(C).
    35. Peter Reinhard Hansen & Guillaume Horel & Asger Lunde & Ilya Archakov, 2015. "A Markov Chain Estimator of Multivariate Volatility from High Frequency Data," CREATES Research Papers 2015-19, Department of Economics and Business Economics, Aarhus University.
    36. Xinghua Zheng & Yingying Li, 2010. "On the estimation of integrated covariance matrices of high dimensional diffusion processes," Papers 1005.1862, arXiv.org, revised Mar 2012.
    37. Audrino, Francesco & Corsi, Fulvio, 2010. "Modeling tick-by-tick realized correlations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2372-2382, November.
    38. Li, Jia & Todorov, Viktor & Tauchen, George & Chen, Rui, 2017. "Mixed-scale jump regressions with bootstrap inference," Journal of Econometrics, Elsevier, vol. 201(2), pages 417-432.
    39. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    40. Gribisch, Bastian, 2013. "A latent dynamic factor approach to forecasting multivariate stock market volatility," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79823, Verein für Socialpolitik / German Economic Association.
    41. Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Janeway Institute Working Papers 2208, Faculty of Economics, University of Cambridge.
    42. Chiriac, Roxana & Voev, Valeri, 2008. "Modelling and forecasting multivariate realized volatility," CoFE Discussion Papers 08/06, University of Konstanz, Center of Finance and Econometrics (CoFE).
    43. Vincenzo Candila, 2013. "A Comparison of the Forecasting Performances of Multivariate Volatility Models," Working Papers 3_228, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    44. Yu‐Sheng Lai, 2022. "High‐frequency data and stock–bond investing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1623-1638, December.
    45. Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan & Gkillas, Konstantinos, 2020. "Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model," Energy Economics, Elsevier, vol. 88(C).
    46. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "How to Estimate Beta?," Hannover Economic Papers (HEP) dp-617, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    47. Laurini, Márcio P., 2007. "Imposing No-Arbitrage Conditions In Implied Volatility Surfaces Using Constrained Smoothing Splines," Insper Working Papers wpe_89, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    48. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    49. Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
    50. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
    51. Andrea Bucci & Vito Ciciretti, 2021. "Market Regime Detection via Realized Covariances: A Comparison between Unsupervised Learning and Nonlinear Models," Papers 2104.03667, arXiv.org.
    52. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    53. Liu, Guangqiang & Wang, Yan & Chen, Xiaodan & Zhang, Yifeng & Shang, Yue, 2020. "Forecasting volatility of the Chinese stock markets using TVP HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    54. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    55. Hu, Sunyang & Gu, Zongyuan & Wang, Yifeng & Zhang, Xiaolei, 2019. "An analysis of the clustering effect of a jump risk complex network in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 622-630.
    56. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    57. Jozef Baruník & Evžen Kocenda & Lukáš Vácha, 2015. "Gold, Oil, and Stocks: Dynamic Correlations," CESifo Working Paper Series 5333, CESifo.
    58. Nolte, Ingmar & Voev, Valeri, 2007. "Estimating high-frequency based (co-) variances: A unified approach," CoFE Discussion Papers 07/07, University of Konstanz, Center of Finance and Econometrics (CoFE).
    59. Peter Christoffersen & Asger Lunde & Kasper V. Olesen, 2014. "Factor Structure in Commodity Futures Return and Volatility," CREATES Research Papers 2014-31, Department of Economics and Business Economics, Aarhus University.
    60. Vortelinos, Dimitrios I., 2016. "Incremental information of stock indicators," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 79-97.
    61. Philipp Matros & Johannes Vilsmeier, 2013. "The Multivariate Option iPoD Framework - Assessing Systemic Financial Risk," Working Papers 143, Bavarian Graduate Program in Economics (BGPE).
    62. Philip Bertram & Robinson Kruse & Philipp Sibbertsen, 2013. "Fractional integration versus level shifts: the case of realized asset correlations," Statistical Papers, Springer, vol. 54(4), pages 977-991, November.
    63. Varneskov, Rasmus & Voev, Valeri, 2013. "The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 83-95.
    64. Rama Cont & Lakshithe Wagalath, 2016. "Institutional Investors And The Dependence Structure Of Asset Returns," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 1-37, March.
    65. Yu‐Sheng Lai, 2019. "Flexible covariance dynamics, high‐frequency data, and optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1529-1548, December.
    66. Shen, Keren & Yao, Jianfeng & Li, Wai Keung, 2019. "On a spiked model for large volatility matrix estimation from noisy high-frequency data," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 207-221.
    67. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.
    68. Shin, Dong Wan & Park, Sangun, 2012. "Efficient realized variance, regression coefficient, and correlation coefficient under different sampling frequencies," Economics Letters, Elsevier, vol. 115(3), pages 334-337.
    69. Kamiar Mohaddes & M. Hashem Pesaran, 2013. "One Hundred Years of Oil Income and the Iranian Economy: A Curse or a Blessing?," Working Papers 771, Economic Research Forum, revised Sep 2013.
    70. Ole Barndorff-Nielsen & Svend Erik Graversen & Jean Jacod & Mark Podolskij & Neil Shephard, 2004. "A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales," Economics Papers 2004-W29, Economics Group, Nuffield College, University of Oxford.
    71. Yu, Qian & Bajja, Salwa, 2020. "Volatility estimation of general Gaussian Ornstein–Uhlenbeck process," Statistics & Probability Letters, Elsevier, vol. 163(C).
    72. Michal Krajňák, 2020. "Je daň z příjmů fyzických osob ze závislé činnosti v České republice progresivní? [Is Personal Income Tax on Dependent Activity in the Czech Republic Progressive?]," Politická ekonomie, Prague University of Economics and Business, vol. 2020(5), pages 534-553.
    73. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
    74. Wei Kuang, 2021. "Conditional covariance matrix forecast using the hybrid exponentially weighted moving average approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1398-1419, December.
    75. Torben G. Andersen & Luca Benzoni, 2010. "Do Bonds Span Volatility Risk in the U.S. Treasury Market? A Specification Test for Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 65(2), pages 603-653, April.
    76. Cherif Guermat & Richard D. F. Harris, 2006. "Bias in the estimation of non-linear transformations of the integrated variance of returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 481-494.
    77. Cecilia Mancini & Fabio Gobbi, 2010. "Identifying the Brownian Covariation from the Co-Jumps Given Discrete Observations," Working Papers - Mathematical Economics 2010-05, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    78. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    79. Kolokolov, Aleksey & Livieri, Giulia & Pirino, Davide, 2018. "Statistical inferences for price staleness," SAFE Working Paper Series 236, Leibniz Institute for Financial Research SAFE.
    80. Bucci, Andrea & Ciciretti, Vito, 2022. "Market regime detection via realized covariances," Economic Modelling, Elsevier, vol. 111(C).
    81. Andrew Phin & Todd Prono & Jonathan J. Reeves & Konark Saxena, 2018. "Level Shifts in Beta, Spurious Abnormal Returns and the TARP Announcement," Finance and Economics Discussion Series 2018-081, Board of Governors of the Federal Reserve System (U.S.).
    82. Qifa Xu & Junqing Zuo & Cuixia Jiang & Yaoyao He, 2021. "A large constrained time‐varying portfolio selection model with DCC‐MIDAS: Evidence from Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3417-3435, July.
    83. Todorov, Viktor & Bollerslev, Tim, 2010. "Jumps and betas: A new framework for disentangling and estimating systematic risks," Journal of Econometrics, Elsevier, vol. 157(2), pages 220-235, August.
    84. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2012. "Intra-daily volatility spillovers between the US and German stock markets," Economics Working Papers 2012-06, Christian-Albrechts-University of Kiel, Department of Economics.
    85. Yao Axel Ehouman, 2020. "Volatility transmission between oil prices and banks’ stock prices as a new source of instability: Lessons from the United States experience," Post-Print hal-02960571, HAL.
    86. Kevin Sheppard & Wen Xu, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    87. Lu, Ran & Xu, Wen & Zeng, Hongjun & Zhou, Xiangjing, 2023. "Volatility connectedness among the Indian equity and major commodity markets under the COVID-19 scenario," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1465-1481.
    88. Ole E. Barndorff-Nielsen & Neil Shephard & Matthias Winkel, 2005. "Limit theorems for multipower variation in the presence of jumps," OFRC Working Papers Series 2005fe06, Oxford Financial Research Centre.
    89. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Economics Papers 2008-W10, Economics Group, Nuffield College, University of Oxford.
    90. Yuta yamauchi & Yasuhiro Omori, 2019. "Multivariate Stochastic Volatility Model with Realized Volatilities and Pairwise Realized Correlations," CIRJE F-Series CIRJE-F-1117, CIRJE, Faculty of Economics, University of Tokyo.
    91. Jia Liu & John M. Maheu, 2018. "Improving Markov switching models using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 297-318, April.
    92. Aslanidis, Nektarios & Christiansen, Charlotte, 2014. "Quantiles of the realized stock–bond correlation and links to the macroeconomy," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 321-331.
    93. Kim Christensen & Mark Podolskij & Mathias Vetter, 2009. "Bias-correcting the realized range-based variance in the presence of market microstructure noise," Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
    94. Bilel Sanhaji & Julien Chevallier, 2023. "Tracking ‘Pure’ Systematic Risk with Realized Betas for Bitcoin and Ethereum," Post-Print hal-04218488, HAL.
    95. Alessandro Casini & Pierre Perron, 2020. "Continuous Record Asymptotics for Change-Point Models," Boston University - Department of Economics - Working Papers Series WP2020-013, Boston University - Department of Economics.
    96. Kevin Sheppard & Wen Xu, 2019. "Factor High-Frequency-Based Volatility (HEAVY) Models," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 33-65.
    97. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    98. Abad, P. & Ferreras, R. & Robles, M.D., 2020. "Intra-industry transfer effects of credit risk news: Rated versus unrated rivals," The British Accounting Review, Elsevier, vol. 52(1).
    99. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    100. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford.
    101. Christensen, Kim & Kinnebrock, Silja & Podolskij, Mark, 2010. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," Journal of Econometrics, Elsevier, vol. 159(1), pages 116-133, November.
    102. Cui, Jing & Zhao, Hua, 2015. "Intraday jumps in China's Treasury bond market and macro news announcements," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 211-223.
    103. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2015. "Intra-daily volatility spillovers in international stock markets," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 95-114.
    104. Michiel de Pooter & Martin Martens & Dick van Dijk, 2005. "Predicting the Daily Covariance Matrix for S&P 100 Stocks using Intraday Data - But which Frequency to use?," Tinbergen Institute Discussion Papers 05-089/4, Tinbergen Institute, revised 03 Jan 2006.
    105. Markus Bibinger & Nikolaus Hautsch & Peter Malec & Markus Reiss, 2014. "Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence," Cambridge Working Papers in Economics 1464, Faculty of Economics, University of Cambridge.
    106. Dellaportas, Petros & Titsias, Michalis K. & Petrova, Katerina & Plataniotis, Anastasios, 2023. "Scalable inference for a full multivariate stochastic volatility model," Journal of Econometrics, Elsevier, vol. 232(2), pages 501-520.
    107. Yuta Kurose & Yasuhiro Omori, 2016. "Multiple-block Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1024, CIRJE, Faculty of Economics, University of Tokyo.
    108. Baruník, Jozef & Kukacka, Jiri, 2014. "Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility," FinMaP-Working Papers 15, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    109. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    110. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    111. Nikolaus Hautsch & Stefan Voigt, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty," Papers 1709.06296, arXiv.org, revised Jun 2018.
    112. Qianqiu Liu, 2009. "On portfolio optimization: How and when do we benefit from high-frequency data?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 560-582.
    113. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    114. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015. "Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
    115. Adam E Clements & Christopher A Coleman-Fenn & Daniel R Smith, 2011. "Forecasting Equicorrelation," NCER Working Paper Series 72, National Centre for Econometric Research, revised 29 Aug 2011.
    116. Lidan Grossmass, 2014. "Obtaining and Predicting the Bounds of Realized Correlations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(III), pages 191-226, September.
    117. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    118. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    119. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    120. Raphael Auer & Bruce Iwadate & Andreas Schrimpf & Alexander F. Wagner & Raphael A. Auer, 2023. "Global Production Linkages and Stock Market Comovement," CESifo Working Paper Series 10492, CESifo.
    121. Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 5-31.
    122. Arnaud Gloter, 2007. "Efficient estimation of drift parameters in stochastic volatility models," Finance and Stochastics, Springer, vol. 11(4), pages 495-519, October.
    123. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    124. Weigand, Roland, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," University of Regensburg Working Papers in Business, Economics and Management Information Systems 478, University of Regensburg, Department of Economics.
    125. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    126. Shabir A A Saleem & Peter N Smith & Abdullah Yalaman, 2021. "Analysis of systematic risk around firm-specific news in an emerging market using high frequency data," CAMA Working Papers 2021-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    127. Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
    128. Li, Jia & Todorov, Viktor & Tauchen, George, 2016. "Inference theory for volatility functional dependencies," Journal of Econometrics, Elsevier, vol. 193(1), pages 17-34.
    129. Lakshithe Wagalath, 2016. "Feedback effects and endogenous risk in financial markets," Finance, Presses universitaires de Grenoble, vol. 37(2), pages 39-74.
    130. Nath, H. (Mindi) B. & Kim, Jae H. & Brooks, Robert D., 2012. "Realized dual-betas for leading Australian stocks: An evaluation of the estimation methods and the effect of the sampling interval," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 83(C), pages 10-22.
    131. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
    132. Jian, Zhihong & Deng, Pingjun & Zhu, Zhican, 2018. "High-dimensional covariance forecasting based on principal component analysis of high-frequency data," Economic Modelling, Elsevier, vol. 75(C), pages 422-431.
    133. Arnerić Josip & Poklepović Tea & Teai Juin Wen, 2018. "Neural Network Approach in Forecasting Realized Variance Using High-Frequency Data," Business Systems Research, Sciendo, vol. 9(2), pages 18-34, July.
    134. Elie Bouri & Konstantinos Gkillas & Rangan Gupta, 2020. "Trade uncertainties and the hedging abilities of Bitcoin," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 49(3), September.
    135. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
    136. Vogler, Jan & Golosnoy, Vasyl, 2023. "Unrestricted maximum likelihood estimation of multivariate realized volatility models," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1063-1074.
    137. Silja Kinnebrock & Mark Podolskij, 2007. "A Note on the Central Limit Theorem for Bipower Variation of General Functions," OFRC Working Papers Series 2007fe03, Oxford Financial Research Centre.
    138. Omura, Akihiro & Li, Bin & Chung, Richard & Todorova, Neda, 2018. "Convenience yield, realised volatility and jumps: Evidence from non-ferrous metals," Economic Modelling, Elsevier, vol. 70(C), pages 496-510.
    139. Choi, Kyongwook & Yu, Wei-Choun & Zivot, Eric, 2010. "Long memory versus structural breaks in modeling and forecasting realized volatility," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 857-875, September.
    140. Patton, Andrew J. & Sheppard, Kevin, 2009. "Optimal combinations of realised volatility estimators," International Journal of Forecasting, Elsevier, vol. 25(2), pages 218-238.
    141. Ilze Kalnina, 2023. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 538-549, April.
    142. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    143. Wenjing Wang & Minjing Tao, 2020. "Forecasting Realized Volatility Matrix With Copula-Based Models," Papers 2002.08849, arXiv.org.
    144. Andre Lucas & Anne Opschoor & Luca Rossini, 2021. "Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution," Tinbergen Institute Discussion Papers 21-010/III, Tinbergen Institute, revised 11 Jul 2023.
    145. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    146. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2011. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-812, CIRJE, Faculty of Economics, University of Tokyo.
    147. Andrew J. Patton & Kevin Sheppard, 2008. "Evaluating Volatility and Correlation Forecasts," OFRC Working Papers Series 2008fe22, Oxford Financial Research Centre.
    148. Ehouman, Yao Axel, 2020. "Volatility transmission between oil prices and banks' stock prices as a new source of instability: Lessons from the United States experience," Economic Modelling, Elsevier, vol. 91(C), pages 198-217.
    149. Virbickaitė, Audronė & Frey, Christoph & Macedo, Demian N., 2020. "Bayesian sequential stock return prediction through copulas," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    150. Wang, Hao & Yue, Mengqi & Zhao, Hua, 2015. "Cojumps in China's spot and stock index futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 541-557.
    151. Gustavo F. Dias & Marcelo Fernandes & Cristina M. Scherrer, 2021. "Price Discovery in a Continuous-Time Setting [Price Discovery and Common Factor Models]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 985-1008.
    152. Ishida, I. & McAleer, M.J. & Oya, K., 2011. "Estimating the Leverage Parameter of Continuous-time Stochastic Volatility Models Using High Frequency S&P 500 VIX," Econometric Institute Research Papers EI 2011-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    153. Kleppe, Tore Selland & Liesenfeld, Roman & Moura, Guilherme Valle & Oglend, Atle, 2022. "Analyzing Commodity Futures Using Factor State-Space Models with Wishart Stochastic Volatility," Econometrics and Statistics, Elsevier, vol. 23(C), pages 105-127.
    154. Mohammad Abu Sayeed & Mardi Dungey & Wenying Yao, 2018. "High-frequency Characterisation of Indian Banking Stocks," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2_suppl), pages 213-238, August.
    155. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2019. "Tests for conditional heteroscedasticity with functional data and goodness-of-fit tests for FGARCH models," MPRA Paper 93048, University Library of Munich, Germany.
    156. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    157. Reiß, Markus & Todorov, Viktor & Tauchen, George, 2015. "Nonparametric test for a constant beta between Itô semi-martingales based on high-frequency data," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2955-2988.
    158. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," Journal of Econometrics, Elsevier, vol. 193(2), pages 367-389.
    159. Fulvio Corsi & Stefano Peluso & Francesco Audrino, 2015. "Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 377-397, April.
    160. Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
    161. Taro Kanatani, 2007. "Finite Sample Analysis of Weighted Realized Covariance with Noisy Asynchronous Observations," KIER Working Papers 634, Kyoto University, Institute of Economic Research.
    162. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    163. Aurea Grané & Helena Veiga, 2012. "Asymmetry, realised volatility and stock return risk estimates," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 11(2), pages 147-164, August.
    164. Vasyl Golosnoy & Benno Hildebrandt & Steffen Köhler, 2019. "Modeling and Forecasting Realized Portfolio Diversification Benefits," JRFM, MDPI, vol. 12(3), pages 1-16, July.
    165. Garcia, René & Renault, Eric & Veredas, David, 2011. "Estimation of stable distributions by indirect inference," Journal of Econometrics, Elsevier, vol. 161(2), pages 325-337, April.
    166. Ghosh, Anisha & Linton, Oliver, 2009. "Consistent estimation of the risk-return tradeoff in the presence of measurement error," UC3M Working papers. Economics we094928, Universidad Carlos III de Madrid. Departamento de Economía.
    167. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.
    168. Richard Y. Chen, 2019. "The Fourier Transform Method for Volatility Functional Inference by Asynchronous Observations," Papers 1911.02205, arXiv.org.
    169. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, Department of Economics and Business Economics, Aarhus University.
    170. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2007. "Power variation for Gaussian processes with stationary increments," CREATES Research Papers 2007-42, Department of Economics and Business Economics, Aarhus University.
    171. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    172. Hiroki Masuda & Takayuki Morimoto, 2012. "Optimal Weight For Realized Variance Based On Intermittent High-Frequency Data," The Japanese Economic Review, Japanese Economic Association, vol. 63(4), pages 497-527, December.
    173. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.
    174. Anna Cieslak & Andreas Schrimpf, 2018. "Non-monetary news in central bank communication," BIS Working Papers 761, Bank for International Settlements.
    175. Philip L. H. Yu & W. K. Li & F. C. Ng, 2017. "The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 513-527, October.
    176. Tao, Minjing & Wang, Yahzen & Yao, Qiwei & Zou, Jian, 2011. "Large volatility matrix inference via combining low-frequency and high-frequency approaches," LSE Research Online Documents on Economics 39321, London School of Economics and Political Science, LSE Library.
    177. Dare, Wale & Fengler, Matthias, 2017. "Global estimation of realized spot volatility in the presence of price jumps," Economics Working Paper Series 1715, University of St. Gallen, School of Economics and Political Science.
    178. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
    179. Casini, Alessandro & Perron, Pierre, 2021. "Continuous record Laplace-based inference about the break date in structural change models," Journal of Econometrics, Elsevier, vol. 224(1), pages 3-21.
    180. Ilze KALNINA & Kokouvi TEWOU, 2015. "Cross-sectional Dependence in Idiosyncratic Volatility," Cahiers de recherche 08-2015, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    181. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
    182. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2015. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-979, CIRJE, Faculty of Economics, University of Tokyo.
    183. Markus Bibinger & Markus Reiss & Nikolaus Hautsch & Peter Malec, 2014. "Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence," SFB 649 Discussion Papers SFB649DP2014-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    184. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
    185. Ishan Goel & Sukant Khurana, 2018. "A Bayesian measure of association that utilizes the underlying distributions of noise and information," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-21, August.
    186. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "Realized semibetas: Disentangling “good” and “bad” downside risks," Journal of Financial Economics, Elsevier, vol. 144(1), pages 227-246.
    187. Symitsi, Efthymia & Symeonidis, Lazaros & Kourtis, Apostolos & Markellos, Raphael, 2018. "Covariance forecasting in equity markets," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 153-168.
    188. Phin, Andrew & Prono, Todd & Reeves, Jonathan J. & Saxena, Konark, 2022. "Shifts in beta and the TARP announcement," Finance Research Letters, Elsevier, vol. 47(PB).
    189. Haugom, Erik & Lien, Gudbrand & Veka, Steinar & Westgaard, Sjur, 2014. "Covariance estimation using high-frequency data: Sensitivities of estimation methods," Economic Modelling, Elsevier, vol. 43(C), pages 416-425.
    190. Bretó, Carles & Veiga, Helena, 2011. "Forecasting volatility: does continuous time do better than discrete time?," DES - Working Papers. Statistics and Econometrics. WS ws112518, Universidad Carlos III de Madrid. Departamento de Estadística.
    191. Dovonon, Prosper & Gonçalves, Sílvia & Meddahi, Nour, 2013. "Bootstrapping realized multivariate volatility measures," Journal of Econometrics, Elsevier, vol. 172(1), pages 49-65.
    192. Jeffrey R. Russell & Federico M. Bandi, 2004. "Microstructure noise, realized volatility, and optimal sampling," Econometric Society 2004 Latin American Meetings 220, Econometric Society.
    193. Grønborg, Niels S. & Lunde, Asger & Olesen, Kasper V. & Vander Elst, Harry, 2022. "Realizing correlations across asset classes," Journal of Financial Markets, Elsevier, vol. 59(PA).
    194. Turan G. Bali & Armen Hovakimian, 2009. "Volatility Spreads and Expected Stock Returns," Management Science, INFORMS, vol. 55(11), pages 1797-1812, November.
    195. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    196. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    197. Xin Huang & Hao Zhou & Haibin Zhu, 2009. "A Framework for Assessing the Systemic Risk of Major Financial Institutions," BIS Working Papers 281, Bank for International Settlements.
    198. Dong Hwan Oh & Andrew J. Patton, 2015. "High-Dimensional Copula-Based Distributions with Mixed Frequency Data," Finance and Economics Discussion Series 2015-50, Board of Governors of the Federal Reserve System (U.S.).
    199. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    200. Rama Cont & Lakshithe Wagalath, 2014. "Institutional Investors and the Dependence Structure of Asset Returns," Working Papers 2014-ACF-01, IESEG School of Management.
    201. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High Dimensional Vector Autoregressive Models," CEIS Research Paper 534, Tor Vergata University, CEIS, revised 24 Mar 2022.
    202. Peter Reinhard Hansen & Yiyao Luo, 2023. "Robust Estimation of Realized Correlation: New Insight about Intraday Fluctuations in Market Betas," Papers 2310.19992, arXiv.org.
    203. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    204. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    205. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    206. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    207. Warusawitharana, Missaka, 2018. "Time-varying volatility and the power law distribution of stock returns," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 123-141.
    208. Haselmann, Rainer & Herwartz, Helmut, 2010. "The introduction of the Euro and its effects on portfolio decisions," Journal of International Money and Finance, Elsevier, vol. 29(1), pages 94-110, February.
    209. Yu‐Sheng Lai, 2018. "Estimation of the optimal futures hedge ratio for equity index portfolios using a realized beta generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1370-1390, November.
    210. Wang, Kent & Liu, Junwei & Liu, Zhi, 2013. "Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1777-1786.
    211. Kirill Dragun & Kris Boudt & Orimar Sauri & Steven Vanduffel, 2021. "Beta-Adjusted Covariance Estimation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1010, Ghent University, Faculty of Economics and Business Administration.
    212. Markus Reiß & Viktor Todorov & George Tauchen, 2014. "Nonparametric Test for a Constant Beta over a Fixed Time Interval," SFB 649 Discussion Papers SFB649DP2014-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    213. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    214. Arindam Banerjee, 2019. "Predicting Stock Return of UAE Listed Companies Using Financial Ratios," Accounting and Finance Research, Sciedu Press, vol. 8(2), pages 214-214, May.
    215. Ruijun Bu & Degui Li & Oliver Linton & Hanchao Wang, 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Working Papers 202212, University of Liverpool, Department of Economics.
    216. Johannes W. Fedderke, 2020. "Is the Phillips curve framework still useful for understanding inflation dynamics in South Africa," Working Papers 10142, South African Reserve Bank.
    217. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    218. Zhang, Congshan & Li, Jia & Todorov, Viktor & Tauchen, George, 2022. "Variation and efficiency of high-frequency betas," Journal of Econometrics, Elsevier, vol. 228(1), pages 156-175.
    219. Herwartz, Helmut & Golosnoy, Vasyl, 2007. "Semiparametric Approaches to the Prediction of Conditional Correlation Matrices in Finance," Economics Working Papers 2007-23, Christian-Albrechts-University of Kiel, Department of Economics.
    220. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2010. "The conditional autoregressive wishart model for multivariate stock market volatility," Economics Working Papers 2010-07, Christian-Albrechts-University of Kiel, Department of Economics.
    221. Ulrich Hounyo, 2013. "Bootstrapping realized volatility and realized beta under a local Gaussianity assumption," CREATES Research Papers 2013-30, Department of Economics and Business Economics, Aarhus University.
    222. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2019. "Estimating beta: Forecast adjustments and the impact of stock characteristics for a broad cross-section," Journal of Financial Markets, Elsevier, vol. 44(C), pages 91-118.
    223. Bollerslev, Tim & Li, Sophia Zhengzi & Todorov, Viktor, 2016. "Roughing up beta: Continuous versus discontinuous betas and the cross section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 120(3), pages 464-490.
    224. Benth, Fred Espen & Schroers, Dennis & Veraart, Almut E.D., 2022. "A weak law of large numbers for realised covariation in a Hilbert space setting," Stochastic Processes and their Applications, Elsevier, vol. 145(C), pages 241-268.
    225. Matros, Philipp & Vilsmeier, Johannes, 2014. "The multivariate option iPoD framework: assessing systemic financial risk," Discussion Papers 20/2014, Deutsche Bundesbank.
    226. Hayashi, Takaki & Yoshida, Nakahiro, 2011. "Nonsynchronous covariation process and limit theorems," Stochastic Processes and their Applications, Elsevier, vol. 121(10), pages 2416-2454, October.
    227. Ortas, E. & Salvador, M. & Moneva, J.M., 2015. "Improved beta modeling and forecasting: An unobserved component approach with conditional heteroscedastic disturbances," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 27-51.
    228. Erlin Guo & Cuixia Li & Fengqin Tang, 2023. "The Convergence Rates of Large Volatility Matrix Estimator Based on Noise, Jumps, and Asynchronization," Mathematics, MDPI, vol. 11(6), pages 1-11, March.
    229. María T. González-Pérez, 2021. "Lessons from estimating the average option-implied volatility term structure for the Spanish banking sector," Working Papers 2128, Banco de España.
    230. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    231. Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
    232. Michela Verardo & Andrew Patton, 2009. "Does Beta Move with News? Systematic Risk and Firm-Specific Information Flows," FMG Discussion Papers dp630, Financial Markets Group.
    233. Papantonis Ioannis & Tzavalis Elias & Agapitos Orestis & Rompolis Leonidas S., 2023. "Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 171-198, April.
    234. Li, Wenlan & Cheng, Yuxiang & Fang, Qiang, 2020. "Forecast on silver futures linked with structural breaks and day-of-the-week effect," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    235. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    236. Li, Jia & Todorov, Viktor & Tauchen, George, 2017. "Adaptive estimation of continuous-time regression models using high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 36-47.
    237. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
    238. Li, Shaoyu & Zheng, Tingguo, 2017. "Modeling spot rate using a realized stochastic volatility model with level effect and dynamic drift☆," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 200-221.
    239. Vortelinos, Dimitrios I., 2010. "The properties of realized correlation: Evidence from the French, German and Greek equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 273-290, August.
    240. Sun, Yucheng & Xu, Wen & Zhang, Chuanhai, 2023. "Identifying latent factors based on high-frequency data," Journal of Econometrics, Elsevier, vol. 233(1), pages 251-270.
    241. Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
    242. Doan, Bao & Lee, John B. & Liu, Qianqiu & Reeves, Jonathan J., 2022. "Beta measurement with high frequency returns," Finance Research Letters, Elsevier, vol. 47(PA).
    243. Bannouh, K. & van Dijk, D.J.C. & Martens, M.P.E., 2008. "Range-based covariance estimation using high-frequency data: The realized co-range," Econometric Institute Research Papers EI 2007-53, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    244. Nabil Bouamara & Kris Boudt & S'ebastien Laurent & Christopher J. Neely, 2023. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Papers 2309.15705, arXiv.org.
    245. Park, Sujin & Hong, Seok Young & Linton, Oliver, 2016. "Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error," Journal of Econometrics, Elsevier, vol. 191(2), pages 325-347.
    246. Shephard, Neil & Xiu, Dacheng, 2017. "Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading," Journal of Econometrics, Elsevier, vol. 201(1), pages 19-42.
    247. Si Mohammed, Kamel & Tedeschi, Marco & Mallek, Sabrine & Tarczyńska-Łuniewska, Małgorzata & Zhang, Anqi, 2023. "Realized semi variance quantile connectedness between oil prices and stock market: Spillover from Russian-Ukraine clash," Resources Policy, Elsevier, vol. 85(PA).
    248. Nien-Lin Liu & Hoang-Long Ngo, 2014. "Approximation of eigenvalues of spot cross volatility matrix with a view toward principal component analysis," Papers 1409.2214, arXiv.org.
    249. Viceira, Luis M., 2012. "Bond risk, bond return volatility, and the term structure of interest rates," International Journal of Forecasting, Elsevier, vol. 28(1), pages 97-117.
    250. Francesco Ravazzolo & Marco J. Lombardi, 2012. "Oil price density forecasts: Exploring the linkages with stock markets," Working Papers No 3/2012, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    251. McMillan, David G. & Speight, Alan E.H., 2010. "Return and volatility spillovers in three euro exchange rates," Journal of Economics and Business, Elsevier, vol. 62(2), pages 79-93, March.
    252. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    253. Haselmann, Rainer & Herwartz, Helmut, 2008. "Portfolio performance and the Euro: Prospects for new potential EMU members," Journal of International Money and Finance, Elsevier, vol. 27(2), pages 314-330, March.
    254. Jian Chen & Xiaoquan Liu, 2010. "The model-free measures and the volatility spread," Applied Economics Letters, Taylor & Francis Journals, vol. 17(18), pages 1829-1833.
    255. Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
    256. Hwang, Eunju & Shin, Dong Wan, 2018. "Two-stage stationary bootstrapping for bivariate average realized volatility matrix under market microstructure noise and asynchronicity," Journal of Econometrics, Elsevier, vol. 202(2), pages 178-195.
    257. Cenesizoglu, Tolga & de Oliveira Ferrazoli Ribeiro, Fabio & Reeves, Jonathan J., 2017. "Beta forecasting at long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 936-957.
    258. Becker, Christoph & Schmidt, Wolfgang M., 2015. "How past market movements affect correlation and volatility," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 78-107.
    259. Dungey, Mardi & Henry, Olan T & Hvodzdyk, Lyudmyla, 2013. "The impact of jumps and thin trading on realized hedge ratios," Working Papers 2013-02, University of Tasmania, Tasmanian School of Business and Economics, revised 28 Mar 2013.
    260. Nicholas Taylor, 2014. "The Economic Value of Volatility Forecasts: A Conditional Approach," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 433-478.
    261. Elezovic, Suad, 2009. "Functional modelling of volatility in the Swedish limit order book," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2107-2118, April.
    262. Yeh, Jin-Huei & Wang, Jying-Nan, 2010. "Correcting microstructure comovement biases for integrated covariance," Finance Research Letters, Elsevier, vol. 7(3), pages 184-191, September.
    263. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    264. Koch, Sophia & Dimpfl, Thomas, 2023. "Attention and retail investor herding in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    265. Yuta Yamauchi & Yasuhiro Omori, 2018. "Multivariate Stochastic Volatility Model with Realized Volatilities and Pairwise Realized Correlations," Papers 1809.09928, arXiv.org, revised Mar 2019.
    266. Henker, Thomas & Husodo, Zaäfri A., 2010. "Noise and efficient variance in the Indonesia Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 18(2), pages 199-216, April.
    267. Bannouh, K. & Martens, M.P.E. & Oomen, R.C.A. & van Dijk, D.J.C., 2012. "Realized mixed-frequency factor models for vast dimensional covariance estimation," ERIM Report Series Research in Management ERS-2012-017-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    268. Liu, Guangying & Zhang, Xinsheng, 2011. "Power variation of fractional integral processes with jumps," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 962-972, August.
    269. Matteo Bonato & Luca Taschini, 2016. "Comovement and the financialization of commodities," GRI Working Papers 215, Grantham Research Institute on Climate Change and the Environment.
    270. Grané, Aurea & Veiga, Helena, 2007. "The effect of realised volatility on stock returns risk estimates," DES - Working Papers. Statistics and Econometrics. WS ws076316, Universidad Carlos III de Madrid. Departamento de Estadística.
    271. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    272. Jianqing Fan & Alex Furger & Dacheng Xiu, 2016. "Incorporating Global Industrial Classification Standard Into Portfolio Allocation: A Simple Factor-Based Large Covariance Matrix Estimator With High-Frequency Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 489-503, October.
    273. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    274. I‐Ming Jiang & Jui‐Cheng Hung & Chuan‐San Wang, 2014. "Volatility Forecasts: Do Volatility Estimators and Evaluation Methods Matter?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(11), pages 1077-1094, November.
    275. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    276. Papavassiliou, Vassilios G., 2013. "A new method for estimating liquidity risk: Insights from a liquidity-adjusted CAPM framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 184-197.
    277. Yuta Yamauchi & Yasuhiro Omori, 2016. "Multivariate Stochastic Volatility Model with Realized Volatilities and Pairwise Realized Correlations ," CIRJE F-Series CIRJE-F-1029, CIRJE, Faculty of Economics, University of Tokyo.
    278. Konstantinos Gkillas & Paraskevi Katsiampa & Dimitrios I. Vortelinos & Mark E. Wohar, 2023. "Greek government‐debt crisis events and European financial markets: News surprises on Greek bond yields and inter‐relations of European financial markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4037-4054, October.
    279. Ciciretti, Vito & Bucci, Andrea, 2023. "Building optimal regime-switching portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    280. Chiu, Mei Choi & Wong, Hoi Ying, 2014. "Mean–variance asset–liability management with asset correlation risk and insurance liabilities," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 300-310.
    281. Yu-Sheng Lai, 2018. "Dynamic hedging with futures: a copula-based GARCH model with high-frequency data," Review of Derivatives Research, Springer, vol. 21(3), pages 307-329, October.
    282. Campbell, John Y., 2009. "The Changing Role of Nominal Government Bonds in Asset Allocation," Scholarly Articles 10884856, Harvard University Department of Economics.
    283. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    284. Jozef Barunik & Pavel Fiser, 2019. "Co-jumping of Treasury Yield Curve Rates," Papers 1905.01541, arXiv.org.
    285. Giuseppe Buccheri & Davide Pirino & Luca Trapin, 2021. "Managing liquidity with portfolio staleness," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 215-239, June.
    286. Kim Christensen & Mikkel Slot Nielsen & Mark Podolskij, 2023. "High-dimensional estimation of quadratic variation based on penalized realized variance," Statistical Inference for Stochastic Processes, Springer, vol. 26(2), pages 331-359, July.
    287. Horváth, Lajos & Kokoszka, Piotr & Rice, Gregory, 2014. "Testing stationarity of functional time series," Journal of Econometrics, Elsevier, vol. 179(1), pages 66-82.
    288. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    289. Vasyl Golosnoy, 2018. "Sequential monitoring of portfolio betas," Statistical Papers, Springer, vol. 59(2), pages 663-684, June.
    290. Taro Kanatani & Roberto Reno', 2007. "Unbiased covariance estimation with interpolated data," Department of Economics University of Siena 502, Department of Economics, University of Siena.
    291. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2013. "Conditional alphas and realized betas," Textos para discussão 341, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    292. L. C. G. Rogers & Fanyin Zhou, 2008. "Estimating correlation from high, low, opening and closing prices," Papers 0804.0162, arXiv.org.
    293. Choi, Yongok & Jacewitz, Stefan & Park, Joon Y., 2016. "A reexamination of stock return predictability," Journal of Econometrics, Elsevier, vol. 192(1), pages 168-189.
    294. Luo, Jiawen & Marfatia, Hardik A. & Ji, Qiang & Klein, Tony, 2023. "Co-volatility and asymmetric transmission of risks between the global oil and China's futures markets," Energy Economics, Elsevier, vol. 117(C).
    295. Ikeda, Shin S., 2016. "A bias-corrected estimator of the covariation matrix of multiple security prices when both microstructure effects and sampling durations are persistent and endogenous," Journal of Econometrics, Elsevier, vol. 193(1), pages 203-214.
    296. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    297. Laurini, Márcio Poletti & Hotta, Luiz Koodi, 2013. "Indirect Inference in fractional short-term interest rate diffusions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 109-126.
    298. Ben Sita, Bernard, 2018. "Estimating the beta-return relationship by considering the sign and the magnitude of daily returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 28-35.
    299. Alfelt, Gustav & Bodnar, Taras & Javed, Farrukh & Tyrcha, Joanna, 2020. "Singular conditional autoregressive Wishart model for realized covariance matrices," Working Papers 2021:1, Örebro University, School of Business.
    300. Liu, Guangqiang & Wei, Yu & Chen, Yongfei & Yu, Jiang & Hu, Yang, 2018. "Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 288-297.
    301. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    302. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
    303. Behfar, Stefan Kambiz, 2016. "Long memory behavior of returns after intraday financial jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 716-725.
    304. Fabio Gobbi & Cecilia Mancini, 2006. "Identifying the covariation between the diffusion parts and the co-jumps given discrete observations," Papers math/0610621, arXiv.org, revised Jul 2008.
    305. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
    306. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2020. "Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction," Energy Economics, Elsevier, vol. 92(C).
    307. Neil Shephard, 2020. "An estimator for predictive regression: reliable inference for financial economics," Papers 2008.06130, arXiv.org.
    308. Konstantinos Gkillas & Christoforos Konstantatos & Costas Siriopoulos, 2021. "Uncertainty Due to Infectious Diseases and Stock–Bond Correlation," Econometrics, MDPI, vol. 9(2), pages 1-18, April.
    309. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    310. Mike Buckle & Jing Chen & Julian Williams, 2014. "How Predictable Are Equity Covariance Matrices? Evidence from High‐Frequency Data for Four Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(7), pages 542-557, November.
    311. Yu‐Sheng Lai, 2023. "Optimal futures hedging by using realized semicovariances: The information contained in signed high‐frequency returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(5), pages 677-701, May.
    312. Papageorgiou, Nicolas & Reeves, Jonathan J. & Xie, Xuan, 2016. "Betas and the myth of market neutrality," International Journal of Forecasting, Elsevier, vol. 32(2), pages 548-558.
    313. Rachid Belfadli & Khalifa Es-Sebaiy & Fatima-Ezzahra Farah, 2023. "Volatility Estimation of Gaussian Ornstein–Uhlenbeck Processes of the Second Kind," Journal of Theoretical Probability, Springer, vol. 36(1), pages 1-17, March.

  21. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    See citations under working paper version above.
  22. Ole E. Barndorff‐Nielsen & Richard D. Gill & Peter E. Jupp, 2003. "On quantum statistical inference," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(4), pages 775-804, November.

    Cited by:

    1. Luati, Alessandra & Novelli, Marco, 2021. "Explicit-duration Hidden Markov Models for quantum state estimation," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    2. Jupp, P.E., 2010. "A van Trees inequality for estimators on manifolds," Journal of Multivariate Analysis, Elsevier, vol. 101(8), pages 1814-1825, September.
    3. Luati, Alessandra & Novelli, Marco, 2020. "The Hammersley–Chapman–Robbins inequality for repeatedly monitored quantum system," Statistics & Probability Letters, Elsevier, vol. 165(C).
    4. Vladislav Kargin, 2004. "Coordination Games with Quantum Information," Game Theory and Information 0409006, University Library of Munich, Germany.
    5. Heller, B. & Wang, M., 2007. "Posterior distribution for negative binomial parameter p using a group invariant prior," Statistics & Probability Letters, Elsevier, vol. 77(15), pages 1542-1548, September.
    6. Jamal Anwar, S. & Ramzan, M. & Usman, M. & Khalid Khan, M., 2020. "Thermal and intrinsic decoherence effects on the dynamics of two three-level moving atomic system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    7. Dale, M.B. & Dale, P.E.R. & Tan, P., 2007. "Supervised clustering using decision trees and decision graphs: An ecological comparison," Ecological Modelling, Elsevier, vol. 204(1), pages 70-78.

  23. Ole E. Barndorff‐Nielsen & Neil Shephard, 2003. "Integrated OU Processes and Non‐Gaussian OU‐based Stochastic Volatility Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(2), pages 277-295, June.

    Cited by:

    1. Piergiacomo Sabino & Nicola Cufaro Petroni, 2022. "Fast simulation of tempered stable Ornstein–Uhlenbeck processes," Computational Statistics, Springer, vol. 37(5), pages 2517-2551, November.
    2. Taufer, Emanuele & Leonenko, Nikolai, 2009. "Simulation of Lvy-driven Ornstein-Uhlenbeck processes with given marginal distribution," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2427-2437, April.
    3. Nicola Cufaro Petroni & Piergiacomo Sabino, 2020. "Tempered stable distributions and finite variation Ornstein-Uhlenbeck processes," Papers 2011.09147, arXiv.org.
    4. Ivan Shaliastovich & George Tauchen, 2010. "Pricing of the Time-Change Risks," Working Papers 10-10, Duke University, Department of Economics.
    5. Emanuele Taufer, 2008. "Characteristic function estimation of non-Gaussian Ornstein-Uhlenbeck processes," DISA Working Papers 0805, Department of Computer and Management Sciences, University of Trento, Italy, revised 07 Jul 2008.
    6. Gong, Yaxian, 2020. "Credit default swap and two-sided moral hazard," Finance Research Letters, Elsevier, vol. 34(C).
    7. Toshiro Watanabe & Kouji Yamamuro, 2010. "Local Subexponentiality and Self-decomposability," Journal of Theoretical Probability, Springer, vol. 23(4), pages 1039-1067, December.
    8. Dassios, Angelos & Qu, Yan & Zhao, Hongbiao, 2018. "Exact simulation for a class of tempered stable," LSE Research Online Documents on Economics 86981, London School of Economics and Political Science, LSE Library.
    9. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2021. "Random variate generation for exponential and gamma tilted stable distributions," LSE Research Online Documents on Economics 108593, London School of Economics and Political Science, LSE Library.
    10. Gennady Gorin & John J. Vastola & Meichen Fang & Lior Pachter, 2022. "Interpretable and tractable models of transcriptional noise for the rational design of single-molecule quantification experiments," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    11. Taufer, Emanuele & Leonenko, Nikolai & Bee, Marco, 2011. "Characteristic function estimation of Ornstein-Uhlenbeck-based stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2525-2539, August.
    12. Aziz Issaka & Indranil SenGupta, 2017. "Analysis of variance based instruments for Ornstein–Uhlenbeck type models: swap and price index," Annals of Finance, Springer, vol. 13(4), pages 401-434, November.
    13. Raknerud, Arvid & Skare, Øivind, 2012. "Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein–Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3260-3275.
    14. Ewald, Christian & Zou, Yihan, 2021. "Stochastic volatility: A tale of co-jumps, non-normality, GMM and high frequency data," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 37-52.
    15. Shu, Yin & Feng, Qianmei & Liu, Hao, 2019. "Using degradation-with-jump measures to estimate life characteristics of lithium-ion battery," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. Masuda, H. & Yoshida, N., 2005. "Asymptotic expansion for Barndorff-Nielsen and Shephard's stochastic volatility model," Stochastic Processes and their Applications, Elsevier, vol. 115(7), pages 1167-1186, July.
    17. Gong, Xiaoli & Zhuang, Xintian, 2017. "American option valuation under time changed tempered stable Lévy processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 57-68.
    18. Szczepocki Piotr, 2020. "Application of iterated filtering to stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck process," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 173-187, June.
    19. Lancelot F. James, 2005. "Analysis of a Class of Likelihood Based Continuous Time Stochastic Volatility Models including Ornstein-Uhlenbeck Models in Financial Economics," Papers math/0503055, arXiv.org, revised Aug 2005.
    20. Semere Habtemicael & Indranil SenGupta, 2016. "Pricing variance and volatility swaps for Barndorff-Nielsen and Shephard process driven financial markets," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 1-35, December.
    21. Ballotta, Laura & Rayée, Grégory, 2022. "Smiles & smirks: Volatility and leverage by jumps," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1145-1161.
    22. Creal, Drew D., 2008. "Analysis of filtering and smoothing algorithms for Lévy-driven stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2863-2876, February.
    23. Anzarut, Michelle & Mena, Ramsés H., 2019. "A Harris process to model stochastic volatility," Econometrics and Statistics, Elsevier, vol. 10(C), pages 151-169.
    24. Semere Habtemicael & Musie Ghebremichael & Indranil SenGupta, 2019. "Volatility and Variance Swap Using Superposition of the Barndorff-Nielsen and Shephard type Lévy Processes," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 75-92, June.
    25. Aubain Hilaire Nzokem, 2023. "Pricing European Options under Stochastic Volatility Models: Case of Five-Parameter Variance-Gamma Process," JRFM, MDPI, vol. 16(1), pages 1-28, January.
    26. Mario Abundo & Enrica Pirozzi, 2019. "On the Integral of the Fractional Brownian Motion and Some Pseudo-Fractional Gaussian Processes," Mathematics, MDPI, vol. 7(10), pages 1-12, October.
    27. Abundo, Mario & Pirozzi, Enrica, 2018. "Integrated stationary Ornstein–Uhlenbeck process, and double integral processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 265-275.
    28. Andersson, Patrik & Lagerås, Andreas N., 2013. "Optimal bond portfolios with fixed time to maturity," Insurance: Mathematics and Economics, Elsevier, vol. 53(2), pages 429-438.
    29. P. Brockwell, 2014. "Recent results in the theory and applications of CARMA processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(4), pages 647-685, August.
    30. A. H. Nzokem, 2022. "Pricing European Options under Stochastic Volatility Models: Case of five-Parameter Variance-Gamma Process," Papers 2201.03378, arXiv.org, revised Jan 2023.
    31. Semere Habtemicael & Indranil Sengupta, 2016. "Pricing Covariance Swaps For Barndorff–Nielsen And Shephard Process Driven Financial Markets," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(03), pages 1-32, September.
    32. He, Yue & Kawai, Reiichiro, 2022. "Super- and subdiffusive positions in fractional Klein–Kramers equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    33. Anatoliy Swishchuk, 2013. "Modeling and Pricing of Swaps for Financial and Energy Markets with Stochastic Volatilities," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8660, December.
    34. Stojanović, Vladica S. & Popović, Biljana Č. & Milovanović, Gradimir V., 2016. "The Split-SV model," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 560-581.
    35. Shibin Zhang, 2011. "Transition Law-based Simulation of Generalized Inverse Gaussian Ornstein–Uhlenbeck Processes," Methodology and Computing in Applied Probability, Springer, vol. 13(3), pages 619-656, September.
    36. Piergiacomo Sabino, 2020. "Exact Simulation of Variance Gamma related OU processes: Application to the Pricing of Energy Derivatives," Papers 2004.06786, arXiv.org.

  24. Ole Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2002. "Some recent developments in stochastic volatility modelling," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 11-23.
    See citations under working paper version above.
  25. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.

    Cited by:

    1. Yu-Min Yen, 2013. "Testing Jumps via False Discovery Rate Control," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    2. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    3. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    4. Mattiussi, V. & Iori, G., 2006. "Currency futures volatility during the 1997 East Asian crisis: an application of Fourier analysis," Working Papers 06/09, Department of Economics, City University London.
    5. Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
    6. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    7. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    8. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    9. Dufour, Jean-Marie & García, René & Taamouti, Abderrahim, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    10. Eleftheria Kafousaki & Stavros Degiannakis, 2023. "Forecasting VIX: the illusion of forecast evaluation criteria," Economics and Business Letters, Oviedo University Press, vol. 12(3), pages 231-240.
    11. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    12. Lee, Hwang Hee & Hyun, Jung-Soon, 2019. "The asymmetric effect of equity volatility on credit default swap spreads," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 125-136.
    13. LAHAYE, Jérôme & LAURENT, Sébastien & NEELY, Christopher J., 2011. "Jumps, cojumps and macro announcements," LIDAM Reprints CORE 2413, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Wen Cheong Chin & Min Cherng Lee, 2018. "S&P500 volatility analysis using high-frequency multipower variation volatility proxies," Empirical Economics, Springer, vol. 54(3), pages 1297-1318, May.
    15. Michel Beine & Jerome Lahaye & Sebastien Laurent & Christopher J. Neely & Franz C. Palm, 2007. "Central bank intervention and exchange rate volatility, its continuous and jump components," Working Papers 2006-031, Federal Reserve Bank of St. Louis.
    16. Peter Reinhard Hansen & Asger Lunde, 2005. "A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 525-554.
    17. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    18. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    19. Nour Meddahi, 2002. "A theoretical comparison between integrated and realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 479-508.
    20. Diego Amaya & Jean-François Bégin & Geneviève Gauthier, 2022. "The Informational Content of High-Frequency Option Prices," Management Science, INFORMS, vol. 68(3), pages 2166-2201, March.
    21. Ozcan Ceylan, 2015. "Limited information-processing capacity and asymmetric stock correlations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1031-1039, June.
    22. Vladimir Tsenkov, 2009. "Financial Markets Modelling," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 87-96.
    23. Diebold, Francis X. & Strasser, Georg H., 2008. "On the correlation structure of microstructure noise in theory and practice," CFS Working Paper Series 2008/32, Center for Financial Studies (CFS).
    24. Helmut Herwartz, 2006. "Econometric analysis of high frequency data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 89-104, March.
    25. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    26. Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
    27. Maria Elvira Mancino & Simone Scotti & Giacomo Toscano, 2020. "Is the variance swap rate affine in the spot variance? Evidence from S&P500 data," Papers 2004.04015, arXiv.org.
    28. Tao, Yubo & Phillips, Peter C.B. & Yu, Jun, 2019. "Random coefficient continuous systems: Testing for extreme sample path behavior," Journal of Econometrics, Elsevier, vol. 209(2), pages 208-237.
    29. ANDERSEN, Torben G. & BOLLERSLEV, Tim & MEDDAHI, Nour, 2002. "Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," Cahiers de recherche 2002-21, Universite de Montreal, Departement de sciences economiques.
    30. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    31. Jing-zhi Huang & Hao Zhou, 2008. "Specification analysis of structural credit risk models," Finance and Economics Discussion Series 2008-55, Board of Governors of the Federal Reserve System (U.S.).
    32. Audrino, Francesco & Corsi, Fulvio, 2010. "Modeling tick-by-tick realized correlations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2372-2382, November.
    33. Gao, Yang & Leung, Henry & Satchell, Stephen, 2022. "Partial moment momentum," Journal of Banking & Finance, Elsevier, vol. 135(C).
    34. Laurini, Márcio P., 2007. "Imposing No-Arbitrage Conditions In Implied Volatility Surfaces Using Constrained Smoothing Splines," Insper Working Papers wpe_89, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    35. Arnerić, Josip & Matković, Mario & Sorić, Petar, 2019. "Comparison of range-based volatility estimators against integrated volatility in European emerging markets," Finance Research Letters, Elsevier, vol. 28(C), pages 118-124.
    36. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    37. Ambrogio Cesa-Bianchi & M. Hashem Pesaran & Alessandro Rebucci, 2018. "Uncertainty and Economic Activity: A Multi-Country Perspective," NBER Working Papers 24325, National Bureau of Economic Research, Inc.
    38. Rachidi Kotchoni, 2012. "Applications of the Characteristic Function Based Continuum GMM in Finance," Post-Print hal-00867795, HAL.
    39. Hossein Hassani & Mohammad Reza Yeganegi & Rangan Gupta & Riza Demirer, 2018. "Forecasting Stock Market (Realized) Volatility in the United Kingdom: Is There a Role for Economic Inequality?," Working Papers 201880, University of Pretoria, Department of Economics.
    40. Ilya Archakov & Peter Reinhard Hansen & Asger Lunde, 2020. "A Multivariate Realized GARCH Model," Papers 2012.02708, arXiv.org.
    41. Eric Jondeau & Jérôme Lahaye & Michael Rockinger, 2013. "Estimating the Price Impact of Trades in an High-Frequency Microstructure Model with Jumps," Swiss Finance Institute Research Paper Series 13-47, Swiss Finance Institute, revised Feb 2016.
    42. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2014. "Is Volatility Clustering of Asset Returns Asymmetric?," Working Papers 050, Ryerson University, Department of Economics.
    43. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.
    44. Kamiar Mohaddes & M. Hashem Pesaran, 2013. "One Hundred Years of Oil Income and the Iranian Economy: A Curse or a Blessing?," Working Papers 771, Economic Research Forum, revised Sep 2013.
    45. Benjamin Yibin Zhang & Hao Zhou & Haibin Zhu, 2009. "Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5099-5131, December.
    46. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "Long Memory and Tail dependence in Trading Volume and Volatility," CREATES Research Papers 2009-30, Department of Economics and Business Economics, Aarhus University.
    47. Wei Kuang, 2021. "Conditional covariance matrix forecast using the hybrid exponentially weighted moving average approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1398-1419, December.
    48. John M. Maheu & Thomas H. McCurdy, 2009. "Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions?," Working Paper series 19_09, Rimini Centre for Economic Analysis.
    49. Cavusoglu, Nevin & Goldberg, Michael D. & Stillwagon, Josh, 2021. "Currency returns and downside risk: Debt, volatility, and the gap from benchmark values," Journal of Macroeconomics, Elsevier, vol. 68(C).
    50. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model," CREATES Research Papers 2013-03, Department of Economics and Business Economics, Aarhus University.
    51. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
    52. Yusaku Nishimura & Xuyi Dong & Bianxia Sun, 2021. "Trump's tweets: Sentiment, stock market volatility, and jumps," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 44(3), pages 497-512, September.
    53. Grammig, Joachim G. & Peter, Franziska J., 2008. "International price discovery in the presence of market microstructure effects," CFR Working Papers 08-10, University of Cologne, Centre for Financial Research (CFR).
    54. Jui‐Cheng Hung & Hung‐Chun Liu & J. Jimmy Yang, 2023. "Does the tail risk index matter in forecasting downside risk?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3451-3466, July.
    55. Bryan Lim & Stefan Zohren & Stephen Roberts, 2020. "Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio," Papers 2002.02008, arXiv.org, revised Sep 2020.
    56. Marine Carrasco & Rachidi Kotchoni, 2015. "Adaptive Realized Kernels," Journal of Financial Econometrics, Oxford University Press, vol. 13(4), pages 757-797.
    57. Caloia, Francesco Giuseppe & Cipollini, Andrea & Muzzioli, Silvia, 2018. "Asymmetric semi-volatility spillover effects in EMU stock markets," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 221-230.
    58. Markopoulou, Chrysi E. & Skintzi, Vasiliki D. & Refenes, Apostolos-Paul N., 2016. "Realized hedge ratio: Predictability and hedging performance," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 121-133.
    59. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2007. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," CREATES Research Papers 2007-22, Department of Economics and Business Economics, Aarhus University.
    60. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    61. Lu, Ran & Xu, Wen & Zeng, Hongjun & Zhou, Xiangjing, 2023. "Volatility connectedness among the Indian equity and major commodity markets under the COVID-19 scenario," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1465-1481.
    62. Stefano Grassi & Nima Nonejad & Paolo Santucci De Magistris, 2017. "Forecasting With the Standardized Self‐Perturbed Kalman Filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 318-341, March.
    63. Jia Liu & John M. Maheu, 2018. "Improving Markov switching models using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 297-318, April.
    64. Sergii Pypko, 2015. "Volatility Forecast in Crises and Expansions," JRFM, MDPI, vol. 8(3), pages 1-26, August.
    65. Christian Bontemps & Nour Meddahi, 2002. "Testing Normality: A GMM Approach," CIRANO Working Papers 2002s-63, CIRANO.
    66. de Vilder, Robin G. & Visser, Marcel P., 2007. "Volatility Proxies for Discrete Time Models," MPRA Paper 4917, University Library of Munich, Germany.
    67. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
    68. Francis X. Diebold & Georg H. Strasser, 2008. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," Boston College Working Papers in Economics 693, Boston College Department of Economics, revised 24 Apr 2012.
    69. Taoufik Bouezmarni & Jeroen Rombouts & Abderrahim Taamouti, 2009. "A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality," CIRANO Working Papers 2009s-28, CIRANO.
    70. Joshua C C Chan & Yong Song, 2017. "Measuring inflation expectations uncertainty using high-frequency data," CAMA Working Papers 2017-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    71. Yusaku Nishimura & Yoshiro Tsutsui & Kenjiro Hirayama, 2012. "Return and Volatility Spillovers between Japanese and Chinese Stock Markets FAn Analysis of Overlapping Trading Hours with High-frequency Data," Discussion Papers in Economics and Business 12-01, Osaka University, Graduate School of Economics.
    72. Jin, Miao & Liu, Yu-Jane & Meng, Juanjuan, 2019. "Fat-finger event and risk-taking behavior," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 126-143.
    73. Jim Griffin & Jia Liu & John M. Maheu, 2021. "Bayesian Nonparametric Estimation of Ex Post Variance [Out of Sample Forecasts of Quadratic Variation]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 823-859.
    74. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    75. Liu, Yifan & Popova, Ivilina, 2023. "Threats to central bank independence and exchange rate volatility: High-frequency identification with Trump’s Fed tweets," Finance Research Letters, Elsevier, vol. 53(C).
    76. Massimiliano Caporin & Michael McAleer, 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," Working Papers in Economics 10/58, University of Canterbury, Department of Economics and Finance.
    77. Abramov, Vyacheslav & Klebaner, Fima, 2006. "Forecasting and testing a non-constant volatility," MPRA Paper 207, University Library of Munich, Germany.
    78. Arnerić Josip, 2020. "Realized density estimation using intraday prices," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 1-9, May.
    79. Nishimura, Yusaku & Tsutsui, Yoshiro & Hirayama, Kenjiro, 2018. "Do international investors cause stock market spillovers? Comparing responses of cross-listed stocks between accessible and inaccessible markets," Economic Modelling, Elsevier, vol. 69(C), pages 237-248.
    80. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2014. "A Robust Neighborhood Truncation Approach To Estimation Of Integrated Quarticity," Econometric Theory, Cambridge University Press, vol. 30(1), pages 3-59, February.
    81. Ambrogio Cesa-Bianchi & M. Hashem Pesaran & Alessandro Rebucci, 2014. "Uncertainty and Economic Activity: A Global Perspective," CESifo Working Paper Series 4736, CESifo.
    82. Ahmed, Walid M.A., 2021. "How do Islamic equity markets respond to good and bad volatility of cryptocurrencies? The case of Bitcoin," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    83. Yin Liao & Heather M. Anderson & Farshid Vahid, 2010. "Do Jumps Matter? Forecasting Multivariate Realized Volatility allowing for Common Jumps," Monash Econometrics and Business Statistics Working Papers 11/10, Monash University, Department of Econometrics and Business Statistics.
    84. Adam E Clements & Christopher A Coleman-Fenn & Daniel R Smith, 2011. "Forecasting Equicorrelation," NCER Working Paper Series 72, National Centre for Econometric Research, revised 29 Aug 2011.
    85. Johannes Stübinger & Lucas Schneider, 2019. "Statistical Arbitrage with Mean-Reverting Overnight Price Gaps on High-Frequency Data of the S&P 500," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    86. Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Indirect inference with time series observed with error," CREATES Research Papers 2014-57, Department of Economics and Business Economics, Aarhus University.
    87. LAURENT, Sébastien & VIOLANTE, Francesco, 2012. "Volatility forecasts evaluation and comparison," LIDAM Reprints CORE 2414, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    88. Alizadeh, Amir H. & Huang, Chih-Yueh & Marsh, Ian W., 2021. "Modelling the volatility of TOCOM energy futures: A regime switching realised volatility approach," Energy Economics, Elsevier, vol. 93(C).
    89. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 154-183.
    90. Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
    91. Nath, H. (Mindi) B. & Kim, Jae H. & Brooks, Robert D., 2012. "Realized dual-betas for leading Australian stocks: An evaluation of the estimation methods and the effect of the sampling interval," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 83(C), pages 10-22.
    92. Murat Körs & Mehmet Baha Karan, 2023. "Stock exchange volatility forecasting under market stress with MIDAS regression," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 295-306, January.
    93. Chu, Carlin C.F. & Lam, K.P., 2011. "Modeling intraday volatility: A new consideration," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 388-418, July.
    94. Kerry W. Fendick, 2013. "Pricing and Hedging Derivative Securities with Unknown Local Volatilities," Papers 1309.6164, arXiv.org, revised Oct 2013.
    95. Arnerić Josip & Poklepović Tea & Teai Juin Wen, 2018. "Neural Network Approach in Forecasting Realized Variance Using High-Frequency Data," Business Systems Research, Sciendo, vol. 9(2), pages 18-34, July.
    96. Trung H. Le & Apostolos Kourtis & Raphael Markellos, 2023. "Modeling skewness in portfolio choice," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 734-770, June.
    97. Braione, Manuela & Scholtes, Nicolas K., 2014. "Construction of value-at-risk forecasts under different distributional assumptions within a BEKK framework," LIDAM Discussion Papers CORE 2014059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    98. Silvia Miranda-Agrippino & Hélène Rey, 2015. "US Monetary Policy and the Global Financial Cycle," NBER Working Papers 21722, National Bureau of Economic Research, Inc.
    99. Mapa, Dennis S., 2003. "A Range-Based GARCH Model for Forecasting Volatility," MPRA Paper 21323, University Library of Munich, Germany.
    100. Adam Aleksander Majewski & Giacomo Bormetti & Fulvio Corsi, 2014. "Smile from the Past: A general option pricing framework with multiple volatility and leverage components," Papers 1404.3555, arXiv.org.
    101. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," NBER Technical Working Papers 0279, National Bureau of Economic Research, Inc.
    102. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    103. Ahadzie, Richard Mawulawoe & Jeyasreedharan, Nagaratnam, 2020. "Trading volume and realized higher-order moments in the Australian stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    104. MEDDAHI, Nour, 2002. "ARMA Representation of Integrated and Realized Variances," Cahiers de recherche 2002-20, Universite de Montreal, Departement de sciences economiques.
    105. Hossein Hassani & Mohammad Reza Yeganegi & Rangan Gupta & Riza Demirer, 2022. "Forecasting stock market (realized) volatility in the United Kingdom: Is there a role of inequality?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2146-2152, April.
    106. Oikonomou, Ioannis & Stancu, Andrei & Symeonidis, Lazaros & Wese Simen, Chardin, 2019. "The information content of short-term options," Journal of Financial Markets, Elsevier, vol. 46(C).
    107. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
    108. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," NBER Working Papers 11188, National Bureau of Economic Research, Inc.
    109. Beatriz Vaz de Melo Mendes & Victor Bello Accioly, 2017. "Improving (E)GARCH forecasts with robust realized range measures: Evidence from international markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 631-658, October.
    110. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    111. Simon Clinet & Yoann Potiron, 2021. "Estimation for high-frequency data under parametric market microstructure noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
    112. Mapa, Dennis S., 2004. "A Forecast Comparison of Financial Volatility Models: GARCH (1,1) is not Enough," MPRA Paper 21028, University Library of Munich, Germany.
    113. Fulvio Corsi & Stefano Peluso & Francesco Audrino, 2015. "Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 377-397, April.
    114. Eduardo Rossi & Paolo Santucci de Magistris, 2012. "Estimation of long memory in integrated variance," DEM Working Papers Series 017, University of Pavia, Department of Economics and Management.
    115. Proietti, Tommaso, 2014. "Exponential Smoothing, Long Memory and Volatility Prediction," MPRA Paper 57230, University Library of Munich, Germany.
    116. Jung, R.C. & Maderitsch, R., 2014. "Structural breaks in volatility spillovers between international financial markets: Contagion or mere interdependence?," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 331-342.
    117. Visser, Marcel P., 2008. "Forecasting S&P 500 Daily Volatility using a Proxy for Downward Price Pressure," MPRA Paper 11100, University Library of Munich, Germany.
    118. Nevin Cavusoglu & Michael D. Goldberg & Joshua Stillwagon, 2019. "New Evidence on the Portfolio Balance Approach to Currency Returns," Working Papers Series 89, Institute for New Economic Thinking.
    119. Pogorelova, Polina & Peresetsky, Anatoly, 2020. "Extracting the global stochastic trend from non-synchronous data on the volatility of financial indices," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 53-71.
    120. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, Department of Economics and Business Economics, Aarhus University.
    121. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018.
    122. Vyacheslav Abramov & Fima Klebaner, 2007. "Estimation and Prediction of a Non-Constant Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(1), pages 1-23, March.
    123. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Duration-Based Volatility Estimation," Global COE Hi-Stat Discussion Paper Series gd08-034, Institute of Economic Research, Hitotsubashi University.
    124. Kotkatvuori-Örnberg, Juha, 2016. "Dynamic conditional copula correlation and optimal hedge ratios with currency futures," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 60-69.
    125. Vortelinos, Dimitrios I. & Thomakos, Dimitrios D., 2013. "Nonparametric realized volatility estimation in the international equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 34-45.
    126. Christensen, Bent Jesper & Posch, Olaf & van der Wel, Michel, 2016. "Estimating dynamic equilibrium models using mixed frequency macro and financial data," Journal of Econometrics, Elsevier, vol. 194(1), pages 116-137.
    127. Bent Jesper Christensen & Morten Ø. Nielsen, 2005. "The Implied-realized Volatility Relation With Jumps In Underlying Asset Prices," Working Paper 1186, Economics Department, Queen's University.
    128. Bollerslev, Tim & Zhang, Benjamin Y. B., 2003. "Measuring and modeling systematic risk in factor pricing models using high-frequency data," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 533-558, December.
    129. Torben G. Andersen & Tim Bollerslev & Dobrislav Dobrev, 2007. "No-Arbitrage Semi-Martingale Restrictions for Continuous-Time Volatility Models subject to Leverage Effects, Jumps and i.i.d. Noise: Theory and Testable Distributional Implications," NBER Working Papers 12963, National Bureau of Economic Research, Inc.
    130. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2020. "Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    131. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    132. Olga Cielinska & Andreas Joseph & Ujwal Shreyas & John Tanner & Michalis Vasios, 2017. "Gauging market dynamics using trade repository data: The case of the Swiss franc de-pegging," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Statistical implications of the new financial landscape, volume 43, Bank for International Settlements.
    133. Ehsan Azmoodeh & Esko Valkeila, 2013. "Spectral characterization of the quadratic variation of mixed Brownian–fractional Brownian motion," Statistical Inference for Stochastic Processes, Springer, vol. 16(2), pages 97-112, July.
    134. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.
    135. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2020. "Forecasting value at risk with intra-day return curves," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1023-1038.
    136. Galbraith, John W. & KI[#x1e63]Inbay, Turgut, 2005. "Content horizons for conditional variance forecasts," International Journal of Forecasting, Elsevier, vol. 21(2), pages 249-260.
    137. Yanwei Jia & Xun Yu Zhou, 2021. "Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach," Papers 2108.06655, arXiv.org, revised Feb 2022.
    138. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    139. Majewski, A. A. & Bormetti, G. & Corsi, F., 2013. "Smile from the Past: A general option pricing framework with multiple volatility and leverage components," Working Papers 13/11, Department of Economics, City University London.
    140. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
    141. Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
    142. Jimmy E. Hilliard & Jitka Hilliard, 2012. "Matching non-synchronous observations in derivative markets: choosing windows and efficient estimators," Quantitative Finance, Taylor & Francis Journals, vol. 12(1), pages 49-60, September.
    143. Sutton, Maxwell & Vasnev, Andrey L. & Gerlach, Richard, 2019. "Mixed interval realized variance: A robust estimator of stock price volatility," Econometrics and Statistics, Elsevier, vol. 11(C), pages 43-62.
    144. François-Éric Racicot & Raymond Théoret & Alain Coën, 2008. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 112-124, February.
    145. Chao Yu & Yue Fang & Zeng Li & Bo Zhang & Xujie Zhao, 2014. "Non-Parametric Estimation Of High-Frequency Spot Volatility For Brownian Semimartingale With Jumps," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 572-591, November.
    146. Ying Chen & Wolfgang Härdle & Uta Pigorsch, 2009. "Localized Realized Volatility Modelling," SFB 649 Discussion Papers SFB649DP2009-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    147. Subbotin, Alexandre, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 15(3), pages 94-138.
    148. Daniela Osterrieder & Daniel Ventosa-Santaulària & J. Eduardo Vera-Valdés, 2015. "Unbalanced Regressions and the Predictive Equation," CREATES Research Papers 2015-09, Department of Economics and Business Economics, Aarhus University.
    149. Giorgio Mirone, 2017. "Inference from the futures: ranking the noise cancelling accuracy of realized measures," CREATES Research Papers 2017-24, Department of Economics and Business Economics, Aarhus University.
    150. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    151. Chao YU & Xujie ZHAO, 2021. "Measuring the Jump Risk Contribution under Market Microstructure Noise – Evidence from Chinese Stock Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 32-47, December.
    152. Wanidwaranan, Phasin & Padungsaksawasdi, Chaiyuth, 2020. "The effect of return jumps on herd behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    153. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2022. "A moving average heterogeneous autoregressive model for forecasting the realized volatility of the US stock market: Evidence from over a century of data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 384-400, January.
    154. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    155. Bucci, Andrea, 2019. "Cholesky-ANN models for predicting multivariate realized volatility," MPRA Paper 95137, University Library of Munich, Germany.
    156. Ortas, E. & Salvador, M. & Moneva, J.M., 2015. "Improved beta modeling and forecasting: An unobserved component approach with conditional heteroscedastic disturbances," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 27-51.
    157. Papantonis Ioannis & Tzavalis Elias & Agapitos Orestis & Rompolis Leonidas S., 2023. "Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 171-198, April.
    158. Qi Wang & Zerong Wang, 2021. "VIX futures and its closed‐form pricing through an affine GARCH model with realized variance," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 135-156, January.
    159. Li, Shaoyu & Zheng, Tingguo, 2017. "Modeling spot rate using a realized stochastic volatility model with level effect and dynamic drift☆," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 200-221.
    160. Johnson, James A. & Medeiros, Marcelo C. & Paye, Bradley S., 2022. "Jumps in stock prices: New insights from old data," Journal of Financial Markets, Elsevier, vol. 60(C).
    161. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A boosting approach to forecasting the volatility of gold-price fluctuations under flexible loss," Resources Policy, Elsevier, vol. 47(C), pages 95-107.
    162. Kshatriya, Saranya & Prasanna, Krishna, 2021. "Jump Interdependencies: Stochastic linkages among international stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    163. Triantafyllou, Athanasios & Dotsis, George, 2017. "Option-implied expectations in commodity markets and monetary policy," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 1-17.
    164. Ceylan, Ozcan, 2012. "Time-Varying Volatility Asymmetry: A Conditioned HAR-RV(CJ) EGARCH-M Model," GIAM Working Papers 12-4, Galatasaray University Economic Research Center.
    165. Bart Frijns & Dimitris Margaritis, 2008. "Forecasting daily volatility with intraday data," The European Journal of Finance, Taylor & Francis Journals, vol. 14(6), pages 523-540.
    166. Ao Kong & Hongliang Zhu & Robert Azencott, 2021. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 416-438, April.
    167. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2005. "Forecasting Exchange Rate Volatility In The Presence Of Jumps," Working Paper 1187, Economics Department, Queen's University.
    168. Mahan Tahvildari, 2021. "Forward indifference valuation and hedging of basis risk under partial information," Papers 2101.00251, arXiv.org.
    169. Richard D. F. Harris & Jian Shen & Evarist Stoja, 2010. "The Limits to Minimum‐Variance Hedging," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(5‐6), pages 737-761, June.
    170. Elena Andreou & Eric Ghysels, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," CIRANO Working Papers 2004s-25, CIRANO.
    171. Majewski, Adam A. & Bormetti, Giacomo & Corsi, Fulvio, 2015. "Smile from the past: A general option pricing framework with multiple volatility and leverage components," Journal of Econometrics, Elsevier, vol. 187(2), pages 521-531.
    172. Xiaoxi Liu & Jinming Xie, 2023. "Forecasting swap rate volatility with information from swaptions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(4), pages 455-479, April.
    173. Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.
    174. Ranaldo, Angelo & de Magistris, Paolo Santucci, 2022. "Liquidity in the global currency market," Journal of Financial Economics, Elsevier, vol. 146(3), pages 859-883.
    175. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Petropoulou, Athina & Sivaprasad, Sheeja, 2023. "The impact of the Russian-Ukrainian war on global financial markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    176. Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
    177. Chunliang Deng & Xingfa Zhang & Yuan Li & Qiang Xiong, 2020. "Garch Model Test Using High-Frequency Data," Mathematics, MDPI, vol. 8(11), pages 1-17, November.
    178. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(4), pages 445-463, October.
    179. Chin Wen CHEONG & Lee Min CHERNG & Grace Lee Ching YAP, 2016. "Heterogeneous Market Hypothesis Evaluations using Various Jump-Robust Realized Volatility," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 50-64, December.
    180. Haselmann, Rainer & Herwartz, Helmut, 2008. "Portfolio performance and the Euro: Prospects for new potential EMU members," Journal of International Money and Finance, Elsevier, vol. 27(2), pages 314-330, March.
    181. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    182. Yusaku Nishimura & Yoshiro Tsutsui & Kenjiro Hirayama, 2017. "Do International Investors Cause Stock Market Comovements? Comparing Responses of Cross-Listed Stocks between Accessible and Inaccessible Markets," Discussion Papers in Economics and Business 17-01, Osaka University, Graduate School of Economics.
    183. Zhang, Hanyu & Dufour, Alfonso, 2019. "Modeling intraday volatility of European bond markets: A data filtering application," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 131-146.
    184. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Analytic Evaluation of Volatility Forecasts," CIRANO Working Papers 2002s-90, CIRANO.
    185. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Density Estimators for Daily Volatility Based on the Use of Realized Measures," Departmental Working Papers 200620, Rutgers University, Department of Economics.
    186. Yin Liao, 2012. "Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction," CAMA Working Papers 2012-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    187. Yu, Chao & Fang, Yue & Zhao, Xujie & Zhang, Bo, 2013. "Kernel filtering of spot volatility in presence of Lévy jumps and market microstructure noise," MPRA Paper 63293, University Library of Munich, Germany, revised 10 Mar 2014.
    188. Elezovic, Suad, 2009. "Functional modelling of volatility in the Swedish limit order book," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2107-2118, April.
    189. Corsi, Fulvio & Fusari, Nicola & La Vecchia, Davide, 2013. "Realizing smiles: Options pricing with realized volatility," Journal of Financial Economics, Elsevier, vol. 107(2), pages 284-304.
    190. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    191. Gero Junike & Wim Schoutens & Hauke Stier, 2022. "Performance of advanced stock price models when it becomes exotic: an empirical study," Annals of Finance, Springer, vol. 18(1), pages 109-119, March.
    192. Audrino, Francesco & Camponovo, Lorenzo & Roth, Constantin, 2015. "Testing the lag structure of assets’ realized volatility dynamics," Economics Working Paper Series 1501, University of St. Gallen, School of Economics and Political Science.
    193. Prateek Sharma & Swati Sharma, 2015. "Forecasting gains of robust realized variance estimators: evidence from European stock markets," Economics Bulletin, AccessEcon, vol. 35(1), pages 61-69.
    194. Nishimura, Yusaku & Sun, Bianxia, 2021. "President’s Tweets, US-China economic conflict and stock market Volatility: Evidence from China and G5 countries," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    195. Kakinaka, Shinji & Umeno, Ken, 2022. "Asymmetric volatility dynamics in cryptocurrency markets on multi-time scales," Research in International Business and Finance, Elsevier, vol. 62(C).
    196. Morelli, Giacomo & Santucci de Magistris, Paolo, 2019. "Volatility tail risk under fractionality," Journal of Banking & Finance, Elsevier, vol. 108(C).
    197. Kuang, Wei, 2022. "The economic value of high-frequency data in equity-oil hedge," Energy, Elsevier, vol. 239(PA).
    198. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.
    199. Grané, Aurea & Veiga, Helena, 2007. "The effect of realised volatility on stock returns risk estimates," DES - Working Papers. Statistics and Econometrics. WS ws076316, Universidad Carlos III de Madrid. Departamento de Estadística.
    200. Huang, Alex YiHou, 2016. "Impacts of implied volatility on stock price realized jumps," Economic Systems, Elsevier, vol. 40(4), pages 622-630.
    201. Robin de Vilder & Marcel P. Visser, 2007. "Proxies for daily volatility," PSE Working Papers halshs-00588307, HAL.
    202. Ao Kong & Hongliang Zhu & Robert Azencott, 2019. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Papers 1912.07165, arXiv.org.
    203. I‐Ming Jiang & Jui‐Cheng Hung & Chuan‐San Wang, 2014. "Volatility Forecasts: Do Volatility Estimators and Evaluation Methods Matter?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(11), pages 1077-1094, November.
    204. Tseng Tseng-Chan & Chung Huimin & Huang Chin-Sheng, 2009. "Modeling Jump and Continuous Components in the Volatility of Oil Futures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-30, May.
    205. Zhang, Zhikai & Wang, Yudong & Li, Bin, 2023. "Asymmetric spillover of geopolitical risk and oil price volatility: A global perspective," Resources Policy, Elsevier, vol. 83(C).
    206. Rey, Hélène & Miranda-Agrippino, Silvia, 2015. "World Asset Markets and the Global Financial Cycle," CEPR Discussion Papers 10936, C.E.P.R. Discussion Papers.
    207. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
    208. Brian Ning & Franco Ho Ting Lin & Sebastian Jaimungal, 2018. "Double Deep Q-Learning for Optimal Execution," Papers 1812.06600, arXiv.org, revised Jun 2020.
    209. Maria Čuljak & Josip Arnerić & Ante Žigman, 2022. "Is Jump Robust Two Times Scaled Estimator Superior among Realized Volatility Competitors?," Mathematics, MDPI, vol. 10(12), pages 1-11, June.
    210. Biao Guo & Hai Lin, 2020. "Volatility and jump risk in option returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1767-1792, November.
    211. Hung, Jui-Cheng, 2015. "Evaluation of realized multi-power variations in minimum variance hedging," Economic Modelling, Elsevier, vol. 51(C), pages 672-679.
    212. Takuo Higashide & Katsuyuki Tanaka & Takuji Kinkyo & Shigeyuki Hamori, 2021. "New Dataset for Forecasting Realized Volatility: Is the Tokyo Stock Exchange Co-Location Dataset Helpful for Expansion of the Heterogeneous Autoregressive Model in the Japanese Stock Market?," JRFM, MDPI, vol. 14(5), pages 1-18, May.
    213. Liang, Chao & Li, Yan & Ma, Feng & Wei, Yu, 2021. "Global equity market volatilities forecasting: A comparison of leverage effects, jumps, and overnight information," International Review of Financial Analysis, Elsevier, vol. 75(C).
    214. Laurini, Márcio Poletti & Hotta, Luiz Koodi, 2013. "Indirect Inference in fractional short-term interest rate diffusions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 109-126.
    215. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
    216. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    217. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    218. Byounghyun Jeon & Sung Won Seo & Jun Sik Kim, 2020. "Uncertainty and the volatility forecasting power of option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1109-1126, July.
    219. Lucas Schneider & Johannes Stübinger, 2020. "Dispersion Trading Based on the Explanatory Power of S&P 500 Stock Returns," Mathematics, MDPI, vol. 8(9), pages 1-22, September.
    220. Fulvio Corsi & Francesco Audrino, 2007. "Realized Correlation Tick-by-Tick," University of St. Gallen Department of Economics working paper series 2007 2007-02, Department of Economics, University of St. Gallen.
    221. Xiaoxi Liu & Jinming Xie, 2023. "Forecasting swap rate volatility with information from swaptions," BIS Working Papers 1068, Bank for International Settlements.
    222. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    223. Kumar, Dilip, 2017. "Realized volatility transmission from crude oil to equity sectors: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 149-167.

  26. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    See citations under working paper version above.
  27. O.E. Barndorff-Nielsen & S.Z. Levendorskii, 2001. "Feller processes of normal inverse Gaussian type," Quantitative Finance, Taylor & Francis Journals, vol. 1(3), pages 318-331, March.

    Cited by:

    1. Kurosaki Tetsuo & Kim Young Shin, 2019. "Foster-Hart optimization for currency portfolios," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-15, April.
    2. Jing Li & Lingfei Li & Rafael Mendoza-Arriaga, 2016. "Additive subordination and its applications in finance," Finance and Stochastics, Springer, vol. 20(3), pages 589-634, July.
    3. Jirô Akahori & Takahiro Tsuchiya, 2006. "What is the Natural Scale for a Lévy Process in Modelling Term Structure of Interest Rates?," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 13(4), pages 299-313, December.
    4. Young Shin Kim & Kum-Hwan Roh & Raphael Douady, 2020. "Tempered Stable Processes with Time Varying Exponential Tails," Papers 2006.07669, arXiv.org, revised Aug 2020.
    5. Sung Ik Kim, 2022. "ARMA–GARCH model with fractional generalized hyperbolic innovations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    6. Young Shin Kim, 2018. "First Passage Time for Tempered Stable Process and Its Application to Perpetual American Option and Barrier Option Pricing," Papers 1801.09362, arXiv.org.
    7. Jose Cruz & Daniel Sevcovic, 2020. "On solutions of a partial integro-differential equation in Bessel potential spaces with applications in option pricing models," Papers 2003.03851, arXiv.org.
    8. Neil Shephard & Ole E. Barndorff-Nielsen, 2012. "Basics of Levy processes," Economics Series Working Papers 610, University of Oxford, Department of Economics.
    9. Kim, Young Shin & Lee, Jaesung & Mittnik, Stefan & Park, Jiho, 2015. "Quanto option pricing in the presence of fat tails and asymmetric dependence," Journal of Econometrics, Elsevier, vol. 187(2), pages 512-520.
    10. Sergei Levendorskiĭ, 2022. "Operators and Boundary Problems in Finance, Economics and Insurance: Peculiarities, Efficient Methods and Outstanding Problems," Mathematics, MDPI, vol. 10(7), pages 1-36, March.
    11. Young Shin Kim, 2022. "Portfolio optimization and marginal contribution to risk on multivariate normal tempered stable model," Annals of Operations Research, Springer, vol. 312(2), pages 853-881, May.
    12. Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2018. "SINH-acceleration: efficient evaluation of probability distributions, option pricing, and Monte-Carlo simulations," Papers 1808.05295, arXiv.org.
    13. Florian Kleinert & Kees van Schaik, 2013. "A variation of the Canadisation algorithm for the pricing of American options driven by L\'evy processes," Papers 1304.4534, arXiv.org.
    14. Young Shin Kim, 2019. "Tempered stable process, first passage time, and path-dependent option pricing," Computational Management Science, Springer, vol. 16(1), pages 187-215, February.
    15. Daniel Sevcovic & Cyril Izuchukwu Udeani, 2021. "Multidimensional linear and nonlinear partial integro-differential equation in Bessel potential spaces with applications in option pricing," Papers 2106.10498, arXiv.org.
    16. Jose Cruz & Daniel Sevcovic, 2019. "Option Pricing in Illiquid Markets with Jumps," Papers 1901.06467, arXiv.org.
    17. Tiantian Li & Young Shin Kim & Qi Fan & Fumin Zhu, 2021. "Aumann–Serrano index of risk in portfolio optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(2), pages 197-217, October.
    18. Lingfei Li & Vadim Linetsky, 2015. "Discretely monitored first passage problems and barrier options: an eigenfunction expansion approach," Finance and Stochastics, Springer, vol. 19(4), pages 941-977, October.
    19. Lingfei Li & Vadim Linetsky, 2013. "Optimal Stopping and Early Exercise: An Eigenfunction Expansion Approach," Operations Research, INFORMS, vol. 61(3), pages 625-643, June.
    20. McCulloch, James, 2012. "Fractal market time," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 686-701.
    21. Anand, Abhinav & Li, Tiantian & Kurosaki, Tetsuo & Kim, Young Shin, 2016. "Foster–Hart optimal portfolios," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 117-130.
    22. Young Shin Kim & Hyangju Kim & Jaehyung Choi, 2023. "Deep Calibration With Artificial Neural Network: A Performance Comparison on Option Pricing Models," Papers 2303.08760, arXiv.org.
    23. Cheng Peng & Young Shin Kim & Stefan Mittnik, 2020. "Portfolio Optimization on Multivariate Regime Switching GARCH Model with Normal Tempered Stable Innovation," Papers 2009.11367, arXiv.org, revised Feb 2023.
    24. Lin, Zuodong & Rachev, Svetlozar T. & Kim, Young Shin & Fabozzi, Frank J., 2012. "Option pricing with regime switching tempered stable processes," Working Paper Series in Economics 43, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    25. Lim, Dongjae & Li, Lingfei & Linetsky, Vadim, 2012. "Evaluating callable and putable bonds: An eigenfunction expansion approach," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1888-1908.
    26. Oleg Kudryavtsev & Antonino Zanette, 2013. "Efficient pricing of swing options in L�vy-driven models," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 627-635, March.
    27. Yuhao Liu & Petar M. Djurić & Young Shin Kim & Svetlozar T. Rachev & James Glimm, 2021. "Systemic Risk Modeling with Lévy Copulas," JRFM, MDPI, vol. 14(6), pages 1-20, June.
    28. Farouk Mselmi, 2022. "Generalized linear model for subordinated Lévy processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 772-801, June.
    29. Abhinav Anand & Tiantian Li & Tetsuo Kurosaki & Young Shin Kim, 2017. "The equity risk posed by the too-big-to-fail banks: a Foster–Hart estimation," Annals of Operations Research, Springer, vol. 253(1), pages 21-41, June.
    30. Kleinert, Florian & van Schaik, Kees, 2015. "A variation of the Canadisation algorithm for the pricing of American options driven by Lévy processes," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 3234-3254.
    31. Oleg Kudryavtsev, 2010. "Efficient pricing options under regime switching," Working Papers inria-00450291, HAL.
    32. James McCulloch, 2012. "Fractal Market Time," Research Paper Series 311, Quantitative Finance Research Centre, University of Technology, Sydney.
    33. Young Shin Kim, 2020. "Portfolio Optimization on the Dispersion Risk and the Asymmetric Tail Risk," Papers 2007.13972, arXiv.org, revised Sep 2020.
    34. Li, Jing & Li, Lingfei & Zhang, Gongqiu, 2017. "Pure jump models for pricing and hedging VIX derivatives," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 28-55.
    35. Holger Fink & Stefan Mittnik, 2021. "Quanto Pricing beyond Black–Scholes," JRFM, MDPI, vol. 14(3), pages 1-27, March.
    36. Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2023. "Efficient inverse $Z$-transform: sufficient conditions," Papers 2305.10725, arXiv.org.
    37. H. Fink & S. Geissel & J. Sass & F. T. Seifried, 2019. "Implied risk aversion: an alternative rating system for retail structured products," Review of Derivatives Research, Springer, vol. 22(3), pages 357-387, October.
    38. Young Kim & Svetlozar Rachev & Michele Bianchi & Frank Fabozzi, 2009. "Computing VAR and AVaR in Infinitely Divisible Distributions," Yale School of Management Working Papers amz2569, Yale School of Management.
    39. Björn Böttcher, 2010. "Feller Processes: The Next Generation in Modeling. Brownian Motion, Lévy Processes and Beyond," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-8, December.
    40. Sergei Levendorskiĭ, 2017. "ULTRA-FAST PRICING BARRIER OPTIONS AND CDSs," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(05), pages 1-27, August.
    41. Imai Junichi, 2013. "Comparison of random number generators via Fourier transform," Monte Carlo Methods and Applications, De Gruyter, vol. 19(3), pages 237-259, October.
    42. Sung Ik Kim & Young Shin Kim, 2018. "Tempered stable structural model in pricing credit spread and credit default swap," Review of Derivatives Research, Springer, vol. 21(1), pages 119-148, April.
    43. Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2022. "L\'evy models amenable to efficient calculations," Papers 2207.02359, arXiv.org.
    44. Young Shin Kim, 2023. "Portfolio Optimization with Relative Tail Risk," Papers 2303.12209, arXiv.org, revised Mar 2023.
    45. Alexander Kushpel, 2015. "Pricing of high-dimensional options," Papers 1510.07221, arXiv.org.
    46. Hassan A. Fallahgoul & Young S. Kim & Frank J. Fabozzi, 2016. "Elliptical tempered stable distribution," Quantitative Finance, Taylor & Francis Journals, vol. 16(7), pages 1069-1087, July.

  28. Ole E. Barndorff-Nielsen & Karsten Prause, 2001. "Apparent scaling," Finance and Stochastics, Springer, vol. 5(1), pages 103-113.

    Cited by:

    1. Neil Shephard & Ole E. Barndorff-Nielsen, 2012. "Basics of Levy processes," Economics Series Working Papers 610, University of Oxford, Department of Economics.
    2. Scott, David J & Würtz, Diethelm & Dong, Christine & Tran, Thanh Tam, 2009. "Moments of the generalized hyperbolic distribution," MPRA Paper 19081, University Library of Munich, Germany.
    3. Diongue, Abdou Kâ & Guégan, Dominique, 2007. "The stationary seasonal hyperbolic asymmetric power ARCH model," Statistics & Probability Letters, Elsevier, vol. 77(11), pages 1158-1164, June.
    4. Segnon, Mawuli & Lux, Thomas, 2013. "Multifractal models in finance: Their origin, properties, and applications," Kiel Working Papers 1860, Kiel Institute for the World Economy (IfW Kiel).
    5. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
    6. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    7. Karlis, Dimitris, 2002. "An EM type algorithm for maximum likelihood estimation of the normal-inverse Gaussian distribution," Statistics & Probability Letters, Elsevier, vol. 57(1), pages 43-52, March.
    8. Alexander Kushpel, 2015. "Pricing of high-dimensional options," Papers 1510.07221, arXiv.org.
    9. Antonis Papapantoleon, 2008. "An introduction to L\'{e}vy processes with applications in finance," Papers 0804.0482, arXiv.org, revised Nov 2008.

  29. Ole E. Barndorff‐Nielsen & Neil Shephard, 2001. "Non‐Gaussian Ornstein–Uhlenbeck‐based models and some of their uses in financial economics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 167-241.

    Cited by:

    1. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    2. Alessandro Bondi & Sergio Pulido & Simone Scotti, 2022. "The rough Hawkes Heston stochastic volatility model," Working Papers hal-03827332, HAL.
    3. Richter, Anja, 2014. "Explicit solutions to quadratic BSDEs and applications to utility maximization in multivariate affine stochastic volatility models," Stochastic Processes and their Applications, Elsevier, vol. 124(11), pages 3578-3611.
    4. Thomas Gkelsinis & Alex Karagrigoriou, 2020. "Theoretical Aspects on Measures of Directed Information with Simulations," Mathematics, MDPI, vol. 8(4), pages 1-13, April.
    5. E. A. Pchelintsev & S. M. Pergamenshchikov, 2018. "Oracle inequalities for the stochastic differential equations," Statistical Inference for Stochastic Processes, Springer, vol. 21(2), pages 469-483, July.
    6. Gonçalo Faria & João Correia-da-Silva, 2014. "A closed-form solution for options with ambiguity about stochastic volatility," Review of Derivatives Research, Springer, vol. 17(2), pages 125-159, July.
    7. Madan, Dilip B. & Wang, King, 2021. "The structure of financial returns," Finance Research Letters, Elsevier, vol. 40(C).
    8. Gradojevic Nikola, 2016. "Multi-criteria classification for pricing European options," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(2), pages 123-139, April.
    9. Ferland, Rene & Lalancette, Simon, 2006. "Dynamics of realized volatilities and correlations: An empirical study," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2109-2130, July.
    10. Jiang, Bibo & Lu, Ye & Park, Joon Y., 2018. "Testing for Stationarity at High Frequency," Working Papers 2018-09, University of Sydney, School of Economics.
    11. Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
    12. Long, Hongwei & Ma, Chunhua & Shimizu, Yasutaka, 2017. "Least squares estimators for stochastic differential equations driven by small Lévy noises," Stochastic Processes and their Applications, Elsevier, vol. 127(5), pages 1475-1495.
    13. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    14. Dimitrios Thomakos & Michail Koubouros, 2008. "The Role of Realized Volatility in the Athens Stock Exchange," Working Papers 0020, University of Peloponnese, Department of Economics.
    15. Brix, Anne Floor & Lunde, Asger & Wei, Wei, 2018. "A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method," Energy Economics, Elsevier, vol. 72(C), pages 560-582.
    16. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    17. Nicholas Apergis & Christina Christou & Stephen M. Miller, 2011. "Country and Industry Convergence of Equity Markets: International Evidence from Club Convergence and Clustering," Working Papers 1105, University of Nevada, Las Vegas , Department of Economics.
    18. Jun Yu & Zhenlin Yang & Xibin Zhang, 2002. "A Class of Nonlinear Stochastic Volatility Models and Its Implications on Pricing Currency Options," Monash Econometrics and Business Statistics Working Papers 17/02, Monash University, Department of Econometrics and Business Statistics.
    19. Bannör, Karl & Kiesel, Rüdiger & Nazarova, Anna & Scherer, Matthias, 2016. "Parametric model risk and power plant valuation," Energy Economics, Elsevier, vol. 59(C), pages 423-434.
    20. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    21. Viktor Todorov & George Tauchen & Iaryna Grynkiv, 2011. "Volatility Activity: Specification and Estimation," Working Papers 11-23, Duke University, Department of Economics.
    22. Kumar, Rohini & Popovic, Lea, 2017. "Large deviations for multi-scale jump-diffusion processes," Stochastic Processes and their Applications, Elsevier, vol. 127(4), pages 1297-1320.
    23. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    24. Piergiacomo Sabino & Nicola Cufaro Petroni, 2022. "Fast simulation of tempered stable Ornstein–Uhlenbeck processes," Computational Statistics, Springer, vol. 37(5), pages 2517-2551, November.
    25. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    26. Marco Minozzo & Silvia Centanni, 2012. "Monte Carlo likelihood inference for marked doubly stochastic Poisson processes with intensity driven by marked point processes," Working Papers 11/2012, University of Verona, Department of Economics.
    27. Taufer, Emanuele & Leonenko, Nikolai, 2009. "Simulation of Lvy-driven Ornstein-Uhlenbeck processes with given marginal distribution," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2427-2437, April.
    28. Nicola Cufaro Petroni & Piergiacomo Sabino, 2020. "Tempered stable distributions and finite variation Ornstein-Uhlenbeck processes," Papers 2011.09147, arXiv.org.
    29. Ioannis Kyriakou & Panos K. Pouliasis & Nikos C. Papapostolou, 2016. "Jumps and stochastic volatility in crude oil prices and advances in average option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1859-1873, December.
    30. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    31. Fred Benth & Nils Detering, 2015. "Pricing and hedging Asian-style options on energy," Finance and Stochastics, Springer, vol. 19(4), pages 849-889, October.
    32. Larsson, Karl & Nossman, Marcus, 2011. "Jumps and stochastic volatility in oil prices: Time series evidence," Energy Economics, Elsevier, vol. 33(3), pages 504-514, May.
    33. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    34. Ivan Shaliastovich & George Tauchen, 2010. "Pricing of the Time-Change Risks," Working Papers 10-10, Duke University, Department of Economics.
    35. Liang Wang & Weixuan Xia, 2022. "Power‐type derivatives for rough volatility with jumps," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1369-1406, July.
    36. Carl Lindberg, 2008. "The estimation of the Barndorff‐Nielsen and Shephard model from daily data based on measures of trading intensity," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(4), pages 277-289, July.
    37. Zeddouk, Fadoua & Devolder, Pierre, 2019. "Mean reversion in stochastic mortality : why and how?," LIDAM Discussion Papers ISBA 2019018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    38. George Tauchen & Viktor Todorov, 2010. "Activity Signature Functions for High-Frequency Data Analysis," Working Papers 10-08, Duke University, Department of Economics.
    39. Giulia Di Nunno & Kęstutis Kubilius & Yuliya Mishura & Anton Yurchenko-Tytarenko, 2023. "From Constant to Rough: A Survey of Continuous Volatility Modeling," Mathematics, MDPI, vol. 11(19), pages 1-35, October.
    40. Vladimir Tsenkov, 2009. "Financial Markets Modelling," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 87-96.
    41. Lars Forsberg & Tim Bollerslev, 2002. "Bridging the gap between the distribution of realized (ECU) volatility and ARCH modelling (of the Euro): the GARCH-NIG model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 535-548.
    42. Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    43. Fulvio Corsi & Francesco Audrino, 2012. "Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 591-616, September.
    44. Tetsuya Takaishi, 2019. "Rough volatility of Bitcoin," Papers 1904.12346, arXiv.org.
    45. Lars Stentoft, 2008. "American Option Pricing Using GARCH Models and the Normal Inverse Gaussian Distribution," Journal of Financial Econometrics, Oxford University Press, vol. 6(4), pages 540-582, Fall.
    46. Sébastien Laurent & Shuping Shi, 2018. "Volatility Estimation and Jump Detection for drift-diffusion Processes," Working Papers halshs-01944449, HAL.
    47. Fred Espen Benth & Martin Groth & Rodwell Kufakunesu, 2007. "Valuing Volatility and Variance Swaps for a Non-Gaussian Ornstein-Uhlenbeck Stochastic Volatility Model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(4), pages 347-363.
    48. Mariani, Maria C. & Tweneboah, Osei K., 2016. "Stochastic differential equations applied to the study of geophysical and financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 170-178.
    49. Takuji Arai & Yuto Imai, 2024. "Option pricing for Barndorff-Nielsen and Shephard model by supervised deep learning," Papers 2402.00445, arXiv.org.
    50. Alvaro Cartea & Marcelo Figueroa & Helyette Geman, 2009. "Modelling Electricity Prices with Forward Looking Capacity Constraints," Applied Mathematical Finance, Taylor & Francis Journals, vol. 16(2), pages 103-122.
    51. Maria Elvira Mancino & Simone Scotti & Giacomo Toscano, 2020. "Is the variance swap rate affine in the spot variance? Evidence from S&P500 data," Papers 2004.04015, arXiv.org.
    52. ANDERSEN, Torben G. & BOLLERSLEV, Tim & MEDDAHI, Nour, 2002. "Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," Cahiers de recherche 2002-21, Universite de Montreal, Departement de sciences economiques.
    53. Ulrich Hounyo & Silvia Gonçalves & Nour Meddahi, 2016. "Bootstrapping pre-averaged realized volatility under market microstructure noise," CIRANO Working Papers 2016s-25, CIRANO.
    54. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    55. Murray, Paula M. & Browne, Ryan P. & McNicholas, Paul D., 2014. "Mixtures of skew-t factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 326-335.
    56. Audrino, Francesco & Corsi, Fulvio, 2010. "Modeling tick-by-tick realized correlations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2372-2382, November.
    57. Gong, Yaxian, 2020. "Credit default swap and two-sided moral hazard," Finance Research Letters, Elsevier, vol. 34(C).
    58. Behme, Anita & Lindner, Alexander & Reker, Jana & Rivero, Victor, 2021. "Continuity properties and the support of killed exponential functionals," Stochastic Processes and their Applications, Elsevier, vol. 140(C), pages 115-146.
    59. Erhan Bayraktar & Li Chen & H. Vincent Poor, 2005. "Consistency Problems for Jump-diffusion Models," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(2), pages 101-119.
    60. Fengler, Matthias & Melnikov, Alexander, 2017. "GARCH option pricing models with Meixner innovations," Economics Working Paper Series 1702, University of St. Gallen, School of Economics and Political Science.
    61. Michael Roberts & Indranil SenGupta, 2020. "Sequential hypothesis testing in machine learning, and crude oil price jump size detection," Papers 2004.08889, arXiv.org, revised Dec 2020.
    62. Bjørn Eraker & Ivan Shaliastovich, 2008. "An Equilibrium Guide To Designing Affine Pricing Models," Mathematical Finance, Wiley Blackwell, vol. 18(4), pages 519-543, October.
    63. Shantanu Awasthi & Indranil SenGupta, 2020. "First exit-time analysis for an approximate Barndorff-Nielsen and Shephard model with stationary self-decomposable variance process," Papers 2006.07167, arXiv.org, revised Jan 2021.
    64. Hanieh Panahi, 2016. "Model Selection Test for the Heavy-Tailed Distributions under Censored Samples with Application in Financial Data," IJFS, MDPI, vol. 4(4), pages 1-14, December.
    65. Wieger Hinderks & Andreas Wagner & Ralf Korn, 2018. "A structural Heath-Jarrow-Morton framework for consistent intraday, spot, and futures electricity prices," Papers 1803.08831, arXiv.org, revised Jan 2019.
    66. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    67. Roberto Leon-Gonzalez, 2014. "Efficient Bayesian Inference in Generalized Inverse Gamma Processes for Stochastic Volatility," Working Paper series 19_14, Rimini Centre for Economic Analysis.
    68. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    69. Masato Ubukata & Toshiaki Watanabe, 2014. "Pricing Nikkei 225 Options Using Realized Volatility," The Japanese Economic Review, Japanese Economic Association, vol. 65(4), pages 431-467, December.
    70. Julie Lyng Forman & Michael Sørensen, 2008. "The Pearson Diffusions: A Class of Statistically Tractable Diffusion Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(3), pages 438-465, September.
    71. Gonzalez, Jhonny & Moriarty, John & Palczewski, Jan, 2017. "Bayesian calibration and number of jump components in electricity spot price models," Energy Economics, Elsevier, vol. 65(C), pages 375-388.
    72. Rama Cont & Peter Tankov, 2009. "Constant proportion portfolio insurance in presence of jumps in asset prices," Post-Print hal-00445646, HAL.
    73. Lars Forsberg & Eric Ghysels, 2007. "Why Do Absolute Returns Predict Volatility So Well?," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 31-67.
    74. Till Massing, 2018. "Simulation of Student–Lévy processes using series representations," Computational Statistics, Springer, vol. 33(4), pages 1649-1685, December.
    75. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    76. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2014. "Is Volatility Clustering of Asset Returns Asymmetric?," Working Papers 050, Ryerson University, Department of Economics.
    77. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.
    78. Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus, 2004. "Multipower Variation and Stochastic Volatility," Economics Series Working Papers 2004-FE-22, University of Oxford, Department of Economics.
    79. Brockwell, Peter J. & Schlemm, Eckhard, 2013. "Parametric estimation of the driving Lévy process of multivariate CARMA processes from discrete observations," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 217-251.
    80. Torben G. Andersen & Luca Benzoni, 2010. "Do Bonds Span Volatility Risk in the U.S. Treasury Market? A Specification Test for Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 65(2), pages 603-653, April.
    81. Cartea, Álvaro & Meyer-Brandis, Thilo, 2009. "How Duration Between Trades of Underlying Securities Affects Option Prices," MPRA Paper 16179, University Library of Munich, Germany.
    82. Dimitrios D. Thomakos & Michail S. Koubouros, 2005. "Realized Volatility and Asymmetries in the A.S.E. Returns," Finance 0507012, University Library of Munich, Germany, revised 17 Jan 2006.
    83. Julien Chevallier & Benoît Sévi, 2012. "On the Stochastic Properties of Carbon Futures Prices," Working Papers halshs-00720166, HAL.
    84. Gajda, J. & Wyłomańska, A. & Kumar, A., 2017. "Generalized fractional Laplace motion," Statistics & Probability Letters, Elsevier, vol. 124(C), pages 101-109.
    85. Takuji Arai & Ryoichi Suzuki, 2015. "Local risk-minimization for Barndorff-Nielsen and Shephard models," Keio-IES Discussion Paper Series 2015-003, Institute for Economics Studies, Keio University.
    86. Mark Tippett, 2004. "Discussion of Interim Reporting Frequency and Financial Analysts’ Expenditures," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(1‐2), pages 199-207, January.
    87. Enrique Villamor & Pablo Olivares, 2020. "Pricing Exchange Options under Stochastic Correlation," Papers 2001.03967, arXiv.org.
    88. Dassios, Angelos & Qu, Yan & Zhao, Hongbiao, 2018. "Exact simulation for a class of tempered stable," LSE Research Online Documents on Economics 86981, London School of Economics and Political Science, LSE Library.
    89. Ole E. Barndorff-Nielsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2014. "Integer-valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 693-724, September.
    90. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    91. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    92. Stefano Iacus & Lorenzo Mercuri, 2015. "Implementation of Lévy CARMA model in Yuima package," Computational Statistics, Springer, vol. 30(4), pages 1111-1141, December.
    93. Jondeau, Eric, 2016. "Asymmetry in tail dependence in equity portfolios," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 351-368.
    94. Javed Farrukh & Podgórski Krzysztof, 2014. "Leverage Effect for Volatility with Generalized Laplace Error," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 157-166, December.
    95. Michael Grabchak, 2021. "On the transition laws of p-tempered $$\alpha $$ α -stable OU-processes," Computational Statistics, Springer, vol. 36(2), pages 1415-1436, June.
    96. Matthieu Garcin & Martino Grasselli, 2020. "Long vs Short Time Scales: the Rough Dilemma and Beyond," Papers 2008.07822, arXiv.org, revised Nov 2021.
    97. Griffin, J.E. & Steel, M.F.J., 2010. "Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2594-2608, November.
    98. Valentin Courgeau & Almut E. D. Veraart, 2022. "Likelihood theory for the graph Ornstein-Uhlenbeck process," Statistical Inference for Stochastic Processes, Springer, vol. 25(2), pages 227-260, July.
    99. Nemat Safarov & Colin Atkinson, 2016. "Natural gas-fired power plants valuation and optimisation under Levy copulas and regime-switching," Papers 1607.01207, arXiv.org, revised Jul 2016.
    100. Christian Bontemps & Nour Meddahi, 2002. "Testing Normality: A GMM Approach," CIRANO Working Papers 2002s-63, CIRANO.
    101. Degiannakis, Stavros & Livada, Alexandra, 2013. "Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process," MPRA Paper 80449, University Library of Munich, Germany.
    102. Coqueret, Guillaume & Tavin, Bertrand, 2016. "An investigation of model risk in a market with jumps and stochastic volatility," European Journal of Operational Research, Elsevier, vol. 253(3), pages 648-658.
    103. Neil Shephard & Ole E. Barndorff-Nielsen & University of Aarhus, 2001. "Econometric Analysis of Realised Volatility and Its Use in Estimating Stochastic Volatility Models," Economics Series Working Papers 71, University of Oxford, Department of Economics.
    104. Grahovac, Danijel & Leonenko, Nikolai N. & Taqqu, Murad S., 2019. "Limit theorems, scaling of moments and intermittency for integrated finite variance supOU processes," Stochastic Processes and their Applications, Elsevier, vol. 129(12), pages 5113-5150.
    105. A. Aghamohammadi & S. Mohammadi, 2017. "Bayesian analysis of penalized quantile regression for longitudinal data," Statistical Papers, Springer, vol. 58(4), pages 1035-1053, December.
    106. Robert Brooks & Robert Faff & Sirimon Treepongkaruna & Eliza Wu, 2015. "Do Sovereign Re-Ratings Destabilize Equity Markets during Financial Crises? New Evidence from Higher Return Moments," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 42(5-6), pages 777-799, June.
    107. Yipeng Yang & Allanus Tsoi, 2016. "A Level Set Analysis and A Nonparametric Regression on S&P 500 Daily Return," IJFS, MDPI, vol. 4(1), pages 1-24, February.
    108. Xiaojing Song & Thu Phuong Truong & Mark Tippett & John van der Burg, 2022. "The quantity theory of stock prices," The European Journal of Finance, Taylor & Francis Journals, vol. 28(17), pages 1685-1707, November.
    109. Fotopoulos, Stergios B., 2005. "Type G and spherical distributions on," Statistics & Probability Letters, Elsevier, vol. 72(1), pages 23-32, April.
    110. G. Mesters & S. J. Koopman & M. Ooms, 2016. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 659-687, April.
    111. ROMBOUTS, Jeroen V.K. & STENTOFT, Lars, 2009. "Bayesian option pricing using mixed normal heteroskedasticity models," LIDAM Discussion Papers CORE 2009013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    112. Caravenna, Francesco & Corbetta, Jacopo, 2018. "The asymptotic smile of a multiscaling stochastic volatility model," Stochastic Processes and their Applications, Elsevier, vol. 128(3), pages 1034-1071.
    113. Gennady Gorin & John J. Vastola & Meichen Fang & Lior Pachter, 2022. "Interpretable and tractable models of transcriptional noise for the rational design of single-molecule quantification experiments," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    114. Karl Friedrich Hofmann & Thorsten Schulz, 2016. "A General Ornstein–Uhlenbeck Stochastic Volatility Model With Lévy Jumps," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(08), pages 1-23, December.
    115. Ying Jiao & Chunhua Ma & Simone Scotti & Chao Zhou, 2018. "The Alpha-Heston Stochastic Volatility Model," Papers 1812.01914, arXiv.org.
    116. Mencía, Javier & Sentana, Enrique, 2013. "Valuation of VIX derivatives," Journal of Financial Economics, Elsevier, vol. 108(2), pages 367-391.
    117. Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.
    118. Park, Yang-Ho, 2016. "The effects of asymmetric volatility and jumps on the pricing of VIX derivatives," Journal of Econometrics, Elsevier, vol. 192(1), pages 313-328.
    119. Godek, Paul E., 2015. "A simple model of market valuation and trend reversion for U.S. equities: 100 Years of bubbles, non-bubbles, and inverse-bubbles," Finance Research Letters, Elsevier, vol. 13(C), pages 29-35.
    120. Jan Kallsen & Richard Vierthauer, 2009. "Quadratic hedging in affine stochastic volatility models," Review of Derivatives Research, Springer, vol. 12(1), pages 3-27, April.
    121. Michael Roberts & Indranil SenGupta, 2019. "Infinitesimal generators for two-dimensional L\'evy process-driven hypothesis testing," Papers 1911.08412, arXiv.org.
    122. Lingohr, Daniel & Müller, Gernot, 2019. "Stochastic modeling of intraday photovoltaic power generation," Energy Economics, Elsevier, vol. 81(C), pages 175-186.
    123. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Power Variation and Time Change," Economics Papers 2002-W24, Economics Group, Nuffield College, University of Oxford.
    124. Hansson, Fredrik & Rüdow Fors, Erik, 2009. "Get Shorty? - Market Impact of the 2008-09 U.K. Short Selling Ban," Working Papers in Economics 365, University of Gothenburg, Department of Economics.
    125. Mencia, Javier F. & Sentana, Enrique, 2004. "Estimation and testing of dynamic models with generalised hyperbolic innovations," LSE Research Online Documents on Economics 24742, London School of Economics and Political Science, LSE Library.
    126. Yuta Kurose & Yasuhiro Omori, 2016. "Multiple-block Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1024, CIRJE, Faculty of Economics, University of Tokyo.
    127. Chunsheng Ma, 2017. "Vector Stochastic Processes with Pólya-Type Correlation Structure," International Statistical Review, International Statistical Institute, vol. 85(2), pages 340-354, August.
    128. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2015. "Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model," Tinbergen Institute Discussion Papers 15-076/IV/DSF94, Tinbergen Institute.
    129. Kyriakos Georgiou & Athanasios N. Yannacopoulos, 2023. "Probability of Default modelling with L\'evy-driven Ornstein-Uhlenbeck processes and applications in credit risk under the IFRS 9," Papers 2309.12384, arXiv.org.
    130. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    131. Daisuke Nagakura & Toshiaki Watanabe, 2010. "A State Space Approach to Estimating the Integrated Variance under the Existence of Market Microstructure Noise," Global COE Hi-Stat Discussion Paper Series gd09-115, Institute of Economic Research, Hitotsubashi University.
    132. Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Indirect inference with time series observed with error," CREATES Research Papers 2014-57, Department of Economics and Business Economics, Aarhus University.
    133. Benth, Fred Espen & Taib, Che Mohd Imran Che, 2013. "On the speed towards the mean for continuous time autoregressive moving average processes with applications to energy markets," Energy Economics, Elsevier, vol. 40(C), pages 259-268.
    134. Neil Shephard, 2005. "Stochastic Volatility," Economics Papers 2005-W17, Economics Group, Nuffield College, University of Oxford.
    135. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
    136. Jianqing Fan, 2004. "A selective overview of nonparametric methods in financial econometrics," Papers math/0411034, arXiv.org.
    137. Leisen, Fabrizio & Mena, Ramsés H. & Palma, Freddy & Rossini, Luca, 2019. "On a flexible construction of a negative binomial model," Statistics & Probability Letters, Elsevier, vol. 152(C), pages 1-8.
    138. Pier Paolo Peirano & Damien Challet, 2012. "Baldovin-Stella stochastic volatility process and Wiener process mixtures," Post-Print hal-00734355, HAL.
    139. Anne Brix & Asger Lunde, 2015. "Prediction-based estimating functions for stochastic volatility models with noisy data: comparison with a GMM alternative," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(4), pages 433-465, October.
    140. Šaltytė Benth, Jūratė & Benth, Fred Espen, 2012. "A critical view on temperature modelling for application in weather derivatives markets," Energy Economics, Elsevier, vol. 34(2), pages 592-602.
    141. Javier Mencía & Enrique Sentana, 2008. "Multivariate Location-Scale Mixtures of Normals and Mean-Variance-skewness Portfolio Allocation," Working Papers wp2008_0805, CEMFI.
    142. Yijie Peng & Michael C. Fu & Jian-Qiang Hu, 2016. "Gradient-based simulated maximum likelihood estimation for stochastic volatility models using characteristic functions," Quantitative Finance, Taylor & Francis Journals, vol. 16(9), pages 1393-1411, September.
    143. Pham, Viet Son & Chong, Carsten, 2018. "Volterra-type Ornstein–Uhlenbeck processes in space and time," Stochastic Processes and their Applications, Elsevier, vol. 128(9), pages 3082-3117.
    144. Shibin Zhang & Xinsheng Zhang, 2013. "A least squares estimator for discretely observed Ornstein–Uhlenbeck processes driven by symmetric α-stable motions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 89-103, February.
    145. Barunik, Jozef & Barunikova, Michaela, 2015. "Revisiting the long memory dynamics of implied-realized volatility relation: A new evidence from wavelet band spectrum regression," FinMaP-Working Papers 43, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    146. Hounyo, Ulrich & Varneskov, Rasmus T., 2017. "A local stable bootstrap for power variations of pure-jump semimartingales and activity index estimation," Journal of Econometrics, Elsevier, vol. 198(1), pages 10-28.
    147. Tim Bollerslev & Hao Zhou, 2001. "Estimating stochastic volatility diffusion using conditional moments of integrated volatility," Finance and Economics Discussion Series 2001-49, Board of Governors of the Federal Reserve System (U.S.).
    148. Capobianco, Enrico, 2004. "Multiscale stochastic dynamics in finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 122-127.
    149. Friedrich Hubalek & Martin Keller-Ressel & Carlo Sgarra, 2014. "Geometric Asian Option Pricing in General Affine Stochastic Volatility Models with Jumps," Papers 1407.2514, arXiv.org.
    150. Fred Espen Benth & Jan Kallsen & Thilo Meyer-Brandis, 2007. "A Non-Gaussian Ornstein-Uhlenbeck Process for Electricity Spot Price Modeling and Derivatives Pricing," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(2), pages 153-169.
    151. Michele Leonardo Bianchi & Svetlozar T. Rachev & Frank J. Fabozzi, 2018. "Calibrating the Italian Smile with Time-Varying Volatility and Heavy-Tailed Models," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 339-378, March.
    152. Fred Espen Benth & Hanna Zdanowicz, 2016. "Pricing And Hedging Of Energy Spread Options And Volatility Modulated Volterra Processes," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-22, February.
    153. Martino Bardi & Annalisa Cesaroni & Andrea Scotti, 2014. "Convergence in Multiscale Financial Models with Non-Gaussian Stochastic Volatility," Papers 1405.6514, arXiv.org.
    154. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    155. Lu, Jin-Ray & Yang, Ya-Huei, 2021. "Option valuations and asset demands and supplies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 49-64.
    156. Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
    157. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    158. Colino, Jesús P., 2008. "New stochastic processes to model interest rates : LIBOR additive processes," DES - Working Papers. Statistics and Econometrics. WS ws085316, Universidad Carlos III de Madrid. Departamento de Estadística.
    159. Laetitia Badouraly Kassim & Jérôme Lelong & Imane Loumrhari, 2015. "Importance sampling for jump processes and applications to finance," Post-Print hal-00842362, HAL.
    160. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 Volatility Using Ultra-high Frequency Data," MPRA Paper 80445, University Library of Munich, Germany.
    161. Paul Fearnhead & Omiros Papaspiliopoulos & Gareth O. Roberts & Andrew Stuart, 2010. "Random‐weight particle filtering of continuous time processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(4), pages 497-512, September.
    162. Tim Leung & Kevin W. Lu, 2023. "Monte Carlo Simulation for Trading Under a L\'evy-Driven Mean-Reverting Framework," Papers 2309.05512, arXiv.org, revised Jan 2024.
    163. Brignone, Riccardo & Gonzato, Luca & Lütkebohmert, Eva, 2023. "Efficient Quasi-Bayesian Estimation of Affine Option Pricing Models Using Risk-Neutral Cumulants," Journal of Banking & Finance, Elsevier, vol. 148(C).
    164. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    165. Raknerud, Arvid & Skare, Øivind, 2012. "Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein–Uhlenbeck processes," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3260-3275.
    166. Kevin W. Lu, 2022. "Calibration for multivariate Lévy-driven Ornstein-Uhlenbeck processes with applications to weak subordination," Statistical Inference for Stochastic Processes, Springer, vol. 25(2), pages 365-396, July.
    167. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    168. Dinghai Xu & Yuying Li, 2010. "Empirical Evidence of the Leverage Effect in a Stochastic Volatility Model: A Realized Volatility Approach," Working Papers 1002, University of Waterloo, Department of Economics, revised May 2010.
    169. McCulloch, James, 2012. "Fractal market time," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 686-701.
    170. Makoto Takahashi & Yasuhiro Omori & Toshiaki Watanabe, 2007. "Estimating Stochastic Volatility Models Using Daily Returns and Realized Volatility Simultaneously ( Revised in March 2008; Published in "Computational Statistics and Data Analysis", 53-6, 2," CARF F-Series CARF-F-108, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    171. Christoffersen, Peter & Heston, Steve & Jacobs, Kris, 2006. "Option valuation with conditional skewness," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 253-284.
    172. John Cotter, 2011. "Minimum Capital Requirement Calculations for UK Futures," Working Papers 200418, Geary Institute, University College Dublin.
    173. Marcos Escobar & Peter Hieber & Matthias Scherer, 2014. "Efficiently pricing double barrier derivatives in stochastic volatility models," Review of Derivatives Research, Springer, vol. 17(2), pages 191-216, July.
    174. Ilze KALNINA & Dacheng XIU, 2015. "Nonparametric Estimation of the Leverage Effect : A Trade-off between Robustness and Efficiency," Cahiers de recherche 09-2015, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    175. Wong, Woon K. & Tu, Anthony H., 2009. "Market imperfections and the information content of implied and realized volatility," Pacific-Basin Finance Journal, Elsevier, vol. 17(1), pages 58-79, January.
    176. Shirota, Shinichiro & Hizu, Takayuki & Omori, Yasuhiro, 2014. "Realized stochastic volatility with leverage and long memory," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 618-641.
    177. Adam Aleksander Majewski & Giacomo Bormetti & Fulvio Corsi, 2014. "Smile from the Past: A general option pricing framework with multiple volatility and leverage components," Papers 1404.3555, arXiv.org.
    178. Choi, Kyongwook & Yu, Wei-Choun & Zivot, Eric, 2010. "Long memory versus structural breaks in modeling and forecasting realized volatility," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 857-875, September.
    179. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    180. Fig-Talamanca, Gianna, 2009. "Testing volatility autocorrelation in the constant elasticity of variance stochastic volatility model," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2201-2218, April.
    181. Buchmann, Boris & Lu, Kevin W. & Madan, Dilip B., 2020. "Self-decomposability of weak variance generalised gamma convolutions," Stochastic Processes and their Applications, Elsevier, vol. 130(2), pages 630-655.
    182. Ching-Kang Ing & Chiao-Yi Yang, 2014. "Predictor Selection for Positive Autoregressive Processes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 243-253, March.
    183. Alessandro Bondi & Sergio Pulido & Simone Scotti, 2022. "The rough Hawkes Heston stochastic volatility model," Papers 2210.12393, arXiv.org.
    184. Palombini, Edgardo, 2003. "Volatility and liquidity in the Italian money market," MPRA Paper 42699, University Library of Munich, Germany.
    185. Paul Glasserman & Zongjian Liu, 2010. "Sensitivity Estimates from Characteristic Functions," Operations Research, INFORMS, vol. 58(6), pages 1611-1623, December.
    186. Tingguo Zheng & Tao Song, 2014. "A Realized Stochastic Volatility Model With Box-Cox Transformation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 593-605, October.
    187. Wan-Lun Wang & Min Liu & Tsung-I Lin, 2017. "Robust skew-t factor analysis models for handling missing data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(4), pages 649-672, November.
    188. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," NBER Technical Working Papers 0279, National Bureau of Economic Research, Inc.
    189. Behme, Anita & Chong, Carsten & Klüppelberg, Claudia, 2015. "Superposition of COGARCH processes," Stochastic Processes and their Applications, Elsevier, vol. 125(4), pages 1426-1469.
    190. Friedrich Hubalek & Petra Posedel, 2008. "Joint analysis and estimation of stock prices and trading volume in Barndorff-Nielsen and Shephard stochastic volatility models," Papers 0807.3464, arXiv.org, revised Oct 2008.
    191. Ravi Bansal & Dana Kiku & Amir Yaron, 2009. "An Empirical Evaluation of the Long-Run Risks Model for Asset Prices," NBER Working Papers 15504, National Bureau of Economic Research, Inc.
    192. Josef Danv{e}k & J. Posp'iv{s}il, 2020. "Numerical aspects of integration in semi-closed option pricing formulas for stochastic volatility jump diffusion models," Papers 2006.13181, arXiv.org.
    193. Alexandre F. Roch, 2008. "Viscosity Solutions and American Option Pricing in a Stochastic Volatility Model of the Ornstein-Uhlenbeck Type," Papers 0812.2444, arXiv.org.
    194. Xu Lin & Sweder van Wijnbergen, "undated". "The Social Cost of Carbon under Climate Volatility Risk," Tinbergen Institute Discussion Papers 23-032/IV, Tinbergen Institute.
    195. Daniel Preve & Anders Eriksson & Jun Yu, 2009. "Forecasting Realized Volatility Using A Nonnegative Semiparametric Model," Finance Working Papers 23049, East Asian Bureau of Economic Research.
    196. Shubham Ekapure & Nuruddin Jiruwala & Sohan Patnaik & Indranil SenGupta, 2021. "A data-science-driven short-term analysis of Amazon, Apple, Google, and Microsoft stocks," Papers 2107.14695, arXiv.org.
    197. Bakerman, Jordan & Pazdernik, Karl & Korkmaz, Gizem & Wilson, Alyson G., 2022. "Dynamic logistic regression and variable selection: Forecasting and contextualizing civil unrest," International Journal of Forecasting, Elsevier, vol. 38(2), pages 648-661.
    198. Liudas Giraitis & Remigijus Leipus & Peter M Robinson & Donatas Surgailis, 2003. "LARCH, Leverage and Long Memory," STICERD - Econometrics Paper Series 460, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    199. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2001. "High- and Low-Frequency Exchange Rate Volatility Dynamics: Range-Based Estimation of Stochastic Volatility Models," NBER Working Papers 8162, National Bureau of Economic Research, Inc.
    200. MEDDAHI, Nour, 2002. "ARMA Representation of Integrated and Realized Variances," Cahiers de recherche 2002-20, Universite de Montreal, Departement de sciences economiques.
    201. Christian E. Galarza & Luis M. Castro & Francisco Louzada & Victor H. Lachos, 2020. "Quantile regression for nonlinear mixed effects models: a likelihood based perspective," Statistical Papers, Springer, vol. 61(3), pages 1281-1307, June.
    202. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Normal modified stable processes," Economics Papers 2001-W6, Economics Group, Nuffield College, University of Oxford.
    203. Ulrich Horst & Wei Xu, 2019. "The Microstructure of Stochastic Volatility Models with Self-Exciting Jump Dynamics," Papers 1911.12969, arXiv.org.
    204. Genya Kobayashi & Hideo Kozumi, 2012. "Bayesian analysis of quantile regression for censored dynamic panel data," Computational Statistics, Springer, vol. 27(2), pages 359-380, June.
    205. Ewald, Christian & Zou, Yihan, 2021. "Stochastic volatility: A tale of co-jumps, non-normality, GMM and high frequency data," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 37-52.
    206. Carole Bernard & Gero Junike & Thibaut Lux & Steven Vanduffel, 2022. "Cost-efficient Payoffs under Model Ambiguity," Papers 2207.02948, arXiv.org, revised Aug 2023.
    207. Baule, Rainer & Shkel, David, 2021. "Model risk and model choice in the case of barrier options and bonus certificates," Journal of Banking & Finance, Elsevier, vol. 133(C).
    208. Sio Chong U & Jacky So & Deng Ding & Lihong Liu, 2016. "An efficient Fourier expansion method for the calculation of value-at-risk: Contributions of extra-ordinary risks," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-27, March.
    209. Fan Jiang & Xin Zang & Jingping Yang, 2020. "Asymptotic expansion for the transition densities of stochastic differential equations driven by the gamma processes," Papers 2003.06218, arXiv.org.
    210. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," NBER Working Papers 11188, National Bureau of Economic Research, Inc.
    211. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility," CIRJE F-Series CIRJE-F-488, CIRJE, Faculty of Economics, University of Tokyo.
    212. Schnurr Alexander & Woerner Jeannette H. C., 2011. "Well-balanced Lévy driven Ornstein–Uhlenbeck processes," Statistics & Risk Modeling, De Gruyter, vol. 28(4), pages 343-357, December.
    213. Rosinski, Jan, 2007. "Tempering stable processes," Stochastic Processes and their Applications, Elsevier, vol. 117(6), pages 677-707, June.
    214. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," Journal of Econometrics, Elsevier, vol. 193(2), pages 367-389.
    215. Fulvio Corsi & Stefano Peluso & Francesco Audrino, 2015. "Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 377-397, April.
    216. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    217. Claudia Yeap & Simon S Kwok & S T Boris Choy, 2018. "A Flexible Generalized Hyperbolic Option Pricing Model and Its Special Cases," Journal of Financial Econometrics, Oxford University Press, vol. 16(3), pages 425-460.
    218. Hasan A. Fallahgoul & Young S. Kim & Frank J. Fabozzi & Jiho Park, 2019. "Quanto Option Pricing with Lévy Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1279-1308, March.
    219. Qian Guo & Huw Rhys & Xiaojing Song & Mark Tippett, 2016. "The Friedman rule and inflation targeting," The European Journal of Finance, Taylor & Francis Journals, vol. 22(14), pages 1414-1434, November.
    220. Ole Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2002. "Some recent developments in stochastic volatility modelling," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 11-23.
    221. S. Kuchuk-Iatsenko & Y. Mishura & Y. Munchak, 2016. "Application of Malliavin calculus to exact and approximate option pricing under stochastic volatility," Papers 1608.00230, arXiv.org.
    222. Li, Chenxu & Wu, Linjia, 2019. "Exact simulation of the Ornstein–Uhlenbeck driven stochastic volatility model," European Journal of Operational Research, Elsevier, vol. 275(2), pages 768-779.
    223. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.
    224. Aurea Grané & Helena Veiga, 2012. "Asymmetry, realised volatility and stock return risk estimates," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 11(2), pages 147-164, August.
    225. Lee, Oesook, 2012. "V-uniform ergodicity of a continuous time asymmetric power GARCH(1,1) model," Statistics & Probability Letters, Elsevier, vol. 82(4), pages 812-817.
    226. Maria P. Braun & Simos G. Meintanis & Viatcheslav B. Melas, 2008. "Optimal Design Approach to GMM Estimation of Parameters Based on Empirical Transforms," International Statistical Review, International Statistical Institute, vol. 76(3), pages 387-400, December.
    227. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    228. Finlay, Richard & Seneta, Eugene, 2012. "A Generalized Hyperbolic model for a risky asset with dependence," Statistics & Probability Letters, Elsevier, vol. 82(12), pages 2164-2169.
    229. Pakkanen, Mikko S. & Sottinen, Tommi & Yazigi, Adil, 2017. "On the conditional small ball property of multivariate Lévy-driven moving average processes," Stochastic Processes and their Applications, Elsevier, vol. 127(3), pages 749-782.
    230. Tsung-I Lin & Pal Wu & Geoffrey McLachlan & Sharon Lee, 2015. "A robust factor analysis model using the restricted skew- $$t$$ t distribution," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 510-531, September.
    231. Chiara Amorino & Arnaud Gloter, 2021. "Joint estimation for volatility and drift parameters of ergodic jump diffusion processes via contrast function," Statistical Inference for Stochastic Processes, Springer, vol. 24(1), pages 61-148, April.
    232. Ole E. Barndorff-Nielsen & Almut E. D. Veraart, 2009. "Stochastic volatility of volatility in continuous time," CREATES Research Papers 2009-25, Department of Economics and Business Economics, Aarhus University.
    233. Nicola Cufaro Petroni & Piergiacomo Sabino, 2019. "Fast Pricing of Energy Derivatives with Mean-reverting Jump-diffusion Processes," Papers 1908.03137, arXiv.org, revised Mar 2020.
    234. Nicholas Salmon & Indranil SenGupta, 2021. "Fractional Barndorff-Nielsen and Shephard model: applications in variance and volatility swaps, and hedging," Annals of Finance, Springer, vol. 17(4), pages 529-558, December.
    235. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "The effects of sovereign rating drifts on financial return distributions: Evidence from the European Union," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 5-20.
    236. T. R. Hurd, 2009. "Credit risk modeling using time-changed Brownian motion," Papers 0904.2376, arXiv.org.
    237. Chiara Amorino & Arnaud Gloter, 2020. "Contrast function estimation for the drift parameter of ergodic jump diffusion process," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(2), pages 279-346, June.
    238. Xianhua Dai & Wolfgang Karl Härdle & Keming Yu, 2016. "Do maternal health problems influence child's worrying status? Evidence from the British Cohort Study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(16), pages 2941-2955, December.
    239. Nour Meddahi, 2000. "Temporal Aggregation of Volatility Models," Econometric Society World Congress 2000 Contributed Papers 1903, Econometric Society.
    240. Vyacheslav Abramov & Fima Klebaner, 2007. "Estimation and Prediction of a Non-Constant Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(1), pages 1-23, March.
    241. Dilip Madan, 2009. "A tale of two volatilities," Review of Derivatives Research, Springer, vol. 12(3), pages 213-230, October.
    242. Garcia, René & Lewis, Marc-André & Pastorello, Sergio & Renault, Éric, 2011. "Estimation of objective and risk-neutral distributions based on moments of integrated volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 22-32, January.
    243. Peter Bank & Selim Gökay, 2016. "Superreplication when trading at market indifference prices," Finance and Stochastics, Springer, vol. 20(1), pages 153-182, January.
    244. Fan, Jianqing & Fan, Yingying & Jiang, Jiancheng, 2007. "Dynamic Integration of Time- and State-Domain Methods for Volatility Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 618-631, June.
    245. Shu, Yin & Feng, Qianmei & Liu, Hao, 2019. "Using degradation-with-jump measures to estimate life characteristics of lithium-ion battery," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    246. Belomestny, Denis & Panov, Vladimir, 2013. "Abelian theorems for stochastic volatility models with application to the estimation of jump activity," Stochastic Processes and their Applications, Elsevier, vol. 123(1), pages 15-44.
    247. Xianfei Hui & Baiqing Sun & Hui Jiang & Yan Zhou, 2022. "Modeling dynamic volatility under uncertain environment with fuzziness and randomness," Papers 2204.12657, arXiv.org, revised Oct 2022.
    248. Habtemicael, Semere & SenGupta, Indranil, 2014. "Ornstein–Uhlenbeck processes for geophysical data analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 147-156.
    249. Tomáš Tichý, 2006. "Model Dependency of the Digital Option Replication – Replication under an Incomplete Model (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 56(7-8), pages 361-379, July.
    250. Li, Long & Bao, Si & Chen, Jing-Chao & Jiang, Tao, 2019. "A method to get a more stationary process and its application in finance with high-frequency data of Chinese index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1405-1417.
    251. Zorana Grbac & David Krief & Peter Tankov, 2018. "Long-time trajectorial large deviations for affine stochastic volatility models and application to variance reduction for option pricing," Papers 1809.06153, arXiv.org.
    252. Griffin, J.E. & Steel, M.F.J., 2006. "Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility," Journal of Econometrics, Elsevier, vol. 134(2), pages 605-644, October.
    253. Nikola Gradojevic & Dragan Kukolj & Ramazan Gencay, 2011. "Clustering and Classification in Option Pricing," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 3(2), pages 109-128, October.
    254. Ying Jiao & Chunhua Ma & Simone Scotti & Chao Zhou, 2021. "The Alpha‐Heston stochastic volatility model," Mathematical Finance, Wiley Blackwell, vol. 31(3), pages 943-978, July.
    255. Kawai Reiichiro & Masuda Hiroki, 2011. "Exact discrete sampling of finite variation tempered stable Ornstein–Uhlenbeck processes," Monte Carlo Methods and Applications, De Gruyter, vol. 17(3), pages 279-300, January.
    256. Tang, Qihe & Tong, Zhiwei & Yang, Yang, 2021. "Large portfolio losses in a turbulent market," European Journal of Operational Research, Elsevier, vol. 292(2), pages 755-769.
    257. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2015. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-979, CIRJE, Faculty of Economics, University of Tokyo.
    258. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2008. "Modeling the leverage effect with copulas and realized volatility," Finance Research Letters, Elsevier, vol. 5(4), pages 221-227, December.
    259. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Estimating quadratic variation using realised volatility," Economics Papers 2001-W20, Economics Group, Nuffield College, University of Oxford, revised 01 Nov 2001.
    260. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
    261. Akira Yamazaki, 2015. "Asset Pricing With Non-Geometric Type Of Dividends," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-38, December.
    262. Takuji Arai & Yuto Imai, 2023. "Monte Carlo simulation for Barndorff-Nielsen and Shephard model under change of measure," Papers 2306.05750, arXiv.org.
    263. Jan Kallsen & Paul Krühner, 2015. "On a Heath–Jarrow–Morton approach for stock options," Finance and Stochastics, Springer, vol. 19(3), pages 583-615, July.
    264. Bollerslev, Tim & Zhang, Benjamin Y. B., 2003. "Measuring and modeling systematic risk in factor pricing models using high-frequency data," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 533-558, December.
    265. Massoud Heidari & Liuren WU, 2002. "Are Interest Rate Derivatives Spanned by the Term Structure of Interest Rates?," Finance 0207013, University Library of Munich, Germany.
    266. John Crosby, 2008. "Pricing a class of exotic commodity options in a multi-factor jump-diffusion model," Quantitative Finance, Taylor & Francis Journals, vol. 8(5), pages 471-483.
    267. Ali Aghamohammadi, 2018. "Bayesian analysis of dynamic panel data by penalized quantile regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 91-108, March.
    268. A. Szimayer & R. Maller, 2004. "Testing for Mean Reversion in Processes of Ornstein-Uhlenbeck Type," Statistical Inference for Stochastic Processes, Springer, vol. 7(2), pages 95-113, May.
    269. Jeffrey R. Russell & Federico M. Bandi, 2004. "Microstructure noise, realized volatility, and optimal sampling," Econometric Society 2004 Latin American Meetings 220, Econometric Society.
    270. Maghyereh, Aktham & Awartani, Basel & Abdoh, Hussein, 2022. "Asymmetric risk transfer in global equity markets: An extended sample that includes the COVID pandemic period," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    271. Ivanovski, Zoran & Stojanovski, Toni & Narasanov, Zoran, 2015. "Volatility And Kurtosis Of Daily Stock Returns At Mse," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 6(2), pages 209-221.
    272. Potiron, Yoann & Mykland, Per A., 2017. "Estimation of integrated quadratic covariation with endogenous sampling times," Journal of Econometrics, Elsevier, vol. 197(1), pages 20-41.
    273. Haugom, Erik & Westgaard, Sjur & Solibakke, Per Bjarte & Lien, Gudbrand, 2011. "Realized volatility and the influence of market measures on predictability: Analysis of Nord Pool forward electricity data," Energy Economics, Elsevier, vol. 33(6), pages 1206-1215.
    274. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
    275. Torben G. Andersen & Tim Bollerslev & Dobrislav Dobrev, 2007. "No-Arbitrage Semi-Martingale Restrictions for Continuous-Time Volatility Models subject to Leverage Effects, Jumps and i.i.d. Noise: Theory and Testable Distributional Implications," NBER Working Papers 12963, National Bureau of Economic Research, Inc.
    276. Fred Espen Benth & Hanna Zdanowicz, 2014. "Pricing and hedging of energy spread options and volatility modulated Volterra processes," Papers 1409.5801, arXiv.org.
    277. Lindström, Erik & Ströjby, Jonas & Brodén, Mats & Wiktorsson, Magnus & Holst, Jan, 2008. "Sequential calibration of options," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2877-2891, February.
    278. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "How accurate is the asymptotic approximation to the distribution of realised volatility?," Economics Papers 2001-W16, Economics Group, Nuffield College, University of Oxford.
    279. Kallsen, Jan & Muhle-Karbe, Johannes, 2010. "Exponentially affine martingales, affine measure changes and exponential moments of affine processes," Stochastic Processes and their Applications, Elsevier, vol. 120(2), pages 163-181, February.
    280. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
    281. Pham, Viet Son, 2020. "Lévy-driven causal CARMA random fields," Stochastic Processes and their Applications, Elsevier, vol. 130(12), pages 7547-7574.
    282. Mario Bonino & Matteo Camelia & Paolo Pigato, 2016. "A multivariate model for financial indices and an algorithm for detection of jumps in the volatility," Working Papers hal-01408495, HAL.
    283. Takaishi, Tetsuya, 2018. "Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 139-154.
    284. Hounyo, Ulrich & Varneskov, Rasmus T., 2020. "Inference for local distributions at high sampling frequencies: A bootstrap approach," Journal of Econometrics, Elsevier, vol. 215(1), pages 1-34.
    285. Christian E. Galarza & Panpan Zhang & Víctor H. Lachos, 2021. "Logistic Quantile Regression for Bounded Outcomes Using a Family of Heavy-Tailed Distributions," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 325-349, November.
    286. Siamak Ghasemzadeh & Mojtaba Ganjali & Taban Baghfalaki, 2018. "Bayesian quantile regression for analyzing ordinal longitudinal responses in the presence of non-ignorable missingness," METRON, Springer;Sapienza Università di Roma, vol. 76(3), pages 321-348, December.
    287. Masuda, H. & Yoshida, N., 2005. "Asymptotic expansion for Barndorff-Nielsen and Shephard's stochastic volatility model," Stochastic Processes and their Applications, Elsevier, vol. 115(7), pages 1167-1186, July.
    288. Ronnie L. Loeffen & Pierre Patie, 2010. "Absolute ruin in the Ornstein-Uhlenbeck type risk model," Papers 1006.2712, arXiv.org.
    289. Marina Resta & Davide Sciutti, 2003. "Spot price dynamics in deregulated power markets," Econometrics 0312002, University Library of Munich, Germany.
    290. Wendong Zheng & Pingping Zeng, 2015. "Pricing timer options and variance derivatives with closed-form partial transform under the 3/2 model," Papers 1504.08136, arXiv.org.
    291. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    292. Giulia Di Nunno & Kk{e}stutis Kubilius & Yuliya Mishura & Anton Yurchenko-Tytarenko, 2023. "From constant to rough: A survey of continuous volatility modeling," Papers 2309.01033, arXiv.org, revised Sep 2023.
    293. Darrel Duffie & Damir Filipović & Walter Schachermayer, 2002. "Affine Processes and Application in Finance," NBER Technical Working Papers 0281, National Bureau of Economic Research, Inc.
    294. Zheng, Tingguo & Xiao, Han & Chen, Rong, 2015. "Generalized ARMA models with martingale difference errors," Journal of Econometrics, Elsevier, vol. 189(2), pages 492-506.
    295. Bercu, Bernard & Proïa, Frédéric & Savy, Nicolas, 2014. "On Ornstein–Uhlenbeck driven by Ornstein–Uhlenbeck processes," Statistics & Probability Letters, Elsevier, vol. 85(C), pages 36-44.
    296. Martin Schweizer & Danijel Zivoi & Mario Šikić, 2018. "Dynamic Mean–Variance Optimization Problems With Deterministic Information," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-38, March.
    297. Lillestöl, Jostein, 2002. "Some crude approximation, calibration and estimation procedures for NIG-variates," SFB 373 Discussion Papers 2002,85, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    298. Badescu Alex & Kulperger Reg & Lazar Emese, 2008. "Option Valuation with Normal Mixture GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-42, May.
    299. John Cotter, 2004. "Realized volatility and minimum capital requirements," Money Macro and Finance (MMF) Research Group Conference 2003 20, Money Macro and Finance Research Group.
    300. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    301. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.
    302. Evarist Stoja & Richard D. F. Harris & Fatih Yilmaz, 2010. "A Cyclical Model of Exchange Rate Volatility," Bristol Economics Discussion Papers 10/618, School of Economics, University of Bristol, UK.
    303. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    304. Amorino, Chiara & Gloter, Arnaud, 2020. "Unbiased truncated quadratic variation for volatility estimation in jump diffusion processes," Stochastic Processes and their Applications, Elsevier, vol. 130(10), pages 5888-5939.
    305. Dani Gamerman & Thiago Rezende Santos & Glaura C. Franco, 2013. "A Non-Gaussian Family Of State-Space Models With Exact Marginal Likelihood," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(6), pages 625-645, November.
    306. Jing-zhi Huang & Liuren Wu, 2004. "Specification Analysis of Option Pricing Models Based on Time-Changed Levy Processes," Econometric Society 2004 North American Winter Meetings 405, Econometric Society.
    307. Ernst Eberlein & Kathrin Glau & Antonis Papapantoleon, 2008. "Analysis of Fourier transform valuation formulas and applications," Papers 0809.3405, arXiv.org, revised Sep 2009.
    308. Alhamzawi, Rahim & Yu, Keming, 2013. "Conjugate priors and variable selection for Bayesian quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 209-219.
    309. Ji Jung Im & Hyun Soo Lim & Sung sub Choi & Denis Nikitin, 2007. "Portfolio Selection under Parameter Uncertainty using a Predictive Distribution," Annals of Economics and Finance, Society for AEF, vol. 8(2), pages 305-312, November.
    310. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
    311. Matteo Gardini & Piergiacomo Sabino & Emanuela Sasso, 2020. "A bivariate Normal Inverse Gaussian process with stochastic delay: efficient simulations and applications to energy markets," Papers 2011.04256, arXiv.org.
    312. Szczepocki Piotr, 2020. "Application of iterated filtering to stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck process," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 173-187, June.
    313. Liu, Bin & Zhou, Cheng & Zhang, Xinsheng, 2019. "A tail adaptive approach for change point detection," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 33-48.
    314. Hinderks, W.J. & Wagner, A., 2020. "Factor models in the German electricity market: Stylized facts, seasonality, and calibration," Energy Economics, Elsevier, vol. 85(C).
    315. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    316. Bretó, Carles, 2014. "On idiosyncratic stochasticity of financial leverage effects," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 20-26.
    317. François-Éric Racicot & Raymond Théoret & Alain Coën, 2008. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 112-124, February.
    318. Yasemin Ulu, 2020. "Volatility Distribution of the DJSTOXXE50 Index," Applied Economics and Finance, Redfame publishing, vol. 7(6), pages 101-107, December.
    319. Subbotin, Alexandre, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 15(3), pages 94-138.
    320. Florence Guillaume & Wim Schoutens, 2014. "Heston Model: The Variance Swap Calibration," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 76-89, April.
    321. D. Delpini & G. Bormetti, 2015. "Stochastic volatility with heterogeneous time scales," Quantitative Finance, Taylor & Francis Journals, vol. 15(10), pages 1597-1608, October.
    322. Shu Ling Chiang & Ming Shann Tsai, 2019. "Valuation of an option using non-parametric methods," Review of Derivatives Research, Springer, vol. 22(3), pages 419-447, October.
    323. Matthieu Garcin & Martino Grasselli, 2022. "Long versus short time scales: the rough dilemma and beyond," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 257-278, June.
    324. S. Ghasemzadeh & M. Ganjali & T. Baghfalaki, 2022. "Quantile regression via the EM algorithm for joint modeling of mixed discrete and continuous data based on Gaussian copula," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1181-1202, December.
    325. John Randal & Peter Thomson & Martin Lally, 2004. "Non-parametric estimation of historical volatility," Quantitative Finance, Taylor & Francis Journals, vol. 4(4), pages 427-440.
    326. Song, Zhaogang & Xiu, Dacheng, 2016. "A tale of two option markets: Pricing kernels and volatility risk," Journal of Econometrics, Elsevier, vol. 190(1), pages 176-196.
    327. Dinghai Xu, 2010. "A Threshold Stochastic Volatility Model with Realized Volatility," Working Papers 1003, University of Waterloo, Department of Economics, revised May 2010.
    328. Catherine Doz & Eric Renault, 2004. "Conditionaly Heteroskedastic Factor Models : Identificationand Instrumental variables Estmation," THEMA Working Papers 2004-13, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    329. Benth, Fred Espen & Kiesel, Rüdiger & Nazarova, Anna, 2012. "A critical empirical study of three electricity spot price models," Energy Economics, Elsevier, vol. 34(5), pages 1589-1616.
    330. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Aug 2018.
    331. Marco Piccirilli & Tiziano Vargiolu, 2018. "Optimal Portfolio in Intraday Electricity Markets Modelled by L\'evy-Ornstein-Uhlenbeck Processes," Papers 1807.01979, arXiv.org.
    332. Luo, Jiaowan & Liu, Kai, 2008. "Stability of infinite dimensional stochastic evolution equations with memory and Markovian jumps," Stochastic Processes and their Applications, Elsevier, vol. 118(5), pages 864-895, May.
    333. Takuji Arai, 2015. "Local risk-minimization for Barndorff-Nielsen and Shephard models with volatility risk premium," Papers 1506.01477, arXiv.org.
    334. Mayerhofer, Eberhard & Stelzer, Robert & Vestweber, Johanna, 2020. "Geometric ergodicity of affine processes on cones," Stochastic Processes and their Applications, Elsevier, vol. 130(7), pages 4141-4173.
    335. Patie, Pierre, 2005. "On a martingale associated to generalized Ornstein-Uhlenbeck processes and an application to finance," Stochastic Processes and their Applications, Elsevier, vol. 115(4), pages 593-607, April.
    336. Oak, Neeraj & Lawson, Daniel & Champneys, Alan, 2014. "Performance comparison of renewable incentive schemes using optimal control," Energy, Elsevier, vol. 64(C), pages 44-57.
    337. Roel C.A. Oomen, 2004. "Statistical Models for High Frequency Security Prices," Econometric Society 2004 North American Winter Meetings 77, Econometric Society.
    338. Creal, Drew D., 2008. "Analysis of filtering and smoothing algorithms for Lévy-driven stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2863-2876, February.
    339. Neil Shephard & Torben G. Andersen, 2008. "Stochastic Volatility: Origins and Overview," OFRC Working Papers Series 2008fe23, Oxford Financial Research Centre.
    340. Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2023. "Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?," MPRA Paper 118459, University Library of Munich, Germany.
    341. Fred Espen Benth & Heidar Eyjolfsson, 2015. "Representation and approximation of ambit fields in Hilbert space," Papers 1509.08272, arXiv.org.
    342. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility (Revised in May 2007, Handbook of Financial Time Series (Published in "Handbook of Financial Time Series" (eds T.G. Andersen, R.A. Davis, Jens-Peter Kreiss," CARF F-Series CARF-F-094, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    343. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    344. Friedrich Hubalek & Petra Posedel, 2008. "Asymptotic analysis for a simple explicit estimator in Barndorff-Nielsen and Shephard stochastic volatility models," Papers 0807.3479, arXiv.org.
    345. Phillip, Andrew & Chan, Jennifer & Peiris, Shelton, 2019. "On long memory effects in the volatility measure of Cryptocurrencies," Finance Research Letters, Elsevier, vol. 28(C), pages 95-100.
    346. S. G. Kou, 2002. "A Jump-Diffusion Model for Option Pricing," Management Science, INFORMS, vol. 48(8), pages 1086-1101, August.
    347. Siddhartha Chib & Neil Shephard, 2001. "Comment on Garland B. Durham and A. Ronald Gallant's "Numerical techniques for maximum likelihood estimation of continuous-time diffusion processes"," Economics Papers 2001-W26, Economics Group, Nuffield College, University of Oxford.
    348. Zhigang Tong, 2016. "Option pricing in stochastic volatility models driven by fractional Lévy processes," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 5(1), pages 56-75.
    349. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic Volatility with Leverage: Fast Likelihood Inference," CIRJE F-Series CIRJE-F-297, CIRJE, Faculty of Economics, University of Tokyo.
    350. José Fajardo & Ernesto Mordecki, 2005. "Duality and Derivative Pricing with Time-Changed Lévy Processes," IBMEC RJ Economics Discussion Papers 2005-12, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    351. Bonomo, Marco & Garcia, René & Meddahi, Nour & Tédongap, Roméo, 2015. "The long and the short of the risk-return trade-off," Journal of Econometrics, Elsevier, vol. 187(2), pages 580-592.
    352. Enrique Villamor & Pablo Olivares, 2023. "Valuing Exchange Options under an Ornstein-Uhlenbeck Covariance Model," IJFS, MDPI, vol. 11(2), pages 1-24, March.
    353. Xianfei Hui & Baiqing Sun & Hui Jiang & Indranil SenGupta, 2021. "Analysis of stock index with a generalized BN-S model: an approach based on machine learning and fuzzy parameters," Papers 2101.08984, arXiv.org, revised Feb 2022.
    354. Bernd Hayo & Britta Niehof, 2013. "Studying International Spillovers in a New Keynesian Continuous Time Framework with Financial Markets," MAGKS Papers on Economics 201342, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    355. Friedrich Hubalek & Carlo Sgarra, 2008. "On the Esscher transforms and other equivalent martingale measures for Barndorff-Nielsen and Shephard stochastic volatility models with jumps," Papers 0807.1227, arXiv.org.
    356. Emanuel Derman & Kun Soo Park & Ward Whitt, 2010. "A stochastic-difference-equation model for hedge-fund returns," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 701-733.
    357. Todorov, Viktor & Tauchen, George & Grynkiv, Iaryna, 2011. "Realized Laplace transforms for estimation of jump diffusive volatility models," Journal of Econometrics, Elsevier, vol. 164(2), pages 367-381, October.
    358. R. Merino & J. Pospíšil & T. Sobotka & J. Vives, 2018. "Decomposition Formula For Jump Diffusion Models," Journal of Enterprising Culture (JEC), World Scientific Publishing Co. Pte. Ltd., vol. 21(08), pages 1-36, December.
    359. Benth, Fred Espen & Paraschiv, Florentina, 2018. "A space-time random field model for electricity forward prices," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 203-216.
    360. Anzarut, Michelle & Mena, Ramsés H., 2019. "A Harris process to model stochastic volatility," Econometrics and Statistics, Elsevier, vol. 10(C), pages 151-169.
    361. Semere Habtemicael & Musie Ghebremichael & Indranil SenGupta, 2019. "Volatility and Variance Swap Using Superposition of the Barndorff-Nielsen and Shephard type Lévy Processes," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 75-92, June.
    362. Imma Valentina Curato & Simona Sanfelici, 2019. "Stochastic leverage effect in high-frequency data: a Fourier based analysis," Papers 1910.06660, arXiv.org, revised Mar 2021.
    363. Xiaowei Zhang & Peter W. Glynn, 2018. "Affine Jump-Diffusions: Stochastic Stability and Limit Theorems," Papers 1811.00122, arXiv.org.
    364. Aubain Hilaire Nzokem, 2023. "Pricing European Options under Stochastic Volatility Models: Case of Five-Parameter Variance-Gamma Process," JRFM, MDPI, vol. 16(1), pages 1-28, January.
    365. Hainaut, Donatien & Devolder, Pierre, 2008. "Mortality modelling with Lévy processes," Insurance: Mathematics and Economics, Elsevier, vol. 42(1), pages 409-418, February.
    366. Christian Laudag'e & Florian Aichinger & Sascha Desmettre, 2023. "A Comparative Study of Factor Models for Different Periods of the Electricity Spot Price Market," Papers 2306.07731, arXiv.org, revised Sep 2023.
    367. Olivares Pablo & Villamor Enrique, 2017. "Valuing Exchange Options Under an Ornstein-Uhlenbeck Covariance Model," Papers 1711.10013, arXiv.org.
    368. Eugenie Hol & Siem Jan Koopman, 2000. "Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility," Tinbergen Institute Discussion Papers 00-104/4, Tinbergen Institute.
    369. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    370. Dries Benoit & Rahim Alhamzawi & Keming Yu, 2013. "Bayesian lasso binary quantile regression," Computational Statistics, Springer, vol. 28(6), pages 2861-2873, December.
    371. Yu, Jialin, 2007. "Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese Yuan," Journal of Econometrics, Elsevier, vol. 141(2), pages 1245-1280, December.
    372. Liu, Zhicao & Ye, Yong & Ma, Feng & Liu, Jing, 2017. "Can economic policy uncertainty help to forecast the volatility: A multifractal perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 181-188.
    373. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.
    374. Ole E. Barndorff-Nielsen & Svend Erik Graversen & Neil Shephard, 2003. "Power variation & stochastic volatility: a review and some new results," Economics Papers 2003-W19, Economics Group, Nuffield College, University of Oxford.
    375. Elena Andreou & Eric Ghysels, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," CIRANO Working Papers 2004s-25, CIRANO.
    376. Majewski, Adam A. & Bormetti, Giacomo & Corsi, Fulvio, 2015. "Smile from the past: A general option pricing framework with multiple volatility and leverage components," Journal of Econometrics, Elsevier, vol. 187(2), pages 521-531.
    377. Fang, Libing & Qian, Yichuo & Chen, Ying & Yu, Honghai, 2018. "How does stock market volatility react to NVIX? Evidence from developed countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 490-499.
    378. Sylvia Frühwirth-Schnatter & Leopold Sögner, 2009. "Bayesian estimation of stochastic volatility models based on OU processes with marginal Gamma law," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 159-179, March.
    379. Carmen Broto & Esther Ruiz, 2004. "Estimation methods for stochastic volatility models: a survey," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
    380. Claudia Kluppelberg & Thilo Meyer-Brandis & Andrea Schmidt, 2010. "Electricity spot price modelling with a view towards extreme spike risk," Quantitative Finance, Taylor & Francis Journals, vol. 10(9), pages 963-974.
    381. Raul Merino & Jan Posp'iv{s}il & Tom'av{s} Sobotka & Josep Vives, 2019. "Decomposition formula for jump diffusion models," Papers 1906.06930, arXiv.org.
    382. Ascione, Giacomo & Mehrdoust, Farshid & Orlando, Giuseppe & Samimi, Oldouz, 2023. "Foreign Exchange Options on Heston-CIR Model Under Lévy Process Framework," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    383. Victor, Konev & Serguei, Pergamenchtchikov, 2015. "Robust model selection for a semimartingale continuous time regression from discrete data," Stochastic Processes and their Applications, Elsevier, vol. 125(1), pages 294-326.
    384. Fred Espen Benth & Steen Koekebakker, 2016. "Stochastic modeling of Supramax spot and forward freight rates," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 18(4), pages 391-413, December.
    385. Michael Schröder, 2015. "Discrete-Time Approximation of Functionals in Models of Ornstein–Uhlenbeck Type, with Applications to Finance," Methodology and Computing in Applied Probability, Springer, vol. 17(2), pages 285-313, June.
    386. Indranil SenGupta & William Nganje & Erik Hanson, 2019. "Refinements of Barndorff-Nielsen and Shephard model: an analysis of crude oil price with machine learning," Papers 1911.13300, arXiv.org, revised Mar 2020.
    387. Michele Bianchi & Frank Fabozzi, 2015. "Investigating the Performance of Non-Gaussian Stochastic Intensity Models in the Calibration of Credit Default Swap Spreads," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 243-273, August.
    388. Brockman, Paul & Guo, Tao & Vivero, Maria Gabriela & Yu, Wayne, 2022. "Is idiosyncratic risk priced? The international evidence," Journal of Empirical Finance, Elsevier, vol. 66(C), pages 121-136.
    389. Viktor Bezborodov & Luca Persio & Yuliya Mishura, 2019. "Option Pricing with Fractional Stochastic Volatility and Discontinuous Payoff Function of Polynomial Growth," Methodology and Computing in Applied Probability, Springer, vol. 21(1), pages 331-366, March.
    390. Takuji Arai, 2019. "Pricing and hedging of VIX options for Barndorff-Nielsen and Shephard models," Papers 1904.12260, arXiv.org.
    391. Piergiacomo Sabino, 2021. "Pricing Energy Derivatives in Markets Driven by Tempered Stable and CGMY Processes of Ornstein-Uhlenbeck Type," Papers 2103.13252, arXiv.org.
    392. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Analytic Evaluation of Volatility Forecasts," CIRANO Working Papers 2002s-90, CIRANO.
    393. Gordon R. Richards, 2004. "A fractal forecasting model for financial time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(8), pages 586-601.
    394. Brockwell, Peter J. & Lindner, Alexander, 2015. "CARMA processes as solutions of integral equations," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 221-227.
    395. Bufalo, Michele & Orlando, Giuseppe, 2023. "A three-factor stochastic model for forecasting production of energy materials," Finance Research Letters, Elsevier, vol. 51(C).
    396. Todorov, Viktor, 2019. "Nonparametric inference for the spectral measure of a bivariate pure-jump semimartingale," Stochastic Processes and their Applications, Elsevier, vol. 129(2), pages 419-451.
    397. Takuji Arai & Yuto Imai & Ryoichi Suzuki, 2017. "Local risk-minimization for Barndorff-Nielsen and Shephard models," Finance and Stochastics, Springer, vol. 21(2), pages 551-592, April.
    398. da Fonseca, Regina C.B. & Figueiredo, Annibal & de Castro, Márcio T. & Mendes, Fábio M., 2013. "Generalized Ornstein–Uhlenbeck process by Doob’s theorem and the time evolution of financial prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1671-1680.
    399. Liudas Giraitis, 2004. "LARCH, Leverage, and Long Memory," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 177-210.
    400. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, December.
    401. Nemat Safarov & Colin Atkinson, 2017. "Natural Gas-Fired Power Plants Valuation And Optimization Under Lévy Copulas And Regime Switching," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(01), pages 1-38, February.
    402. Jeanblanc, M. & Pitman, J. & Yor, M., 0. "Self-similar processes with independent increments associated with Lévy and Bessel processes," Stochastic Processes and their Applications, Elsevier, vol. 100(1-2), pages 223-231, July.
    403. Corsi, Fulvio & Fusari, Nicola & La Vecchia, Davide, 2013. "Realizing smiles: Options pricing with realized volatility," Journal of Financial Economics, Elsevier, vol. 107(2), pages 284-304.
    404. Taylor, Nicholas, 2007. "A note on the importance of overnight information in risk management models," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 161-180, January.
    405. Fengkai Yang, 2018. "A Stochastic EM Algorithm for Quantile and Censored Quantile Regression Models," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 555-582, August.
    406. Riccardo Brignone & Carlo Sgarra, 2020. "Asian options pricing in Hawkes-type jump-diffusion models," Annals of Finance, Springer, vol. 16(1), pages 101-119, March.
    407. Giancarlo Salirrosas Mart'inez, 2016. "Biased Roulette Wheel: A Quantitative Trading Strategy Approach," Papers 1609.09601, arXiv.org.
    408. Weiliang Lu & Alexis Arrigoni & Anatoliy Swishchuk & Stéphane Goutte, 2021. "Modelling of Fuel- and Energy-Switching Prices by Mean-Reverting Processes and Their Applications to Alberta Energy Markets," Mathematics, MDPI, vol. 9(7), pages 1-24, March.
    409. P. Brockwell, 2014. "Recent results in the theory and applications of CARMA processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(4), pages 647-685, August.
    410. A. H. Nzokem, 2022. "Pricing European Options under Stochastic Volatility Models: Case of five-Parameter Variance-Gamma Process," Papers 2201.03378, arXiv.org, revised Jan 2023.
    411. Petra Posedel Šimović & Azra Tafro, 2021. "Pricing the Volatility Risk Premium with a Discrete Stochastic Volatility Model," Mathematics, MDPI, vol. 9(17), pages 1-15, August.
    412. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    413. Gero Junike & Wim Schoutens & Hauke Stier, 2022. "Performance of advanced stock price models when it becomes exotic: an empirical study," Annals of Finance, Springer, vol. 18(1), pages 109-119, March.
    414. Michael C. Fu & Bingqing Li & Rongwen Wu & Tianqi Zhang, 2020. "Option Pricing Under a Discrete-Time Markov Switching Stochastic Volatility with Co-Jump Model," Papers 2006.15054, arXiv.org.
    415. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2023. "Shot-noise cojumps: exact simulation and option pricing," LSE Research Online Documents on Economics 111537, London School of Economics and Political Science, LSE Library.
    416. Sandya N. Kumari, 2020. "L¨¦vy Processes in Gold Option Modeling," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 12(2), pages 1-65, February.
    417. Wan-Lun Wang & Luis M. Castro & Yen-Ting Chang & Tsung-I Lin, 2019. "Mixtures of restricted skew-t factor analyzers with common factor loadings," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(2), pages 445-480, June.
    418. Piergiacomo Sabino, 2021. "Normal Tempered Stable Processes and the Pricing of Energy Derivatives," Papers 2105.03071, arXiv.org.
    419. Wergen, Gregor, 2014. "Modeling record-breaking stock prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 114-133.
    420. E. Nicolato & D. Sloth, 2014. "Risk adjustments of option prices under time-changed dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 125-141, January.
    421. Reiichiro Kawai, 2013. "Local Asymptotic Normality Property for Ornstein–Uhlenbeck Processes with Jumps Under Discrete Sampling," Journal of Theoretical Probability, Springer, vol. 26(4), pages 932-967, December.
    422. Sergey S. Stepanov, 2009. "Resilience of Volatility," Papers 0911.5048, arXiv.org.
    423. José Antonio Núñez-Mora & Roberto Joaquín Santillán-Salgado & Mario Iván Contreras-Valdez, 2022. "COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets," Mathematics, MDPI, vol. 10(9), pages 1-36, April.
    424. Lin, Tsung-I & McLachlan, Geoffrey J. & Lee, Sharon X., 2016. "Extending mixtures of factor models using the restricted multivariate skew-normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 398-413.
    425. N. Chopin & P. E. Jacob & O. Papaspiliopoulos, 2013. "SMC-super-2: an efficient algorithm for sequential analysis of state space models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(3), pages 397-426, June.
    426. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.
    427. Grané, Aurea & Veiga, Helena, 2007. "The effect of realised volatility on stock returns risk estimates," DES - Working Papers. Statistics and Econometrics. WS ws076316, Universidad Carlos III de Madrid. Departamento de Estadística.
    428. Palandri, Alessandro, 2015. "Do negative and positive equity returns share the same volatility dynamics?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 486-505.
    429. Lan Zhang, 2012. "Implied and realized volatility: empirical model selection," Annals of Finance, Springer, vol. 8(2), pages 259-275, May.
    430. Takuji Arai, 2020. "Al\`os type decomposition formula for Barndorff-Nielsen and Shephard model," Papers 2005.07393, arXiv.org, revised Sep 2020.
    431. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Realised power variation and stochastic volatility models," Economics Papers 2001-W18, Economics Group, Nuffield College, University of Oxford.
    432. Marino, L. & Menozzi, S., 2023. "Weak well-posedness for a class of degenerate Lévy-driven SDEs with Hölder continuous coefficients," Stochastic Processes and their Applications, Elsevier, vol. 162(C), pages 106-170.
    433. René Garcia & Eric Ghysels & Eric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    434. Ziehaus Christina, 2012. "A note on optimal consumption and investment in a geometric Ornstein–Uhlenbeck market," Statistics & Risk Modeling, De Gruyter, vol. 29(3), pages 269-280, August.
    435. Ma, Feng & Wei, Yu & Huang, Dengshi & Chen, Yixiang, 2014. "Which is the better forecasting model? A comparison between HAR-RV and multifractality volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 171-180.
    436. Jensen Anders Tolver & Lange Theis, 2010. "On Convergence of the QMLE for Misspecified GARCH Models," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-31, June.
    437. Rønn-Nielsen, Anders & Stehr, Mads, 2022. "Extremes of Lévy-driven spatial random fields with regularly varying Lévy measure," Stochastic Processes and their Applications, Elsevier, vol. 150(C), pages 19-49.
    438. Michael Grabchak & Eliana Christou, 2021. "A note on calculating expected shortfall for discrete time stochastic volatility models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-16, December.
    439. Christophe Andrieu & Arnaud Doucet & Roman Holenstein, 2010. "Particle Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 269-342, June.
    440. Yukihiro Tsuzuki, 2013. "Pricing Bounds on Barrier Options (forthcoming in "Journal of Futures Markets")," CARF F-Series CARF-F-325, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    441. Nicholas Salmon & Indranil SenGupta, 2021. "Fractional Barndorff-Nielsen and Shephard model: applications in variance and volatility swaps, and hedging," Papers 2105.02325, arXiv.org.
    442. Suk Kim, Myung & Wang, Suojin, 2006. "On the applicability of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2210-2217, December.
    443. Richard Hawkes & Paresh Date, 2007. "Medium‐term horizon volatility forecasting: A comparative study," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 23(6), pages 465-481, November.
    444. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
    445. Amengual, Dante & Xiu, Dacheng, 2018. "Resolution of policy uncertainty and sudden declines in volatility," Journal of Econometrics, Elsevier, vol. 203(2), pages 297-315.
    446. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2008. "Stochastic Modeling of Electricity and Related Markets," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6811, December.
    447. Genon-Catalot, Valentine & Laredo, Catherine, 2006. "Leroux's method for general hidden Markov models," Stochastic Processes and their Applications, Elsevier, vol. 116(2), pages 222-243, February.
    448. M. C. Jones, 2015. "On Families of Distributions with Shape Parameters," International Statistical Review, International Statistical Institute, vol. 83(2), pages 175-192, August.
    449. Hubalek, Friedrich & Sgarra, Carlo, 2009. "On the Esscher transforms and other equivalent martingale measures for Barndorff-Nielsen and Shephard stochastic volatility models with jumps," Stochastic Processes and their Applications, Elsevier, vol. 119(7), pages 2137-2157, July.
    450. Yang-Ho Park, 2015. "The Effects of Asymmetric Volatility and Jumps on the Pricing of VIX Derivatives," Finance and Economics Discussion Series 2015-71, Board of Governors of the Federal Reserve System (U.S.).
    451. Stephen J. Taylor & Chi‐Feng Tzeng & Martin Widdicks, 2018. "Information about price and volatility jumps inferred from options prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(10), pages 1206-1226, October.
    452. Bregantini, Daniele, 2013. "Moment-based estimation of stochastic volatility," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4755-4764.
    453. Ulrich Hounyo & Rasmus T. Varneskov, 2018. "Inference for Local Distributions at High Sampling Frequencies: A Bootstrap Approach," CREATES Research Papers 2018-16, Department of Economics and Business Economics, Aarhus University.
    454. Carr, Peter & Wu, Liuren, 2004. "Time-changed Levy processes and option pricing," Journal of Financial Economics, Elsevier, vol. 71(1), pages 113-141, January.
    455. Dong, Xiaohui & Wang, Ming & Zhong, Guang-Yan & Yang, Fengzao & Duan, Weilong & Li, Jiang-Cheng & Xiong, Kezhao & Zeng, Chunhua, 2018. "Stochastic delayed kinetics of foraging colony system under non-Gaussian noise," Chaos, Solitons & Fractals, Elsevier, vol. 112(C), pages 1-13.
    456. Vrins, Frédéric, 2016. "Characteristic function of time-inhomogeneous Lévy-driven Ornstein–Uhlenbeck processes," Statistics & Probability Letters, Elsevier, vol. 116(C), pages 55-61.
    457. Anatoliy Swishchuk, 2013. "Modeling and Pricing of Swaps for Financial and Energy Markets with Stochastic Volatilities," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8660, December.
    458. Adland, Roar & Benth, Fred Espen & Koekebakker, Steen, 2018. "Multivariate modeling and analysis of regional ocean freight rates," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 194-221.
    459. Wanyang Dai, 2014. "Mean-variance hedging based on an incomplete market with external risk factors of non-Gaussian OU processes," Papers 1410.0991, arXiv.org, revised Aug 2015.
    460. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    461. Svetlozar Rachev & Stoyan Stoyanov & Frank J. Fabozzi, 2017. "Behavioral Finance Option Pricing Formulas Consistent with Rational Dynamic Asset Pricing," Papers 1710.03205, arXiv.org.
    462. Curato, Imma Valentina, 2019. "Estimation of the stochastic leverage effect using the Fourier transform method," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3207-3238.
    463. Ignatieva, Katja & Wong, Patrick, 2022. "Modelling high frequency crude oil dynamics using affine and non-affine jump–diffusion models," Energy Economics, Elsevier, vol. 108(C).
    464. Wendong Zheng & Pingping Zeng, 2016. "Pricing timer options and variance derivatives with closed-form partial transform under the 3/2 model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 23(5), pages 344-373, September.
    465. Stojanović, Vladica S. & Popović, Biljana Č. & Milovanović, Gradimir V., 2016. "The Split-SV model," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 560-581.
    466. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    467. Matei, Marius, 2011. "Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 116-141, June.
    468. Abdelrazeq, Ibrahim, 2015. "Model verification for Lévy-driven Ornstein–Uhlenbeck processes with estimated parameters," Statistics & Probability Letters, Elsevier, vol. 104(C), pages 26-35.
    469. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    470. Takuji Arai & Yuto Imai & Ryoichi Suzuki, 2015. "Local risk-minimization for Barndorff-Nielsen and Shephard models," Papers 1503.08589, arXiv.org, revised Jan 2016.
    471. Ragnhild Noven & Almut Veraart & Axel Gandy, 2015. "A Lévy-driven rainfall model with applications to futures pricing," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(4), pages 403-432, October.
    472. Yanhui Mi, 2016. "A modified stochastic volatility model based on Gamma Ornstein–Uhlenbeck process and option pricing," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 1-16, June.
    473. Nicola Cufaro Petroni & Piergiacomo Sabino, 2020. "Gamma Related Ornstein-Uhlenbeck Processes and their Simulation," Papers 2003.08810, arXiv.org.
    474. Alexander Kushpel, 2015. "Pricing of high-dimensional options," Papers 1510.07221, arXiv.org.
    475. Piergiacomo Sabino, 2020. "Exact Simulation of Variance Gamma related OU processes: Application to the Pricing of Energy Derivatives," Papers 2004.06786, arXiv.org.
    476. Michele Nguyen & Almut E. D. Veraart, 2017. "Spatio-temporal Ornstein–Uhlenbeck Processes: Theory, Simulation and Statistical Inference," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 46-80, March.
    477. Shuddhasattwa Rafiq & Ruhul Salim, 2014. "Does oil price volatility matter for Asian emerging economies?," Economic Analysis and Policy, Elsevier, vol. 44(4), pages 417-441.
    478. Winston Buckley & Sandun Perera, 2019. "Optimal demand in a mispriced asymmetric Carr–Geman–Madan–Yor (CGMY) economy," Annals of Finance, Springer, vol. 15(3), pages 337-368, September.
    479. Kleppe, Tore Selland & Skaug, Hans Julius, 2012. "Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3105-3119.
    480. Cantia, Catalin & Tunaru, Radu, 2017. "A factor model for joint default probabilities. Pricing of CDS, index swaps and index tranches," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 21-35.
    481. Vladim'ir Hol'y & Petra Tomanov'a, 2018. "Estimation of Ornstein-Uhlenbeck Process Using Ultra-High-Frequency Data with Application to Intraday Pairs Trading Strategy," Papers 1811.09312, arXiv.org, revised Jul 2022.
    482. Albeverio, Sergio & Smii, Boubaker, 2015. "Asymptotic expansions for SDE’s with small multiplicative noise," Stochastic Processes and their Applications, Elsevier, vol. 125(3), pages 1009-1031.
    483. Yuan Li & Kaimon Miyachi & Kenichiro Shiraya & Akira Yamazaki, 2019. "Approximation Method Using Black-Scholes Formula for Barrier Option Pricing under Lévy Models," CARF F-Series CARF-F-454, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, revised Jun 2021.
    484. Jayabrata Biswas & Kiranmoy Das, 2021. "A Bayesian quantile regression approach to multivariate semi-continuous longitudinal data," Computational Statistics, Springer, vol. 36(1), pages 241-260, March.
    485. Corsaro, Stefania & Kyriakou, Ioannis & Marazzina, Daniele & Marino, Zelda, 2019. "A general framework for pricing Asian options under stochastic volatility on parallel architectures," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1082-1095.
    486. Benth, Fred Espen & Rüdiger, Barbara & Süss, Andre, 2018. "Ornstein–Uhlenbeck processes in Hilbert space with non-Gaussian stochastic volatility," Stochastic Processes and their Applications, Elsevier, vol. 128(2), pages 461-486.

  30. Ole E. Barndorff‐Nielsen & Tina Hviid Rydberg, 2000. "Exact Distributional Results for Random Resistance Trees," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(1), pages 129-141, March.

    Cited by:

    1. Letac, Gérard & Wesołowski, Jacek, 2020. "Multivariate reciprocal inverse Gaussian distributions from the Sabot–Tarrès–Zeng integral," Journal of Multivariate Analysis, Elsevier, vol. 175(C).

  31. Barndorff-Nielsen, Ole E. & Pérez-Abreu, Victor, 1999. "Stationary and self-similar processes driven by Lévy processes," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 357-369, December.

    Cited by:

    1. Wiktorsson, Magnus, 2002. "Simulation of stochastic integrals with respect to Lévy processes of type G," Stochastic Processes and their Applications, Elsevier, vol. 101(1), pages 113-125, September.
    2. Grahovac, Danijel, 2020. "Multifractal processes: Definition, properties and new examples," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    3. Rubenthaler, Sylvain & Wiktorsson, Magnus, 2003. "Improved convergence rate for the simulation of stochastic differential equations driven by subordinated Lévy processes," Stochastic Processes and their Applications, Elsevier, vol. 108(1), pages 1-26, November.

  32. O. E. Barndorff‐Nielsen & C. Kluppelberg, 1999. "Tail Exactness of Multivariate Saddlepoint Approximations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 26(2), pages 253-264, June.

    Cited by:

    1. Tore Selland Kleppe & Hans J. Skaug, 2008. "Building and Fitting Non‐Gaussian Latent Variable Models via the Moment‐Generating Function," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 664-676, December.
    2. Varughese, Melvin M., 2013. "Parameter estimation for multivariate diffusion systems," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 417-428.
    3. Theodosopoulos, Ted, 2007. "A reversion of the Chernoff bound," Statistics & Probability Letters, Elsevier, vol. 77(5), pages 558-565, March.
    4. Balkema, August A. & Klüppelberg, Claudia & Resnick, Sidney I., 2003. "Domains of attraction for exponential families," Stochastic Processes and their Applications, Elsevier, vol. 107(1), pages 83-103, September.

  33. Ole E. Barndorff-Nielsen, 1997. "Processes of normal inverse Gaussian type," Finance and Stochastics, Springer, vol. 2(1), pages 41-68.

    Cited by:

    1. Fageot, Julien & Fallah, Alireza & Unser, Michael, 2017. "Multidimensional Lévy white noise in weighted Besov spaces," Stochastic Processes and their Applications, Elsevier, vol. 127(5), pages 1599-1621.
    2. Wenli Zhu & Xinfeng Ruan, 2019. "Pricing Swaps on Discrete Realized Higher Moments Under the Lévy Process," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 507-532, February.
    3. Peter Carr & Liuren Wu, 2004. "Static Hedging of Standard Options," Finance 0409016, University Library of Munich, Germany.
    4. Bujar Huskaj & Marcus Nossman, 2013. "A Term Structure Model for VIX Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(5), pages 421-442, May.
    5. José Fajardo & Aquiles Farias, 2002. "Generalized Hyperbolic Distributions and Brazilian Data," Working Papers Series 52, Central Bank of Brazil, Research Department.
    6. Hui, Wallace & Gel, Yulia R. & Gastwirth, Joseph L., 2008. "lawstat: An R Package for Law, Public Policy and Biostatistics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i03).
    7. Askari, Hossein & Krichene, Noureddine, 2010. "The impact of monetary policy on oil process parameters and market expectations," Global Finance Journal, Elsevier, vol. 21(2), pages 186-200.
    8. Fred Espen Benth & Martin Groth & Rodwell Kufakunesu, 2007. "Valuing Volatility and Variance Swaps for a Non-Gaussian Ornstein-Uhlenbeck Stochastic Volatility Model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(4), pages 347-363.
    9. Barbachan, José Santiago Fajardo, 2003. "Optimal Consumption and Investment with Lévy Processes," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 57(4), October.
    10. Nishant Agrawal & Yaozhong Hu, 2020. "Jump Models with delay -- option pricing and logarithmic Euler-Maruyama scheme," Papers 2010.04287, arXiv.org, revised Oct 2020.
    11. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
    12. Valeria V. Lakshina, 2019. "Do Portfolio Investors Need To Consider The Asymmetry Of Returns On The Russian Stock Market?," HSE Working papers WP BRP 75/FE/2019, National Research University Higher School of Economics.
    13. Svetlana Boyarchenko, 2001. "Capital Accumulation under Non-Gaussian Processes and the Marshallian Law," Penn CARESS Working Papers 471ab9dee66c9aa1d3ef23dd9, Penn Economics Department.
    14. Hiroki Masuda, 2005. "Classical Method of Moments for Partially and Discretely Observed Ergodic Models," Statistical Inference for Stochastic Processes, Springer, vol. 8(1), pages 25-50, January.
    15. Ernst Eberlein & Dilip Madan, 2009. "Sato processes and the valuation of structured products," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 27-42.
    16. Oscar Gutierrez, 2008. "Option valuation, time-changed processes and the fast Fourier transform," Quantitative Finance, Taylor & Francis Journals, vol. 8(2), pages 103-108.
    17. Hasanjan Sayit, 2022. "A discussion of stochastic dominance and mean-risk optimal portfolio problems based on mean-variance-mixture models," Papers 2202.02488, arXiv.org, revised Jul 2023.
    18. Cui, Zhenyu & Lars Kirkby, J. & Nguyen, Duy, 2019. "A general framework for time-changed Markov processes and applications," European Journal of Operational Research, Elsevier, vol. 273(2), pages 785-800.
    19. Gong, Xiaoli & Zhuang, Xintian, 2017. "Measuring financial risk and portfolio reversion with time changed tempered stable Lévy processes," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 148-159.
    20. Grahovac, Danijel & Leonenko, Nikolai N. & Taqqu, Murad S., 2019. "Limit theorems, scaling of moments and intermittency for integrated finite variance supOU processes," Stochastic Processes and their Applications, Elsevier, vol. 129(12), pages 5113-5150.
    21. Kirkby, J. Lars & Mitra, Sovan & Nguyen, Duy, 2020. "An analysis of dollar cost averaging and market timing investment strategies," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1168-1186.
    22. Fischer, Thomas & Lundtofte , Frederik, 2018. "Unequal Returns: Using the Atkinson Index to Measure Financial Risk," Working Papers 2018:25, Lund University, Department of Economics.
    23. Kirkby, J. Lars & Nguyen, Duy, 2021. "Equity-linked Guaranteed Minimum Death Benefits with dollar cost averaging," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 408-428.
    24. Martin Keller-Ressel, 2008. "Moment Explosions and Long-Term Behavior of Affine Stochastic Volatility Models," Papers 0802.1823, arXiv.org, revised Oct 2008.
    25. Takuji Arai & Yuto Imai & Ryo Nakashima, 2018. "Numerical analysis on quadratic hedging strategies for normal inverse Gaussian models," Papers 1801.05597, arXiv.org.
    26. A. Alexandre Trindade & Abootaleb Shirvani & Xiaohan Ma, 2020. "A Socioeconomic Well-Being Index," Applied Economics and Finance, Redfame publishing, vol. 7(4), pages 48-62, July.
    27. Christensen, Troels Sønderby & Pircalabu, Anca & Høg, Esben, 2019. "A seasonal copula mixture for hedging the clean spark spread with wind power futures," Energy Economics, Elsevier, vol. 78(C), pages 64-80.
    28. Yang, Seungho & Oh, Gabjin, 2020. "A Bayesian estimation of exponential Lévy models for implied volatility smile," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    29. Anne Laure Bronstein & Gilles Pages & Benedikt Wilbertz, 2010. "How to speed up the quantization tree algorithm with an application to swing options," Quantitative Finance, Taylor & Francis Journals, vol. 10(9), pages 995-1007.
    30. Laurent E. Calvet & Adlai J. Fisher, 2006. "Multifrequency Jump-Diffusions: An Equilibrium Approach," NBER Working Papers 12797, National Bureau of Economic Research, Inc.
    31. Amirhossein Sobhani & Mariyan Milev, 2017. "A Numerical Method for Pricing Discrete Double Barrier Option by Lagrange Interpolation on Jacobi Node," Papers 1712.01060, arXiv.org, revised Feb 2018.
    32. Cao, Wenbin & Guernsey, Scott B. & Linn, Scott C., 2018. "Evidence of infinite and finite jump processes in commodity futures prices: Crude oil and natural gas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 629-641.
    33. Hsieh, Ming-hua & Wang, Jennifer L. & Chiu, Yu-Fen & Chen, Yen-Chih, 2018. "Valuation of variable long-term care Annuities with Guaranteed Lifetime Withdrawal Benefits: A variance reduction approach," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 246-254.
    34. Michael Samet & Christian Bayer & Chiheb Ben Hammouda & Antonis Papapantoleon & Ra'ul Tempone, 2022. "Optimal Damping with Hierarchical Adaptive Quadrature for Efficient Fourier Pricing of Multi-Asset Options in L\'evy Models," Papers 2203.08196, arXiv.org, revised Oct 2023.
    35. Fajardo, J., 2004. "Equivalent Martingale Measures and Lévy Processes," Finance Lab Working Papers flwp_61, Finance Lab, Insper Instituto de Ensino e Pesquisa.
    36. Gong, Xiao-li & Zhuang, Xin-tian, 2016. "Option pricing and hedging for optimized Lévy driven stochastic volatility models," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 118-127.
    37. Gel, Yulia R., 2010. "Test of fit for a Laplace distribution against heavier tailed alternatives," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 958-965, April.
    38. Julien Fageot & Michael Unser & John Paul Ward, 2020. "The $$n$$n-term Approximation of Periodic Generalized Lévy Processes," Journal of Theoretical Probability, Springer, vol. 33(1), pages 180-200, March.
    39. Gong, Xiaoli & Zhuang, Xintian, 2017. "Pricing foreign equity option under stochastic volatility tempered stable Lévy processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 83-93.
    40. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    41. Nguyen Thanh Long, 2002. "Analytical Aproach to Value Options with State Variables of a Levy System," Finance 0207004, University Library of Munich, Germany, revised 19 Jan 2003.
    42. Li, Minqiang & Peng, Liang & Qi, Yongcheng, 2011. "Reduce computation in profile empirical likelihood method," MPRA Paper 33744, University Library of Munich, Germany.
    43. Svetlana Boyarchenko & Sergei Levendorskii, 2004. "American options: the EPV pricing model," Finance 0405024, University Library of Munich, Germany.
    44. Gurjeet Dhesi & Bilal Shakeel & Marcel Ausloos, 2021. "Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach," Annals of Operations Research, Springer, vol. 299(1), pages 1397-1410, April.
    45. Nishant Agrawal & Yaozhong Hu, 2020. "Jump Models with Delay—Option Pricing and Logarithmic Euler–Maruyama Scheme," Mathematics, MDPI, vol. 8(11), pages 1-21, November.
    46. Zorana Grbac & David Krief & Peter Tankov, 2018. "Long-time trajectorial large deviations for affine stochastic volatility models and application to variance reduction for option pricing," Papers 1809.06153, arXiv.org.
    47. Griffin, J.E. & Steel, M.F.J., 2006. "Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility," Journal of Econometrics, Elsevier, vol. 134(2), pages 605-644, October.
    48. Massoud Heidari & Liuren WU, 2002. "Are Interest Rate Derivatives Spanned by the Term Structure of Interest Rates?," Finance 0207013, University Library of Munich, Germany.
    49. Lindström, Erik & Ströjby, Jonas & Brodén, Mats & Wiktorsson, Magnus & Holst, Jan, 2008. "Sequential calibration of options," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2877-2891, February.
    50. Piccirilli, Marco & Schmeck, Maren Diane & Vargiolu, Tiziano, 2019. "Capturing the power options smile by an additive two-factor model for overlapping futures prices," Center for Mathematical Economics Working Papers 625, Center for Mathematical Economics, Bielefeld University.
    51. Oleg Kudryavtsev & Antonino Zanette, 2013. "Efficient pricing of swing options in L�vy-driven models," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 627-635, March.
    52. Bin Xie & Weiping Li & Nan Liang, 2021. "Pricing S&P 500 Index Options with L\'evy Jumps," Papers 2111.10033, arXiv.org, revised Nov 2021.
    53. Fred Espen Benth & Jurate Saltyte-Benth, 2005. "Stochastic Modelling of Temperature Variations with a View Towards Weather Derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(1), pages 53-85.
    54. Fred Espen Benth & Paul Kettler, 2010. "Dynamic copula models for the spark spread," Quantitative Finance, Taylor & Francis Journals, vol. 11(3), pages 407-421.
    55. Shuang Li & Yanli Zhou & Yonghong Wu & Xiangyu Ge, 2017. "Equilibrium approach of asset and option pricing under Lévy process and stochastic volatility," Australian Journal of Management, Australian School of Business, vol. 42(2), pages 276-295, May.
    56. Jing-zhi Huang & Liuren Wu, 2004. "Specification Analysis of Option Pricing Models Based on Time-Changed Levy Processes," Econometric Society 2004 North American Winter Meetings 405, Econometric Society.
    57. Gong, Xiaoli & Zhuang, Xintian, 2017. "American option valuation under time changed tempered stable Lévy processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 57-68.
    58. Hinderks, W.J. & Wagner, A., 2020. "Factor models in the German electricity market: Stylized facts, seasonality, and calibration," Energy Economics, Elsevier, vol. 85(C).
    59. Roberto Marfè, 2012. "A generalized variance gamma process for financial applications," Quantitative Finance, Taylor & Francis Journals, vol. 12(1), pages 75-87, June.
    60. Weilong Fu & Ali Hirsa, 2019. "A fast method for pricing American options under the variance gamma model," Papers 1903.07519, arXiv.org.
    61. Jose Luis Alayon G., 2015. "Distribucion hiperbolica generalizada: una aplicacion en la seleccion de portafolios y en cuantificacion de medidas de riesgo de mercado," Revista de Economía del Rosario, Universidad del Rosario, vol. 18(2), pages 249-308, December.
    62. Nilsson, Birger & Hansson, Björn, 2004. "A Two-State Capital Asset Pricing Model with Unobservable States," Working Papers 2004:28, Lund University, Department of Economics.
    63. Mercik, Szymon & Weron, Rafal, 2002. "Origins of scaling in FX markets," MPRA Paper 2294, University Library of Munich, Germany.
    64. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.
    65. Gong, Xiaoli & Zhuang, Xintian, 2016. "Option pricing for stochastic volatility model with infinite activity Lévy jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 455(C), pages 1-10.
    66. Weiwei Guo & Lingfei Li, 2019. "Parametric inference for discretely observed subordinate diffusions," Statistical Inference for Stochastic Processes, Springer, vol. 22(1), pages 77-110, April.
    67. Michele Bianchi & Frank Fabozzi, 2015. "Investigating the Performance of Non-Gaussian Stochastic Intensity Models in the Calibration of Credit Default Swap Spreads," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 243-273, August.
    68. Lakshina, Valeriya, 2020. "Do portfolio investors need to consider the asymmetry of returns on the Russian stock market?," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    69. Ali Hirsa & Weilong Fu, 2020. "An unsupervised deep learning approach in solving partial integro-differential equations," Papers 2006.15012, arXiv.org, revised Dec 2020.
    70. Asante Gyamerah, Samuel & Ngare, Philip & Ikpe, Dennis, 2018. "A Levy Regime-Switching Temperature Dynamics Model for Weather Derivatives," MPRA Paper 89680, University Library of Munich, Germany, revised 10 Jul 2018.
    71. E. Nicolato & D. Sloth, 2014. "Risk adjustments of option prices under time-changed dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 125-141, January.
    72. José Antonio Núñez-Mora & Roberto Joaquín Santillán-Salgado & Mario Iván Contreras-Valdez, 2022. "COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets," Mathematics, MDPI, vol. 10(9), pages 1-36, April.
    73. Mr. Noureddine Krichene, 2008. "Crude Oil Prices: Trends and Forecast," IMF Working Papers 2008/133, International Monetary Fund.
    74. Fu, Jun & Yang, Hailiang, 2012. "Equilibruim approach of asset pricing under Lévy process," European Journal of Operational Research, Elsevier, vol. 223(3), pages 701-708.
    75. Carr, Peter & Wu, Liuren, 2004. "Time-changed Levy processes and option pricing," Journal of Financial Economics, Elsevier, vol. 71(1), pages 113-141, January.
    76. Evis Këllezi & Nick Webber, 2004. "Valuing Bermudan options when asset returns are Levy processes," Quantitative Finance, Taylor & Francis Journals, vol. 4(1), pages 87-100.
    77. Ma, Chao & Ma, Qinghua & Yao, Haixiang & Hou, Tiancheng, 2018. "An accurate European option pricing model under Fractional Stable Process based on Feynman Path Integral," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 87-117.
    78. Peter Tankov & Laura Tinsi, 2021. "Decision making with dynamic probabilistic forecasts," Papers 2106.16047, arXiv.org.
    79. Silvia Lavagnini, 2021. "Pricing Asian Options with Correlators," Papers 2104.11684, arXiv.org.
    80. Feng, Chengxiao & Tan, Jie & Jiang, Zhenyu & Chen, Shuang, 2020. "A generalized European option pricing model with risk management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

  34. O. Barndorff-Nielsen, 1995. "Quasi profile and directed likelihoods from estimating functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 47(3), pages 461-464, September.

    Cited by:

    1. Gianfranco Adimari & Laura Ventura, 2002. "Quasi-likelihood fromM-estimators: A numerical comparison with empirical likelihood," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(2), pages 175-185, June.
    2. G. Adimari & L. Ventura, 2002. "Quasi-Profile Log Likelihoods for Unbiased Estimating Functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 54(2), pages 235-244, June.
    3. Stefano Cabras & María Castellanos & Erlis Ruli, 2014. "A Quasi likelihood approximation of posterior distributions for likelihood-intractable complex models," METRON, Springer;Sapienza Università di Roma, vol. 72(2), pages 153-167, August.

  35. Barndorff-Nielsen, O. E. & Sorensen, M., 1991. "Information quantities in non-classical settings," Computational Statistics & Data Analysis, Elsevier, vol. 12(2), pages 143-158, September.

    Cited by:

    1. Küchler, Uwe & Sørensen, Michael M., 1998. "A note on limit theorems for multivariate martingales," SFB 373 Discussion Papers 1998,45, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  36. Barndorff-Nielsen, O. E. & Jørgensen, B., 1991. "Some parametric models on the simplex," Journal of Multivariate Analysis, Elsevier, vol. 39(1), pages 106-116, October.

    Cited by:

    1. Wanke, Peter & Barros, C.P., 2016. "Efficiency in Latin American airlines: A two-stage approach combining Virtual Frontier Dynamic DEA and Simplex Regression," Journal of Air Transport Management, Elsevier, vol. 54(C), pages 93-103.
    2. Lucio Masserini & Matilde Bini & Monica Pratesi, 2017. "Effectiveness of non-selective evaluation test scores for predicting first-year performance in university career: a zero-inflated beta regression approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 693-708, March.
    3. Silvia De Nicol`o & Maria Rosaria Ferrante & Silvia Pacei, 2021. "Mind the Income Gap: Bias Correction of Inequality Estimators in Small-Sized Samples," Papers 2107.08950, arXiv.org, revised May 2023.
    4. Malini Iyengar & Dipak Dey, 2002. "A semiparametric model for compositional data analysis in presence of covariates on the simplex," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 11(2), pages 303-315, December.
    5. Rodrigues, Antonio Carlos & Martins, Ricardo Silveira & Wanke, Peter Fernandes & Siegler, Janaina, 2018. "Efficiency of specialized 3PL providers in an emerging economy," International Journal of Production Economics, Elsevier, vol. 205(C), pages 163-178.
    6. Chunsheng Ma, 2023. "Vector Random Fields on the Probability Simplex with Metric-Dependent Covariance Matrix Functions," Journal of Theoretical Probability, Springer, vol. 36(3), pages 1922-1938, September.
    7. Hui Song & Yingwei Peng & Dongsheng Tu, 2017. "Jointly modeling longitudinal proportional data and survival times with an application to the quality of life data in a breast cancer trial," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 183-206, April.
    8. Jay Verkuilen & Michael Smithson, 2012. "Mixed and Mixture Regression Models for Continuous Bounded Responses Using the Beta Distribution," Journal of Educational and Behavioral Statistics, , vol. 37(1), pages 82-113, February.
    9. Abdelhakim Aknouche & Stefanos Dimitrakopoulos, 2023. "Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 393-417, July.
    10. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.
    11. Rashad A. R. Bantan & Christophe Chesneau & Farrukh Jamal & Mohammed Elgarhy & Muhammad H. Tahir & Aqib Ali & Muhammad Zubair & Sania Anam, 2020. "Some New Facts about the Unit-Rayleigh Distribution with Applications," Mathematics, MDPI, vol. 8(11), pages 1-23, November.
    12. Peter Xue-Kun Song & Ming Tan, 2000. "Marginal Models for Longitudinal Continuous Proportional Data," Biometrics, The International Biometric Society, vol. 56(2), pages 496-502, June.
    13. Zhenguo Qiu & Peter X.‐K. Song & Ming Tan, 2008. "Simplex Mixed‐Effects Models for Longitudinal Proportional Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 577-596, December.
    14. Seitebaleng Makgai & Andriette Bekker & Mohammad Arashi, 2021. "Compositional Data Modeling through Dirichlet Innovations," Mathematics, MDPI, vol. 9(19), pages 1-18, October.
    15. Josmar Mazucheli & Bruna Alves & Mustafa Ç. Korkmaz & Víctor Leiva, 2022. "Vasicek Quantile and Mean Regression Models for Bounded Data: New Formulation, Mathematical Derivations, and Numerical Applications," Mathematics, MDPI, vol. 10(9), pages 1-23, April.
    16. Rosineide Fernando da Paz & Jorge Luis Bazán & Luis Aparecido Milan, 2017. "Bayesian estimation for a mixture of simplex distributions with an unknown number of components: HDI analysis in Brazil," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(9), pages 1630-1643, July.
    17. Hoyle, Edward & Hughston, Lane P. & Macrina, Andrea, 2011. "Lévy random bridges and the modelling of financial information," Stochastic Processes and their Applications, Elsevier, vol. 121(4), pages 856-884, April.
    18. Patrícia L. Espinheira & Alisson Oliveira Silva, 2020. "Residual and influence analysis to a general class of simplex regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 523-552, June.
    19. Ongaro, A. & Migliorati, S., 2013. "A generalization of the Dirichlet distribution," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 412-426.
    20. Ricardo Rasmussen Petterle & Wagner Hugo Bonat & Cassius Tadeu Scarpin, 2019. "Quasi-beta Longitudinal Regression Model Applied to Water Quality Index Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 346-368, June.
    21. Barros, C.P. & Wanke, Peter & Dumbo, Silvestre & Manso, Jose Pires, 2017. "Efficiency in angolan hydro-electric power station: A two-stage virtual frontier dynamic DEA and simplex regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 588-596.
    22. Wenting Liu & Huiqiong Li & Anmin Tang & Zixin Cui, 2023. "Bayesian Joint Modeling Analysis of Longitudinal Proportional and Survival Data," Mathematics, MDPI, vol. 11(16), pages 1-17, August.

  37. O. Barndorff-Nielsen & P. Jupp, 1989. "Approximating exponential models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 41(2), pages 247-267, June.

    Cited by:

    1. Ivanov, Alexander V. & Zwanzig, Silvelyn, 2002. "Saddlepoint Expansions in Linear Regression," Journal of Multivariate Analysis, Elsevier, vol. 83(1), pages 183-207, October.

  38. Barndorff-Nielsen, O. & Blæsild, P. & Halgreen, C., 1978. "First hitting time models for the generalized inverse Gaussian distribution," Stochastic Processes and their Applications, Elsevier, vol. 7(1), pages 49-54, March.

    Cited by:

    1. Lemonte, Artur J. & Cordeiro, Gauss M., 2011. "The exponentiated generalized inverse Gaussian distribution," Statistics & Probability Letters, Elsevier, vol. 81(4), pages 506-517, April.
    2. Thabane, Lehana & Drekic, Steve, 2003. "Hypothesis testing for the generalized multivariate modified Bessel model," Journal of Multivariate Analysis, Elsevier, vol. 86(2), pages 360-374, August.
    3. Jedidi, Wissem & Simon, Thomas, 2015. "Diffusion hitting times and the bell-shape," Statistics & Probability Letters, Elsevier, vol. 102(C), pages 38-41.
    4. Eduardo A Aponte & Dario Schöbi & Klaas E Stephan & Jakob Heinzle, 2017. "The Stochastic Early Reaction, Inhibition, and late Action (SERIA) model for antisaccades," PLOS Computational Biology, Public Library of Science, vol. 13(8), pages 1-36, August.
    5. Hariya, Yuu, 2020. "On some identities in law involving exponential functionals of Brownian motion and Cauchy random variable," Stochastic Processes and their Applications, Elsevier, vol. 130(10), pages 5999-6037.
    6. Matsumoto, Hiroyuki & Yor, Marc, 2003. "Interpretation via Brownian motion of some independence properties between GIG and gamma variables," Statistics & Probability Letters, Elsevier, vol. 61(3), pages 253-259, February.

  39. Barndorff-Nielsen, O. & Schou, G., 1973. "On the parametrization of autoregressive models by partial autocorrelations," Journal of Multivariate Analysis, Elsevier, vol. 3(4), pages 408-419, December.

    Cited by:

    1. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    2. Ng, Chi Tim & Joe, Harry, 2010. "Generating random AR(p) and MA(q) Toeplitz correlation matrices," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1532-1545, July.
    3. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-time measurement of business conditions," International Finance Discussion Papers 901, Board of Governors of the Federal Reserve System (U.S.).
    4. Del Negro, Marco & Schorfheide, Frank, 2005. "Monetary policy analysis with potentially misspecified models," Working Paper Series 475, European Central Bank.
    5. Meyer-Gohde, Alexander & Neuhoff, Daniel, 2018. "Generalized exogenous processes in DSGE: A Bayesian approach," IMFS Working Paper Series 125, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    6. Ku, Simon F., 1997. "Limited distribution of sample partial autocorrelations: A matrix approach," Stochastic Processes and their Applications, Elsevier, vol. 72(1), pages 121-143, December.
    7. Tobias Hartl & Roland Weigand, 2018. "Approximate State Space Modelling of Unobserved Fractional Components," Papers 1812.09142, arXiv.org, revised May 2020.
    8. Zhihao Xu & Clifford M. Hurvich, 2021. "A Unified Frequency Domain Cross-Validatory Approach to HAC Standard Error Estimation," Papers 2108.06093, arXiv.org, revised Jun 2023.
    9. Gabriele Fiorentini & Alessandro Galesi & Enrique Sentana, 2014. "A Spectral EM Algorithm for Dynamic Factor Models," Working Papers wp2014_1411, CEMFI.
    10. Heikki Kauppi, 2008. "Yield-Curve Based Probit Models for Forecasting U.S. Recessions: Stability and Dynamics," Discussion Papers 31, Aboa Centre for Economics.
    11. Bladt Martin & McNeil Alexander J., 2022. "Time series with infinite-order partial copula dependence," Dependence Modeling, De Gruyter, vol. 10(1), pages 87-107, January.
    12. Paroli, Roberta & Spezia, Luigi, 2008. "Bayesian inference in non-homogeneous Markov mixtures of periodic autoregressions with state-dependent exogenous variables," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2311-2330, January.
    13. Gabriele Fiorentini & Enrique Sentana, 2014. "Neglected Serial Correlation Tests in UCARIMA Models," Working Papers wp2014_1406, CEMFI.
    14. Tommaso Proietti & Alessandra Luati, 2015. "Generalised partial autocorrelations and the mutual information between past and future," CREATES Research Papers 2015-24, Department of Economics and Business Economics, Aarhus University.
    15. Philippe, Anne, 2006. "Bayesian analysis of autoregressive moving average processes with unknown orders," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1904-1923, December.
    16. O. Anderson, 1976. "Some new Time Sdries results," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 23(1), pages 65-76, December.
    17. Chen, Cathy W.S. & Yu, Tiffany H.K., 2005. "Long-term dependence with asymmetric conditional heteroscedasticity in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 413-424.
    18. Daniel Neuhoff, 2015. "Dynamics of Real Per Capita GDP," SFB 649 Discussion Papers SFB649DP2015-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper 410, Tor Vergata University, CEIS, revised 19 Jul 2017.
    20. McLeod, A. Ian & Zhang, Ying, 2008. "Improved Subset Autoregression: With R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i02).
    21. Pötscher, Benedikt M. & Preinerstorfer, David, 2018. "Controlling the size of autocorrelation robust tests," Journal of Econometrics, Elsevier, vol. 207(2), pages 406-431.
    22. Chen, Tianbo & Sun, Ying & Li, Ta-Hsin, 2021. "A semi-parametric estimation method for the quantile spectrum with an application to earthquake classification using convolutional neural network," Computational Statistics & Data Analysis, Elsevier, vol. 154(C).
    23. Proietti, Tommaso & Luati, Alessandra, 2013. "The Exponential Model for the Spectrum of a Time Series: Extensions and Applications," MPRA Paper 45280, University Library of Munich, Germany.
    24. Ilya Archakov & Peter Reinhard Hansen & Yiyao Luo, 2022. "A New Method for Generating Random Correlation Matrices," Papers 2210.08147, arXiv.org.
    25. McLeod, A.I. & Zhang, Y., 2008. "Faster ARMA maximum likelihood estimation," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2166-2176, January.
    26. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    27. Fitzgibbon, L.J., 2006. "On sampling stationary autoregressive model parameters uniformly in r2 value," Statistics & Probability Letters, Elsevier, vol. 76(4), pages 349-352, February.
    28. Wang, Wan-Lun & Fan, Tsai-Hung, 2012. "Bayesian analysis of multivariate t linear mixed models using a combination of IBF and Gibbs samplers," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 300-310.
    29. Sigrunn Holbek Sørbye & Håvard Rue, 2017. "Penalised Complexity Priors for Stationary Autoregressive Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 923-935, November.
    30. Zhang, Y. & McLeod, A.I., 2006. "Fitting MA(q) models in the closed invertible region," Statistics & Probability Letters, Elsevier, vol. 76(13), pages 1331-1334, July.
    31. Luigi Spezia & Andy Vinten & Roberta Paroli & Marc Stutter, 2021. "An evolutionary Monte Carlo method for the analysis of turbidity high‐frequency time series through Markov switching autoregressive models," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
    32. Paul Labonne & Martin Weale, 2018. "Temporal disaggregation of overlapping noisy quarterly data using state space models: Estimation of monthly business sector output from Value Added Tax data in the UK," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-18, Economic Statistics Centre of Excellence (ESCoE).
    33. Dégerine, Serge & Lambert-Lacroix, Sophie, 2003. "Characterization of the partial autocorrelation function of nonstationary time series," Journal of Multivariate Analysis, Elsevier, vol. 87(1), pages 46-59, October.
    34. Smith, Michael Stanley & Maneesoonthorn, Worapree, 2018. "Inversion copulas from nonlinear state space models with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 34(3), pages 389-407.
    35. Bingham, N.H. & Inoue, Akihiko & Kasahara, Yukio, 2012. "An explicit representation of Verblunsky coefficients," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 403-410.
    36. Martin Bladt & Alexander J. McNeil, 2021. "Time series models with infinite-order partial copula dependence," Papers 2107.00960, arXiv.org.
    37. Wang, Wan-Lun & Fan, Tsai-Hung, 2010. "ECM-based maximum likelihood inference for multivariate linear mixed models with autoregressive errors," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1328-1341, May.
    38. Shaman, Paul, 2010. "Generalized Levinson-Durbin sequences, binomial coefficients and autoregressive estimation," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1263-1273, May.
    39. Maria Barbieri & Caterina Conigliani, 1998. "Bayesian analysis of autoregressive time series with change points," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 7(3), pages 243-255, December.

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