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Limit theorems for multipower variation in the presence of jumps

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Cited by:

  1. Christensen, Kim & Oomen, Roel & Podolskij, Mark, 2010. "Realised quantile-based estimation of the integrated variance," Journal of Econometrics, Elsevier, vol. 159(1), pages 74-98, November.
  2. Kolokolov, Aleksey & Livieri, Giulia & Pirino, Davide, 2020. "Statistical inferences for price staleness," Journal of Econometrics, Elsevier, vol. 218(1), pages 32-81.
  3. Cheng, Mingmian & Liao, Yuan & Yang, Xiye, 2023. "Uniform predictive inference for factor models with instrumental and idiosyncratic betas," Journal of Econometrics, Elsevier, vol. 237(2).
  4. Vetter, Mathias & Podolskij, Mark, 2006. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," Technical Reports 2006,51, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  5. 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.
  6. Busch, Thomas & Christensen, Bent Jesper & Nielsen, Morten Ørregaard, 2011. "The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets," Journal of Econometrics, Elsevier, vol. 160(1), pages 48-57, January.
  7. Tauchen, George & Zhou, Hao, 2011. "Realized jumps on financial markets and predicting credit spreads," Journal of Econometrics, Elsevier, vol. 160(1), pages 102-118, January.
  8. 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.
  9. Almut Veraart, 2011. "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(3), pages 253-291, September.
  10. 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.
  11. 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.
  12. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  13. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2013. "Econometric modeling of exchange rate volatility and jumps," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 16, pages 373-427, Edward Elgar Publishing.
  14. 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.
  15. repec:hal:journl:peer-00732538 is not listed on IDEAS
  16. 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.
  17. Vetter, Mathias, 2010. "Limit theorems for bipower variation of semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 120(1), pages 22-38, January.
  18. Christensen, Kim & Oomen, Roel C.A. & Podolskij, Mark, 2014. "Fact or friction: Jumps at ultra high frequency," Journal of Financial Economics, Elsevier, vol. 114(3), pages 576-599.
  19. Corsi, Fulvio & Pirino, Davide & Renò, Roberto, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Journal of Econometrics, Elsevier, vol. 159(2), pages 276-288, December.
  20. Todorov, Viktor & Tauchen, George, 2010. "Activity signature functions for high-frequency data analysis," Journal of Econometrics, Elsevier, vol. 154(2), pages 125-138, February.
  21. 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.
  22. 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.
  23. 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.
  24. Prosper Dovonon & Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2019. "Bootstrapping High-Frequency Jump Tests," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 793-803, April.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2011. "A Functional Filtering and Neighborhood Truncation Approach to Integrated Quarticity Estimation," CREATES Research Papers 2011-23, Department of Economics and Business Economics, Aarhus University.
  30. Duong, Diep & Swanson, Norman R., 2015. "Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction," Journal of Econometrics, Elsevier, vol. 187(2), pages 606-621.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
  37. Park, Joon Y. & Wang, Bin, 2021. "Nonparametric estimation of jump diffusion models," Journal of Econometrics, Elsevier, vol. 222(1), pages 688-715.
  38. 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.
  39. 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.).
  40. 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.
  41. Federico M. Bandi & Roberto Reno, 2009. "Nonparametric Stochastic Volatility," Global COE Hi-Stat Discussion Paper Series gd08-035, Institute of Economic Research, Hitotsubashi University.
  42. Kolokolov, Aleksey & Livieri, Giulia & Pirino, Davide, 2018. "Statistical inferences for price staleness," SAFE Working Paper Series 236, Leibniz Institute for Financial Research SAFE.
  43. 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.
  44. 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.
  45. 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).
  46. 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.
  47. Patrick Chang, 2020. "Fourier instantaneous estimators and the Epps effect," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-24, September.
  48. Christensen, K. & Podolskij, M. & Thamrongrat, N. & Veliyev, B., 2017. "Inference from high-frequency data: A subsampling approach," Journal of Econometrics, Elsevier, vol. 197(2), pages 245-272.
  49. Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten Ørregaard Nielsen, 2010. "Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 233-261.
  50. Per A. Mykland & Neil Shephard & Kevin Sheppard, 2012. "Efficient and feasible inference for the components of financial variation using blocked multipower variation," Economics Papers 2012-W02, Economics Group, Nuffield College, University of Oxford.
  51. 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.).
  52. Andersen, Torben G. & Li, Yingying & Todorov, Viktor & Zhou, Bo, 2023. "Volatility measurement with pockets of extreme return persistence," Journal of Econometrics, Elsevier, vol. 237(2).
  53. 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.
  54. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
  55. Mark Podolskij & Mathias Vetter, 2010. "Understanding limit theorems for semimartingales: a short survey," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(s1), pages 329-351.
  56. 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.
  57. 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.
  58. 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.
  59. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Inference for Integrated Volatility," Departmental Working Papers 200616, Rutgers University, Department of Economics.
  60. 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.
  61. 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.
  62. 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.
  63. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
  64. Liu, Guangying & Zhang, Xinsheng, 2011. "Power variation of fractional integral processes with jumps," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 962-972, August.
  65. 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.
  66. 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.
  67. 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.
  68. 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.
  69. 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).
  70. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
  71. 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.
  72. 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.
  73. 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.
  74. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility Regressions with Fat Tails," TSE Working Papers 20-1097, Toulouse School of Economics (TSE).
  75. 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.
  76. 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.
  77. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
  78. 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.
  79. 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).
  80. Hacène Djellout & Hui Jiang, 2015. "Large Deviations Of The Threshold Estimator Of Integrated (Co-)Volatility Vector In The Presence Of Jumps," Working Papers hal-01147189, HAL.
  81. 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.
  82. Kanaya, Shin & Otsu, Taisuke, 2012. "Large deviations of realized volatility," Stochastic Processes and their Applications, Elsevier, vol. 122(2), pages 546-581.
  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. Jihyun Kim & Nour Meddahi, 2020. "Volatility Regressions with Fat Tails," Post-Print hal-03142647, HAL.
  85. Hacène Djellout & Arnaud Guillin & Yacouba Samoura, 2014. "Large Deviations Of The Realized (Co-)Volatility Vector," Working Papers hal-01082903, HAL.
  86. 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.
  87. 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.
  88. 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.
  89. 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.
  90. 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.
  91. 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.
  92. repec:hal:journl:peer-00741630 is not listed on IDEAS
  93. Hacène Djellout & Arnaud Guillin & Yacouba Samoura, 2017. "Large Deviations Of The Realized (Co-)Volatility Vector," Post-Print hal-01082903, HAL.
  94. 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.
  95. Kalnina, Ilze, 2011. "Subsampling high frequency data," Journal of Econometrics, Elsevier, vol. 161(2), pages 262-283, April.
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