IDEAS home Printed from https://ideas.repec.org/e/c/pla169.html
   My authors  Follow this author

Sébastien Laurent
(Sebastien Laurent)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Jérôme Lahaye & Sébastien Laurent & Christopher J. Neely, 2011. "Jumps, cojumps and macro announcements," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 893-921, September.

    Mentioned in:

    1. Jumps, cojumps and macro announcements (Journal of Applied Econometrics 2011) in ReplicationWiki ()

Working papers

  1. F. Blasques & Christian Francq & Sébastien Laurent, 2023. "Quasi score-driven models," Post-Print hal-04069143, HAL.

    Cited by:

    1. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Tinbergen Institute Discussion Papers 24-051/III, Tinbergen Institute, revised 22 Oct 2024.
    2. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.
    3. Francq, Christian & Zakoian, Jean-Michel, 2024. "Finite moments testing in a general class of nonlinear time series models," MPRA Paper 121193, University Library of Munich, Germany.
    4. Francisco Blasques & Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2024. "Robust Multivariate Observation-Driven Filtering for a Common Stochastic Trend: Theory and Application," Tinbergen Institute Discussion Papers 24-062/III, Tinbergen Institute.
    5. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    6. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    7. Pierluigi Vallarino, 2024. "Dynamic kernel models," Tinbergen Institute Discussion Papers 24-082/III, Tinbergen Institute.
    8. Yinhao Wu & Ping He, 2024. "The continuous-time limit of quasi score-driven volatility models," Papers 2409.14734, arXiv.org, revised Jun 2025.
    9. van Os, Bram & van Dijk, Dick, 2024. "Accelerating peak dating in a dynamic factor Markov-switching model," International Journal of Forecasting, Elsevier, vol. 40(1), pages 313-323.

  2. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2022. "We modeled long memory with just one lag!," LIDAM Discussion Papers CORE 2022016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Shikta Sing & Supun Chandrasena & Yue Shi & Abdullah Alhussain & Claude Diebolt & Martin Enilov & Tapas Mishra, 2024. "A Learning Model with Memory in the Financial Markets," Working Papers of BETA 2024-41, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    2. Anna Mikusheva & Mikkel S{o}lvsten, 2023. "Linear Regression with Weak Exogeneity," Papers 2308.08958, arXiv.org, revised Jan 2024.
    3. Jie Wang & Yongqiao Wang, 2025. "Forecasting Expected Shortfall and Value‐at‐Risk With Cross‐Sectional Aggregation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 391-423, March.
    4. del Barrio Castro, Tomas & Escribano, Alvaro & Sibbertsen, Philipp, 2024. "Modeling and Forecasting the Long Memory of Cyclical Trends in Paleoclimate Data," Hannover Economic Papers (HEP) dp-722, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  3. Sébastien Laurent & Shuping Shi, 2022. "Unit Root Test with High-Frequency Data," Post-Print hal-03543167, HAL.

    Cited by:

    1. Richard Mawulawoe Ahadzie & Nagaratnam Jeyasreedharan, 2024. "Higher‐order moments and asset pricing in the Australian stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 75-128, March.
    2. H. Peter Boswijk & Jun Yu & Yang Zu, 2024. "Testing for an Explosive Bubble using High-Frequency Volatility," Working Papers 202402, University of Macau, Faculty of Business Administration.
    3. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    4. 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.
    5. Cui, Tianxiang & Suleman, Muhammad Tahir & Zhang, Hongwei, 2022. "Do the green bonds overreact to the COVID-19 pandemic?," Finance Research Letters, Elsevier, vol. 49(C).

  4. Francisco Blasques & Christian Francq & Sébastien Laurent, 2020. "A New Class of Robust Observation-Driven Models," Tinbergen Institute Discussion Papers 20-073/III, Tinbergen Institute.

    Cited by:

    1. F. Blasques & Christian Francq & Sébastien Laurent, 2023. "Quasi score-driven models," Post-Print hal-04069143, HAL.
    2. Labonne, Paul, 2025. "Asymmetric uncertainty: Nowcasting using skewness in real-time data," International Journal of Forecasting, Elsevier, vol. 41(1), pages 229-250.
    3. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).

  5. Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," AMSE Working Papers 1845, Aix-Marseille School of Economics, France.

    Cited by:

    1. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    2. David Ardia & S'ebastien Laurent & Rosnel Sessinou, 2024. "High-Dimensional Mean-Variance Spanning Tests," Papers 2403.17127, arXiv.org.
    3. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    4. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling and Estimation," Papers 2206.14275, arXiv.org, revised Jan 2025.
    5. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    6. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).
    7. Boubacar Maïnassara, Y. & Kadmiri, O. & Saussereau, B., 2022. "Estimation of multivariate asymmetric power GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    8. 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.
    9. Chen Tong & Peter Reinhard Hansen, 2025. "Dynamic Factor Correlation Model," Papers 2503.01080, arXiv.org.
    10. Stefano Grassi & Francesco Violante, 2021. "Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas," CREATES Research Papers 2021-05, Department of Economics and Business Economics, Aarhus University.
    11. Simon Hediger & Jeffrey Näf & Marc S. Paolella & Paweł Polak, 2023. "Heterogeneous tail generalized common factor modeling," Digital Finance, Springer, vol. 5(2), pages 389-420, June.
    12. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    13. Hsiang‐Tai Lee, 2022. "A Markov regime‐switching Cholesky GARCH model for directly estimating the dynamic of optimal hedge ratio," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 389-412, March.

  6. Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.

    Cited by:

    1. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019. "Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure," Papers 1902.10991, arXiv.org, revised Dec 2020.
    2. Luc Bauwens & Guillaume Chevillon & Sébastien Laurent, 2023. "We modeled long memory with just one lag!," Post-Print hal-04185755, HAL.
    3. Anna Mikusheva & Mikkel S{o}lvsten, 2023. "Linear Regression with Weak Exogeneity," Papers 2308.08958, arXiv.org, revised Jan 2024.
    4. 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.
    5. 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.
    6. Javier Haulde & Morten Ørregaard Nielsen, 2022. "Fractional integration and cointegration," CREATES Research Papers 2022-02, Department of Economics and Business Economics, Aarhus University.
    7. 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.

  7. Sébastien Laurent & Shuping Shi, 2018. "Volatility Estimation and Jump Detection for drift-diffusion Processes," AMSE Working Papers 1843, Aix-Marseille School of Economics, France.

    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. Linyu Wang & Yifan Ji & Zhongxin Ni, 2024. "Which implied volatilities contain more information? Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1896-1919, April.
    5. Shuping Shi & Peter C. B. Phillips, 2022. "Econometric Analysis of Asset Price Bubbles," Cowles Foundation Discussion Papers 2331, Cowles Foundation for Research in Economics, Yale University.
    6. Chae-Deug, Yi, 2024. "Realized normal volatility and maximum outlying jumps in high frequency returns for Korean won–US Dollar," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    7. Cui, Tianxiang & Suleman, Muhammad Tahir & Zhang, Hongwei, 2022. "Do the green bonds overreact to the COVID-19 pandemic?," Finance Research Letters, Elsevier, vol. 49(C).
    8. Yucheng Sun, 2024. "Testing for jumps with robust spot volatility estimators," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 78(1), pages 79-104, February.
    9. 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).

  8. Christophe Hurlin & Sébastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2017. "Risk Measure Inference," Post-Print hal-01457393, HAL.

    Cited by:

    1. Francq, Christian & Zakoian, Jean-Michel, 2019. "Virtual Historical Simulation for estimating the conditional VaR of large portfolios," MPRA Paper 95965, University Library of Munich, Germany.
    2. Francq, Christian & Zakoian, Jean-Michel, 2015. "Looking for efficient qml estimation of conditional value-at-risk at multiple risk levels," MPRA Paper 67195, University Library of Munich, Germany.
    3. Michael B. Gordy & Alexander J. McNeil, 2018. "Spectral Backtests of Forecast Distributions with Application to Risk Management," Finance and Economics Discussion Series 2018-021, Board of Governors of the Federal Reserve System (U.S.).
    4. Hassanniakalager, Arman & Baker, Paul L. & Platanakis, Emmanouil, 2024. "A False Discovery Rate approach to optimal volatility forecasting model selection," International Journal of Forecasting, Elsevier, vol. 40(3), pages 881-902.
    5. Wided Khiari & Salim Ben Sassi, 2019. "On Identifying the Systemically Important Tunisian Banks: An Empirical Approach Based on the △CoVaR Measures," Risks, MDPI, vol. 7(4), pages 1-15, December.
    6. Sarlin, Peter & Holopainen, Markus, 2016. "Toward robust early-warning models: a horse race, ensembles and model uncertainty," Working Paper Series 1900, European Central Bank.
    7. Markus Holopainen & Peter Sarlin, 2015. "Toward robust early-warning models: A horse race, ensembles and model uncertainty," Papers 1501.04682, arXiv.org, revised Apr 2016.
    8. Ophélie Couperier & Jérémy Leymarie, 2020. "Backtesting Expected Shortfall via Multi-Quantile Regression," Working Papers halshs-01909375, HAL.
    9. Saidane, Dhafer & Sène, Babacar & Désiré Kanga, Kouamé, 2021. "Pan-African banks, banking interconnectivity: A new systemic risk measure in the WAEMU," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    10. Hurlin, Christophe & Leymarie, Jérémy & Patin, Antoine, 2018. "Loss functions for Loss Given Default model comparison," European Journal of Operational Research, Elsevier, vol. 268(1), pages 348-360.
    11. Raphaëlle BELLANDO & Oana TOADER, 2017. "An analysis of banks’ weaknesses in the light of stress tests," LEO Working Papers / DR LEO 2479, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.

  9. Sébastien Laurent & Christelle Lecourt & Franz C. Palm, 2016. "Testing for jumps in conditionally Gaussian ARMA-GARCH models, a robust approach," Post-Print hal-01447861, HAL.

    Cited by:

    1. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    2. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    3. Charles, Amélie & Darné, Olivier, 2019. "Volatility estimation for Bitcoin: Replication and robustness," International Economics, Elsevier, vol. 157(C), pages 23-32.
    4. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    5. Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    6. Michael Frömmel & Eyup Kadioglu, 2023. "Impact of trading hours extensions on foreign exchange volatility: intraday evidence from the Moscow exchange," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    7. Francq, Christian & Zakoian, Jean-Michel, 2019. "Virtual Historical Simulation for estimating the conditional VaR of large portfolios," MPRA Paper 95965, University Library of Munich, Germany.
    8. Tafakori, Laleh & Pourkhanali, Armin & Fard, Farzad Alavi, 2018. "Forecasting spikes in electricity return innovations," Energy, Elsevier, vol. 150(C), pages 508-526.
    9. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    10. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    11. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    12. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2020. "On the pernicious effects of oil price uncertainty on US real economic activities," Empirical Economics, Springer, vol. 59(6), pages 2689-2715, December.
    13. 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.
    14. Thomas Chuffart & Emmanuel Flachaire & Anne Péguin-Feissolle, 2017. "Testing for misspecification in the short-run component of GARCH-type models," Post-Print hal-03157205, HAL.
    15. Semei Coronado & Rangan Gupta & Besma Hkiri & Omar Rojas, 2020. "Time-Varying Spillover between Currency and Stock Markets in the United States: More than Two Centuries of Historical Evidence," Working Papers 202060, University of Pretoria, Department of Economics.
    16. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2021. "Oil Price Shocks, Real Economic Activity and Uncertainty," Post-Print hal-03284089, HAL.
    17. 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).
    18. Yinhao Wu & Ping He, 2024. "The continuous-time limit of quasi score-driven volatility models," Papers 2409.14734, arXiv.org, revised Jun 2025.
    19. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    20. Mike K. P. So & Wing Ki Liu & Amanda M. Y. Chu, 2018. "Bayesian Shrinkage Estimation Of Time-Varying Covariance Matrices In Financial Time Series," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 369-404, December.
    21. Xu, Fang & Bouri, Elie & Cepni, Oguzhan, 2022. "Blockchain and crypto-exposed US companies and major cryptocurrencies: The role of jumps and co-jumps," Finance Research Letters, Elsevier, vol. 50(C).
    22. Amélie Charles & Olivier Darné, 0. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 0, pages 1-24.
    23. Elie Bouri, 2019. "The Effect of Jumps in the Crude Oil Market on the Sovereign Risks of Major Oil Exporters," Risks, MDPI, vol. 7(4), pages 1-15, December.
    24. Carnero M. Angeles & Pérez Ana, 2021. "Outliers and misleading leverage effect in asymmetric GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(1), pages 1-19, February.
    25. Acereda, Beatriz & Leon, Angel & Mora, Juan, 2020. "Estimating the expected shortfall of cryptocurrencies: An evaluation based on backtesting," Finance Research Letters, Elsevier, vol. 33(C).
    26. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    27. Semei Coronado & Rangan Gupta & Besma Hkiri & Omar Rojas, 2020. "Time-Varying Spillovers between Currency and Stock Markets in the USA: Historical Evidence From More than Two Centuries," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(4), pages 44-76, December.
    28. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    29. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    30. Mudassar Hasan & Muhammad Abubakr Naeem & Muhammad Arif & Syed Jawad Hussain Shahzad & Xuan Vinh Vo, 2022. "Liquidity connectedness in cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    31. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    32. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    33. Collet, Jerome & Ielpo, Florian, 2018. "Sector spillovers in credit markets," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 267-278.
    34. 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.

  10. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.

    Cited by:

    1. Kregždė Arvydas & Kišonaitė Karolina, 2018. "Co-movements of Lithuanian and Central European Stock Markets Across Different Time Horizons: A Wavelet Approach," Ekonomika (Economics), Sciendo, vol. 97(2), pages 55-69, December.
    2. Elena Ivona Dumitrescu & Georgiana-Denisa Banulescu, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," Post-Print hal-03331122, HAL.
    3. Denisa Georgiana Banulescu & Ferrara Laurent & Marsilli Clément, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," Working Papers hal-03563168, HAL.
    4. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
    5. 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.

  11. Alain Hecq & Franz C. Palm & Sébastien Laurent, 2016. "On the Univariate Representation of BEKK Models with Common Factors," Post-Print hal-01440307, HAL.

    Cited by:

    1. 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.
    2. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019. "Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure," Papers 1902.10991, arXiv.org, revised Dec 2020.
    3. Dovonon, Prosper & Renault, Eric, 2011. "Testing for Common GARCH Factors," MPRA Paper 40224, University Library of Munich, Germany.
    4. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    5. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    6. 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.
    7. Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
    8. Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2015. "Long Memory Through Marginalization of Large Systems and Hidden Cross-Section Dependence," Working Papers hal-01158524, HAL.
    9. 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.

  12. Christian M. Hafner & Sebastien Laurent & Francesco Violante, 2015. "Weak diffusion limits of dynamic conditional correlation models," CREATES Research Papers 2015-03, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Ding, Yashuang (Dexter), 2023. "A simple joint model for returns, volatility and volatility of volatility," Journal of Econometrics, Elsevier, vol. 232(2), pages 521-543.
    2. Tao Chen & Yixuan Li & Renfang Tian, 2023. "A Functional Data Approach for Continuous-Time Analysis Subject to Modeling Discrepancy under Infill Asymptotics," Mathematics, MDPI, vol. 11(20), pages 1-27, October.
    3. Christian M. Hafner & Sébastien Laurent & Francesco Violante, 2017. "Weak Diffusion Limits of Dynamic Conditional Correlation Models," Post-Print hal-01590010, HAL.
    4. Yinhao Wu & Ping He, 2024. "The continuous-time limit of quasi score-driven volatility models," Papers 2409.14734, arXiv.org, revised Jun 2025.
    5. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    6. Ding, Y., 2020. "Diffusion Limits of Real-Time GARCH," Cambridge Working Papers in Economics 20112, Faculty of Economics, University of Cambridge.

  13. Chevillon, Guillaume & Hecq , Alain & Laurent, Sébastien, 2015. "Long Memory Through Marginalization of Large Systems and Hidden Cross-Section Dependence," ESSEC Working Papers WP1507, ESSEC Research Center, ESSEC Business School.

    Cited by:

    1. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.
    2. Hecq Alain & Laurent Sébastien & Palm Franz C., 2016. "On the Univariate Representation of BEKK Models with Common Factors," Journal of Time Series Econometrics, De Gruyter, vol. 8(2), pages 91-113, July.

  14. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg, 2014. "Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity," CREATES Research Papers 2014-05, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.
    2. Nabil Bouamara & Kris Boudt & Sebastien Laurent & Christopher J. Neely, 2024. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Working Papers 2024-006, Federal Reserve Bank of St. Louis.
    3. Serge Darolles & Christian Francq & Sebastien Laurent, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-04590180, HAL.
    4. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Discussion Papers CORE 2016001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Cai, Zhanrui & Li, Changcheng & Wen, Jiawei & Yang, Songshan, 2024. "Asset splitting algorithm for ultrahigh dimensional portfolio selection and its theoretical property," Journal of Econometrics, Elsevier, vol. 239(2).
    6. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    7. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    8. Francq, Christian & Zakoian, Jean-Michel, 2019. "Virtual Historical Simulation for estimating the conditional VaR of large portfolios," MPRA Paper 95965, University Library of Munich, Germany.
    9. 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.
    10. Sébastien Laurent & Shuping Shi, 2018. "Volatility Estimation and Jump Detection for drift-diffusion Processes," Working Papers halshs-01944449, HAL.
    11. 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).
    12. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    13. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).
    14. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    15. 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.

  15. Deniz Erdemlioglu & Sebastien Laurent & Christopher J. Neely, 2013. "Which continuous-time model is most appropriate for exchange rates?," Working Papers 2013-024, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Kam Fong Chan & Phil Gray & Zheyao Pan, 2021. "The profitability of trading on large Lévy jumps," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 627-635, June.
    2. 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).
    3. Jerome Lahaye & Christopher J. Neely, 2014. "The role of jumps in volatility spillovers in foreign exchange markets: meteor shower and heat waves revisited," Working Papers 2014-034, Federal Reserve Bank of St. Louis.
    4. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.

  16. 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.

    Cited by:

    1. Abimelech Paye Gbatu & Zhen Wang & Presley K. Wesseh Jr. & Isaac Yak Repha Tutdel, 2017. "Causal Effects and Dynamic Relationship between Exchange Rate Volatility and Economic Development in Liberia," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 119-131.
    2. Imane El Ouadghiri & Remzi Uctum, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01386027, HAL.
    3. 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.
    4. Imane El Ouadghiri & Valérie Mignon & Nicolas Boitout, 2014. "On the impact of macroeconomic news surprises on Treasury-bond yields," Working Papers hal-04141345, HAL.
    5. Cynthia Royal Tori & Scott L. Tori, 2019. "Swedish krona-euro return volatility and non-traditional monetary policies," Economics Bulletin, AccessEcon, vol. 39(3), pages 2162-2174.
    6. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in Equilibrium Prices and Asymmetric News in Foreign Exchange Markets," Working Papers hal-04141414, HAL.
    7. Nicolas Boitout & Imane El Ouadghiri & Valérie Mignon, 2016. "On the impact of macroeconomic news surprises on Treasury-bond returns," Post-Print hal-01386014, HAL.
    8. Das, Suman & Roy, Saikat Sinha, 2023. "Following the leaders? A study of co-movement and volatility spillover in BRICS currencies," Economic Systems, Elsevier, vol. 47(2).
    9. Oshinloye, Micheal & Onanuga, Olaronke & Onanuga, Abayomi, 2015. "Exchange Rate Behaviour in the West Africa Monetary Zone: A GARCH Approach," MPRA Paper 83324, University Library of Munich, Germany.
    10. 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.
    11. 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.
    12. Su, Fei, 2021. "Conditional volatility persistence and volatility spillovers in the foreign exchange market," Research in International Business and Finance, Elsevier, vol. 55(C).
    13. Dondukova Oyuna & Liu Yaobin, 2021. "Forecasting the Crude Oil Prices Volatility With Stochastic Volatility Models," SAGE Open, , vol. 11(3), pages 21582440211, July.
    14. 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, January-A.
    15. Mohini GUPTA & Purwa SRIVASTAVA & Amritkant MISHRA & Malayaranjan SAHOO, 2021. "Time-varying volatility spillover of foreign exchange rate in three Asian markets: Based on DCC-GARCH approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(629), W), pages 105-120, Winter.

  17. 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).

    Cited by:

    1. Cifter, Atilla, 2012. "Volatility Forecasting with Asymmetric Normal Mixture Garch Model: Evidence from South Africa," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 127-142, June.
    2. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    3. Sucarrat, Genaro, 2020. "Identification of Volatility Proxies as Expectations of Squared Financial Return," MPRA Paper 101953, University Library of Munich, Germany.
    4. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Yam Wing Siu, 2018. "Volatility Forecast by Volatility Index and Its Use as a Risk Management Tool Under a Value-at-Risk Approach," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-48, June.
    6. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    7. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    8. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
    9. Sucarrat, Genaro, 2021. "Identification of volatility proxies as expectations of squared financial returns," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1677-1690.

  18. Lambert, Philippe & Laurent, Sebastien & Veredas, David, 2012. "Testing conditional asymmetry: A residual-based approach," LIDAM Reprints ISBA 2012006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
    2. Marcelo Fernandes & Eduardo Mendes & Olivier Scaillet, 2015. "Testing for symmetry and conditional symmetry using asymmetric kernels," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 649-671, August.
    3. Denisa Banulescu & Christophe Hurlin & Jeremy Leymarie & Olivier Scaillet, 2020. "Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures," Working Papers halshs-03088668, HAL.
    4. Elena Andreou & Bas J.M. Werker, 2014. "Residual-based Rank Specification Tests for AR-GARCH type models," University of Cyprus Working Papers in Economics 02-2014, University of Cyprus Department of Economics.
    5. Yves Dominicy & Hiroaki Ogata & David Veredas, 2013. "Inference for vast dimensional elliptical distributions," Computational Statistics, Springer, vol. 28(4), pages 1853-1880, August.
    6. Andreou, Elena & Werker, Bas J.M., 2015. "Residual-based rank specification tests for AR–GARCH type models," Journal of Econometrics, Elsevier, vol. 185(2), pages 305-331.
    7. Harry-Paul Vander Elst, 2015. "FloGARCH: Realizing Long Memory and Asymmetries in Returns Valitility," Working Papers ECARES ECARES 2015-12, ULB -- Universite Libre de Bruxelles.
    8. Werker, Bas J M & Andreou, Elena, 2013. "Residual-based Rank Specification Tests for AR-GARCH type models," CEPR Discussion Papers 9583, C.E.P.R. Discussion Papers.
    9. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).

  19. Hecq, A.W. & Laurent, S.F.J.A. & Palm, F.C., 2011. "On the univariate representation of multivariate volatility models with common factors," Research Memorandum 011, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).

    Cited by:

    1. 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.

  20. 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).

    Cited by:

    1. 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).
    2. Balázs Égert & Evžen Kočenda, 2014. "The impact of macro news and central bank communication on emerging European forex markets," Post-Print hal-01385932, HAL.
    3. Min Zhu & Yuping Song & Xin Zheng, 2025. "Volatility Dynamics and Mixed Jump-GARCH Model Based Jump Detection in Financial Markets," Computational Economics, Springer;Society for Computational Economics, vol. 65(5), pages 2545-2577, May.
    4. Khademalomoom, Siroos & Narayan, Paresh Kumar, 2020. "Intraday-of-the-week effects: What do the exchange rate data tell us?," Emerging Markets Review, Elsevier, vol. 43(C).
    5. Bibinger, Markus & Neely, Christopher & Winkelmann, Lars, 2018. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," IRTG 1792 Discussion Papers 2018-055, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Imane El Ouadghiri & Remzi Uctum, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01386027, HAL.
    7. 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.
    8. 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.
    9. 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.
    10. 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).
    11. Nabil Bouamara & Kris Boudt & Sebastien Laurent & Christopher J. Neely, 2024. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Working Papers 2024-006, Federal Reserve Bank of St. Louis.
    12. 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).
    13. Fuess, Roland & Grabellus, Markus & Mager, Ferdinand & Stein, Michael, 2015. "Something in the Air: Information Density, News Surprises, and Price Jumps," Working Papers on Finance 1517, University of St. Gallen, School of Finance.
    14. 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.
    15. Toan Luu Duc Huynh & Tobias Burggraf, 2020. "If worst comes to worst: Co-movement of global stock markets in the US-China trade war," Economics and Business Letters, Oviedo University Press, vol. 9(1), pages 21-30.
    16. Jena, Sangram Keshari & Tiwari, Aviral Kumar & Hammoudeh, Shawkat & Roubaud, David, 2019. "Distributional predictability between commodity spot and futures: Evidence from nonparametric causality-in-quantiles tests," Energy Economics, Elsevier, vol. 78(C), pages 615-628.
    17. Vitali Alexeev & Mardi Dungey, 2015. "Equity portfolio diversification with high frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1205-1215, July.
    18. 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.
    19. Kerssenfischer, Mark & Schmeling, Maik, 2024. "What moves markets?," Journal of Monetary Economics, Elsevier, vol. 145(C).
    20. Lian, Yu-Min & Chen, Jun-Home & Liao, Szu-Lang, 2021. "Cojump risks and their impacts on option pricing," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 399-410.
    21. Osler, Carol & Savaser, Tanseli, 2011. "Extreme returns: The case of currencies," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2868-2880, November.
    22. Özbekler, Ali Gencay & Kontonikas, Alexandros & Triantafyllou, Athanasios, 2021. "Volatility forecasting in European government bond markets," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1691-1709.
    23. Mardi Dungey & Matteo Luciani & David Veredas, 2012. "Ranking Systemically Important Financial Institutions," Tinbergen Institute Discussion Papers 12-115/IV/DSF44, Tinbergen Institute.
    24. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2018. "Systemic risk in the US: Interconnectedness as a circuit breaker," Economic Modelling, Elsevier, vol. 71(C), pages 305-315.
    25. 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.
    26. 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.
    27. 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.
    28. Amal Abricha & Amine Ben Amar & Makram Bellalah, 2024. "Commodity futures markets under stress and stress-free periods: Further insights from a quantile connectedness approach," Post-Print hal-04515196, HAL.
    29. Robert G. Bowman & Kam Fong Chan & Christopher J. Neely, 2017. "Systematic Cojumps, Market Component Portfolios and Scheduled Macroeconomic Announcements," Working Papers 2017-11, Federal Reserve Bank of St. Louis.
    30. Mohammad Isleimeyyeh & Amine Ben Amar & Stéphane Goutte & Ramzi Benkraiem, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," Post-Print hal-03674806, HAL.
    31. 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.
    32. Fricke, Christoph, 2012. "Expected and unexpected bond excess returns: Macroeconomic and market microstructure effects," Hannover Economic Papers (HEP) dp-493, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    33. Julien Chevallier & Florian Ielpo, 2013. "Volatility spillovers in commodity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 20(13), pages 1211-1227, September.
    34. 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.
    35. 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.
    36. Paiardini, Paola, 2014. "The impact of economic news on bond prices: Evidence from the MTS platform," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 302-322.
    37. 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).
    38. 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.
    39. 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).
    40. Deniz Erdemlioglu & Nikola Gradojevic, 2020. "Heterogeneous investment horizons, risk regimes, and realized jumps," Post-Print hal-02995997, HAL.
    41. Kam Fong Chan & Phil Gray & Zheyao Pan, 2021. "The profitability of trading on large Lévy jumps," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 627-635, June.
    42. 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).
    43. Elie Bouri & Rangan Gupta & Xuan Vinh Vo, 2022. "Jumps in Geopolitical Risk and the Cryptocurrency Market: The Singularity of Bitcoin," Defence and Peace Economics, Taylor & Francis Journals, vol. 33(2), pages 150-161, February.
    44. Funke, Michael & Shu, Chang & Cheng, Xiaoqiang & Eraslan, Sercan, 2015. "Assessing the CNH–CNY pricing differential: Role of fundamentals, contagion and policy," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 245-262.
    45. Charles S. Bos & Pawel Janus & Siem Jan Koopman, 2009. "Spot Variance Path Estimation and its Application to High Frequency Jump Testing," Tinbergen Institute Discussion Papers 09-110/4, Tinbergen Institute.
    46. Winkelmann, Lars & Bibinger, Markus & Linzert, Tobias, 2013. "ECB monetary policy surprises: identification through cojumps in interest rates," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79721, Verein für Socialpolitik / German Economic Association.
    47. Imane El Ouadghiri & Valérie Mignon & Nicolas Boitout, 2014. "On the impact of macroeconomic news surprises on Treasury-bond yields," Working Papers hal-04141345, HAL.
    48. 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.
    49. 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.
    50. Gomez-Gonzalez, Jose Eduardo & Hirs-Garzon, Jorge & Uribe, Jorge M., 2020. "Spillovers beyond the variance: exploring the natural gas and oil higher order risk linkages with the global financial markets," Working papers 46, Red Investigadores de Economía.
    51. Gene Birz & Sandip Dutta & Han Yu, 2022. "Economic forecasts, anchoring bias, and stock returns," Financial Management, Financial Management Association International, vol. 51(1), pages 169-191, March.
    52. Ederington, Louis & Guan, Wei & Yang, Lisa (Zongfei), 2019. "The impact of the U.S. employment report on exchange rates," Journal of International Money and Finance, Elsevier, vol. 90(C), pages 257-267.
    53. 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.
    54. Novotný, Jan & Petrov, Dmitri & Urga, Giovanni, 2015. "Trading price jump clusters in foreign exchange markets," Journal of Financial Markets, Elsevier, vol. 24(C), pages 66-92.
    55. Arouri, Mohamed & M’saddek, Oussama & Nguyen, Duc Khuong & Pukthuanthong, Kuntara, 2019. "Cojumps and asset allocation in international equity markets," Journal of Economic Dynamics and Control, Elsevier, vol. 98(C), pages 1-22.
    56. 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.
    57. 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.
    58. Gomez-Gonzalez, Jose E. & Hirs-Garzon, Jorge & Uribe, Jorge M., 2022. "Spillovers beyond the variance: Exploring the higher order risk linkages between commodity markets and global financial markets," Journal of Commodity Markets, Elsevier, vol. 28(C).
    59. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    60. Hans DEWACHTER & Deniz ERDEMLIOGLU & Jean-Yves GNABO & Christelle LECOURT, 2013. "The intra-day impact of communication on euro-dollar volatility and jumps," Working Papers of Department of Economics, Leuven ces13.04, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    61. 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.
    62. Massimiliano Caporin & Aleksey Kolokolov & Roberto RenoÕ, 2014. "Multi-jumps," "Marco Fanno" Working Papers 0185, Dipartimento di Scienze Economiche "Marco Fanno".
      • Caporin, Massimiliano & Kolokolov, Aleksey & Renò, Roberto, 2014. "Multi-jumps," MPRA Paper 58175, University Library of Munich, Germany.
    63. Wenying Yao & Mardi Dungey & Vitali Alexeev, 2020. "Modelling Financial Contagion Using High Frequency Data," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 314-330, September.
    64. Rognone, Lavinia & Hyde, Stuart & Zhang, S. Sarah, 2020. "News sentiment in the cryptocurrency market: An empirical comparison with Forex," International Review of Financial Analysis, Elsevier, vol. 69(C).
    65. Jan Hanousek & Ev??en Ko??enda & Jan Novotn??, 2013. "Price Jumps on European Stock Markets," William Davidson Institute Working Papers Series wp1059, William Davidson Institute at the University of Michigan.
    66. Alekseev, Oleg & Janda, Karel & Petit, Mathieu & Zilberman, David, 2024. "Return and volatility spillovers between the raw material and electric vehicles markets," Energy Economics, Elsevier, vol. 137(C).
    67. 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.
    68. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in Equilibrium Prices and Asymmetric News in Foreign Exchange Markets," Working Papers hal-04141414, HAL.
    69. Lars Winkelmann & Wenying Yao, 2023. "Tests for Jumps in Yield Spreads," Berlin School of Economics Discussion Papers 0024, Berlin School of Economics.
    70. 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.
    71. Caporin, Massimiliano & Poli, Francesco, 2022. "News and intraday jumps: Evidence from regularization and class imbalance," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    72. 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.
    73. 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).
    74. 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.
    75. Debasish Maitra & Varun Dawar, 2019. "Return and Volatility Spillover among Commodity Futures, Stock Market and Exchange Rate: Evidence from India," Global Business Review, International Management Institute, vol. 20(1), pages 214-237, February.
    76. 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.
    77. Jerome Lahaye & Christopher J. Neely, 2014. "The role of jumps in volatility spillovers in foreign exchange markets: meteor shower and heat waves revisited," Working Papers 2014-034, Federal Reserve Bank of St. Louis.
    78. 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.
    79. 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.
    80. Chen, Ke & Vitiello, Luiz & Hyde, Stuart & Poon, Ser-Huang, 2018. "The reality of stock market jumps diversification," Journal of International Money and Finance, Elsevier, vol. 86(C), pages 171-188.
    81. 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.
    82. 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.
    83. Boudt, Kris & Petitjean, Mikael, 2014. "Intraday liquidity dynamics and news releases around price jumps: Evidence from the DJIA stocks," LIDAM Reprints LFIN 2014006, Université catholique de Louvain, Louvain Finance (LFIN).
    84. 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.
    85. 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.
    86. 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).
    87. Bibinger, Markus & Winkelmann, Lars, 2013. "Econometrics of co-jumps in high-frequency data with noise," SFB 649 Discussion Papers 2013-021, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    88. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2014. "Identifying periods of financial stress in Asian currencies: the role of high frequency financial market data," Working Papers 2014-12, University of Tasmania, Tasmanian School of Business and Economics.
    89. Lian, Yu-Min & Chen, Jun-Home, 2019. "Portfolio selection in a multi-asset, incomplete-market economy," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 228-238.
    90. Erdemlioglu, Deniz & Laurent, Sébastien & Neely, Christopher J., 2015. "Which continuous-time model is most appropriate for exchange rates?," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 256-268.
    91. 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).
    92. Qian, Ya & Tu, Jun & Härdle, Wolfgang Karl, 2019. "Information Arrival, News Sentiment, Volatilities and Jumps of Intraday Returns," IRTG 1792 Discussion Papers 2019-002, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    93. Bruce Mizrach & Christopher J. Neely, 2007. "The microstructure of the U.S. treasury market," Working Papers 2007-052, Federal Reserve Bank of St. Louis.
    94. Gkillas, Konstantinos & Konstantatos, Christoforos & Tsagkanos, Athanasios & Siriopoulos, Costas, 2021. "Do economic news releases affect tail risk? Evidence from an emerging market," Finance Research Letters, Elsevier, vol. 40(C).
    95. 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).
    96. 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.
    97. Lee, Suzanne S. & Wang, Minho, 2020. "Tales of tails: Jumps in currency markets," Journal of Financial Markets, Elsevier, vol. 48(C).
    98. Denisa Georgiana Banulescu & Ferrara Laurent & Marsilli Clément, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," Working Papers hal-03563168, HAL.
    99. Maghyereh, Aktham I. & Awartani, Basel, 2016. "Dynamic transmissions between Sukuk and bond markets," Research in International Business and Finance, Elsevier, vol. 38(C), pages 246-261.
    100. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
    101. Lian, Yu-Min & Chen, Jun-Home & Liao, Szu-Lang, 2024. "Pricing derivatives on foreign assets using Markov-modulated cojump-diffusion dynamics," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 503-519.
    102. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    103. Kuttu, Saint & Aboagye, Anthony Q.Q. & Bokpin, Godfred A., 2018. "Evidence of time-varying conditional discrete jump dynamics in sub-Saharan African foreign exchange markets," Research in International Business and Finance, Elsevier, vol. 46(C), pages 211-226.
    104. 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.
    105. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.
    106. 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.
    107. 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.
    108. 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.
    109. 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.
    110. 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.
    111. 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.
    112. 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).
    113. Boudt, Kris & Neely, Christopher J. & Sercu, Piet & Wauters, Marjan, 2019. "The response of multinationals’ foreign exchange rate exposure to macroeconomic news," Journal of International Money and Finance, Elsevier, vol. 94(C), pages 32-47.
    114. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    115. 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.
    116. Kam F. Chan & Philip Gray, 2018. "Volatility jumps and macroeconomic news announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(8), pages 881-897, August.
    117. Usman Arief & Zaäfri Ananto Husodo, 2021. "Private Information from Extreme Price Movements (Empirical Evidences from Southeast Asia Countries)," International Symposia in Economic Theory and Econometrics, in: Recent Developments in Asian Economics International Symposia in Economic Theory and Econometrics, volume 28, pages 221-242, Emerald Group Publishing Limited.
    118. Ayadi, Mohamed A. & Ben Omrane, Walid & Das, Deepan Kumar, 2024. "Macroeconomic news, senior officials' speeches, and emerging currency markets: An intraday analysis of price jump reaction," Emerging Markets Review, Elsevier, vol. 60(C).
    119. 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.
    120. 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.
    121. Linzert, Tobias & Winkelmann, Lars & Bibinger, Markus, 2014. "ECB monetary policy surprises: identification through cojumps in interest rates," Working Paper Series 1674, European Central Bank.
    122. Lian, Yu-Min & Chen, Jun-Home, 2024. "Pricing vulnerable options under cross-asset markov-modulated jump-diffusion dynamics," International Review of Economics & Finance, Elsevier, vol. 94(C).
    123. 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.
    124. Baruník Jozef & Fišer Pavel, 2024. "Co-Jumping of Treasury Yield Curve Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(3), pages 481-506.
    125. Lian, Yu-Min & Chen, Jun-Home, 2020. "Joint dynamic modeling and option pricing in incomplete derivative-security market," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    126. 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.
    127. 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).
    128. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam, 2019. "An empirical examination of the jump and diffusion aspects of asset pricing: Japanese evidence," Working Papers 2019-02, University of Tasmania, Tasmanian School of Business and Economics.
    129. 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.
    130. 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.
    131. 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.
    132. 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.
    133. Barbara Będowska-Sójka, 2010. "Intraday CAC40, DAX and WIG20 returns when the American macro news is announced," Bank i Kredyt, Narodowy Bank Polski, vol. 41(2), pages 7-20.
    134. Chendi Ni & Yuying Li & Peter A. Forsyth, 2023. "Neural Network Approach to Portfolio Optimization with Leverage Constraints:a Case Study on High Inflation Investment," Papers 2304.05297, arXiv.org, revised May 2023.
    135. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market instability and technical trading at high frequency: Evidence from NASDAQ stocks," Economic Modelling, Elsevier, vol. 102(C).
    136. 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).
    137. 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.
    138. 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.
    139. 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).
    140. Chae-Deug, Yi, 2024. "Realized normal volatility and maximum outlying jumps in high frequency returns for Korean won–US Dollar," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    141. 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.
    142. Gkillas, Konstantinos & Konstantatos, Christoforos & Floros, Christos & Tsagkanos, Athanasios, 2021. "Realized volatility spillovers between US spot and futures during ECB news: Evidence from the European sovereign debt crisis," International Review of Financial Analysis, Elsevier, vol. 74(C).
    143. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    144. Deniz Erdemlioglu & Christopher J. Neely & Xiye Yang, 2023. "Fed-Driven Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications," Working Papers 2023-016, Federal Reserve Bank of St. Louis, revised 27 May 2025.
    145. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," EconomiX Working Papers 2015-17, University of Paris Nanterre, EconomiX.
    146. Shi, Yujie & Wang, Liming & Ke, Jian, 2021. "Does the US-China trade war affect co-movements between US and Chinese stock markets?," Research in International Business and Finance, Elsevier, vol. 58(C).
    147. S. Rubun Dey & Christopher J. Neely, 2010. "A survey of announcement effects on foreign exchange returns," Review, Federal Reserve Bank of St. Louis, vol. 92(Sep), pages 417-464.
    148. 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.
    149. 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.
    150. Vladimir Balash & Alexey Faizliev & Sergei Sidorov & Elena Chistopolskaya, 2021. "Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets," Mathematics, MDPI, vol. 9(19), pages 1-31, October.
    151. Shah, Adil Ahmad & Paul, Manas & Bhanja, Niyati & Dar, Arif Billah, 2021. "Dynamics of connectedness across crude oil, precious metals and exchange rate: Evidence from time and frequency domains," Resources Policy, Elsevier, vol. 73(C).
    152. Mateus, Cesario & Chinthalapati, Raju & Mateus, Irina B., 2017. "Intraday industry-specific spillover effect in European equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 278-298.
    153. 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.
    154. Hutchison, Michael & Sushko, Vladyslav, 2013. "Impact of macro-economic surprises on carry trade activity," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1133-1147.
    155. 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.
    156. Naeyoung Kang & Jungmu Kim, 2019. "An Empirical Analysis of Bitcoin Price Jump Risk," Sustainability, MDPI, vol. 11(7), pages 1-11, April.
    157. Dumitru, Ana-Maria & Urga, Giovanni, 2016. "Jumps and Information Asymmetry in the US Treasury Market," EconStor Preprints 130148, ZBW - Leibniz Information Centre for Economics.
    158. 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).
    159. 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.
    160. Christopher J. Neely, 2011. "A survey of announcement effects on foreign exchange volatility and jumps," Review, Federal Reserve Bank of St. Louis, vol. 93(Sep), pages 361-385.
    161. 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).
    162. Tomasz Schabek & Bojana Olgiæ Draženoviæ & Davor Mance, 2019. "Reaction of Zagreb Stock Exchange CROBEX Index to macroeconomic announcements within a high frequency time interval," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(2), pages 741-758.
    163. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," Working Papers hal-04141409, HAL.
    164. 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.).
    165. Adam Clements & Yin Liao, 2013. "The dynamics of co-jumps, volatility and correlation," NCER Working Paper Series 91, National Centre for Econometric Research.
    166. 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.
    167. 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.
    168. 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.
    169. Winkelmann, Lars & Bibinger, Markus & Linzert, Tobias, 2013. "ECB monetary policy surprises: Identification through cojumps in interest rates," SFB 649 Discussion Papers 2013-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    170. 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.
    171. Mardi Dungey & Jet Holloway & Abdullah Yalaman & Wenying Yao, 2022. "Characterizing financial crises using high-frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 22(4), pages 743-760, April.
    172. 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.
    173. Walid Ben Omrane & Khaled Guesmi & Qi Qianru & Samir Saadi, 2023. "The high-frequency impact of macroeconomic news on jumps and co-jumps in the cryptocurrency markets," Annals of Operations Research, Springer, vol. 330(1), pages 177-209, November.
    174. Yeh, Jin-Huei & Yun, Mu-Shu, 2023. "Assessing jump and cojumps in financial asset returns with applications in futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    175. 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).

  21. BOUDT, Kris & CROUX, Christophe & LAURENT, Sébastien, 2011. "Outlyingness weighted covariation," LIDAM Reprints CORE 2443, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Manabu Asai & Michael McAleer, 2015. "The Impact of Jumps and Leverage in Forecasting Co-Volatility," Documentos de Trabajo del ICAE 2015-02, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Iulia LUPU & Gheorghe HURDUZEU & Mariana NICOLAE, 2016. "Connections Between Sentiment Indices And Reduced Volatilities Of Sustainability Stock Market Indices," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(1), pages 157-174.
    3. 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.
    4. 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.
    5. Robert G. Bowman & Kam Fong Chan & Christopher J. Neely, 2017. "Systematic Cojumps, Market Component Portfolios and Scheduled Macroeconomic Announcements," Working Papers 2017-11, Federal Reserve Bank of St. Louis.
    6. Kim Christensen & Silja Kinnebrock & Mark Podolskij, 2009. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," CREATES Research Papers 2009-45, Department of Economics and Business Economics, Aarhus University.
    7. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Jump-Robust Volatility Estimation using Nearest Neighbor Truncation," CREATES Research Papers 2009-52, Department of Economics and Business Economics, Aarhus University.
    8. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    9. 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.
    10. 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.
    11. Fiszeder, Piotr & Małecka, Marta & Molnár, Peter, 2024. "Robust estimation of the range-based GARCH model: Forecasting volatility, value at risk and expected shortfall of cryptocurrencies," Economic Modelling, Elsevier, vol. 141(C).
    12. 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.
    13. 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.
    14. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. 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).
    16. 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.
    17. 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).
    18. Erdemlioglu, Deniz & Laurent, Sébastien & Neely, Christopher J., 2015. "Which continuous-time model is most appropriate for exchange rates?," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 256-268.
    19. 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.
    20. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    21. 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.
    22. 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).
    23. 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.
    24. 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.
    25. Chae-Deug, Yi, 2024. "Realized normal volatility and maximum outlying jumps in high frequency returns for Korean won–US Dollar," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    26. Cecilia Mancini & Vanessa Mattiussi & Roberto Renò, 2015. "Spot volatility estimation using delta sequences," Finance and Stochastics, Springer, vol. 19(2), pages 261-293, April.
    27. 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.
    28. 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.
    29. 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).

  22. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. 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.
    2. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2011. "Semiparametric estimation with generated covariates," SFB 649 Discussion Papers 2011-064, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Kurose, Yuta & Omori, Yasuhiro, 2016. "Dynamic equicorrelation stochastic volatility," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 795-813.
    5. Chia-Lin Chang & Juan-à ngel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2011. "The Rise and Fall of S&P500 Variance Futures," KIER Working Papers 795, Kyoto University, Institute of Economic Research.
    6. Serge Darolles & Christian Francq & Sebastien Laurent, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-04590180, HAL.
    7. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Working Papers in Economics 11/26, University of Canterbury, Department of Economics and Finance.
    9. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Liu, Wei-han, 2016. "A re-examination of maturity effect of energy futures price from the perspective of stochastic volatility," Energy Economics, Elsevier, vol. 56(C), pages 351-362.
    11. Paulo Araújo Santos & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "GFC-Robust Risk Management Under the Basel Accord Using Extreme Value Methodologies," Working Papers in Economics 11/28, University of Canterbury, Department of Economics and Finance.
    12. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    13. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    14. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    17. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH models," Economics Series Working Papers 594, University of Oxford, Department of Economics.
    18. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Martin Burda & John M. Maheu, 2012. "Bayesian Adaptively Updated Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Paper series 46_12, Rimini Centre for Economic Analysis.
    21. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    23. Yaya, OlaOluwa S. & Tumala, Mohammed M. & Udomboso, Christopher G., 2016. "Volatility persistence and returns spillovers between oil and gold prices: Analysis before and after the global financial crisis," Resources Policy, Elsevier, vol. 49(C), pages 273-281.
    24. 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.
    25. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    26. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  23. Hecq, A.W. & Palm, F.C. & Laurent, S.F.J.A., 2011. "Common intraday periodicity," Research Memorandum 010, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).

    Cited by:

    1. 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.
    2. Tomás del Barrio Castro & Alain Hecq, 2016. "Testing for Deterministic Seasonality in Mixed-Frequency VARs," DEA Working Papers 76, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    3. Hans DEWACHTER & Deniz ERDEMLIOGLU & Jean-Yves GNABO & Christelle LECOURT, 2013. "The intra-day impact of communication on euro-dollar volatility and jumps," Working Papers of Department of Economics, Leuven ces13.04, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    4. 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.
    5. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
    6. Erdemlioglu, Deniz & Laurent, Sébastien & Neely, Christopher J., 2015. "Which continuous-time model is most appropriate for exchange rates?," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 256-268.
    7. 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.
    8. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    9. Herrmann, Klaus & Teis, Stefan & Yu, Weijun, 2014. "Components of intraday volatility and their prediction at different sampling frequencies with application to DAX and BUND futures," FAU Discussion Papers in Economics 15/2014, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.

  24. 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).

    Cited by:

    1. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    2. Hautsch, Nikolaus & Kyj, Lada. M. & Malec, Peter, 2013. "Do high-frequency data improve high-dimensional portfolio allocations?," SFB 649 Discussion Papers 2013-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. 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.
    4. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    5. Han, Chulwoo & Park, Frank C., 2022. "A geometric framework for covariance dynamics," Journal of Banking & Finance, Elsevier, vol. 134(C).
    6. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    7. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Hartl, Tobias & Weigand, Roland, 2019. "Multivariate Fractional Components Analysis," University of Regensburg Working Papers in Business, Economics and Management Information Systems 38283, University of Regensburg, Department of Economics.
    9. Szymon Lis & Marcin Chlebus, 2021. "Comparison of the accuracy in VaR forecasting for commodities using different methods of combining forecasts," Working Papers 2021-11, Faculty of Economic Sciences, University of Warsaw.
    10. Rasmus Søndergaard Pedersen & Anders Rahbek, 2012. "Multivariate Variance Targeting in the BEKK-GARCH Model," Discussion Papers 12-23, University of Copenhagen. Department of Economics.
    11. Karl Oton Rudolf & Samer Ajour El Zein & Nicola Jackman Lansdowne, 2021. "Bitcoin as an Investment and Hedge Alternative. A DCC MGARCH Model Analysis," Risks, MDPI, vol. 9(9), pages 1-22, August.
    12. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    13. Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
    14. Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
    15. 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.
    16. 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).
    17. Triki, Mohamed Bilel & Ben Maatoug, Abderrazek, 2021. "The GOLD market as a safe haven against the stock market uncertainty: Evidence from geopolitical risk," Resources Policy, Elsevier, vol. 70(C).
    18. Radovan Parrák, 2013. "The Economic Valuation of Variance Forecasts: An Artificial Option Market Approach," Working Papers IES 2013/09, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2013.
    19. Serge Darolles & Christian Francq & Sebastien Laurent, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-04590180, HAL.
    20. 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.
    21. Aslanidis, Nektarios & Casas, Isabel, 2011. "Modelling asset correlations: A nonparametric approach," Working Papers 2011-01, University of Sydney, School of Economics.
    22. Mei, Dexiang & Zeng, Qing & Cao, Xiang & Diao, Xiaohua, 2019. "Uncertainty and oil volatility: New evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 155-163.
    23. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    24. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    25. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Discussion Papers CORE 2016001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    26. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    27. 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.
    28. Liu, Zhenhua & Wang, Yushu & Yuan, Xinting & Ding, Zhihua & Ji, Qiang, 2025. "Geopolitical risk and vulnerability of energy markets," Energy Economics, Elsevier, vol. 141(C).
    29. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    30. Gian Piero Aielli & Massimiliano Caporin, 2011. "Variance Clustering Improved Dynamic Conditional Correlation MGARCH Estimators," "Marco Fanno" Working Papers 0133, Dipartimento di Scienze Economiche "Marco Fanno".
    31. Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022. "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, vol. 62(5), pages 2239-2262, May.
    32. Wang, Yizhi & Lucey, Brian M. & Vigne, Samuel A. & Yarovaya, Larisa, 2022. "The Effects of Central Bank Digital Currencies News on Financial Markets," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    33. Rasmus Søndergaard Pedersen, 2014. "Targeting estimation of CCC-Garch models with infinite fourth moments," Discussion Papers 14-04, University of Copenhagen. Department of Economics.
    34. Md Zulquar Nain & Sajad Ahmad Bhat & Javed Ahmad Bhat, 2023. "ESG investments, bear periods and adaptive resilience: evidence from India using a DBEKK‑MGARCH," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 25(1), pages 5-21, December.
    35. Jacobs, Michael & Karagozoglu, Ahmet K., 2014. "On the characteristics of dynamic correlations between asset pairs," Research in International Business and Finance, Elsevier, vol. 32(C), pages 60-82.
    36. Lv, Wendai, 2018. "Does the OVX matter for volatility forecasting? Evidence from the crude oil market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 916-922.
    37. 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.
    38. Stavroula P. Fameliti & Vasiliki D. Skintzi, 2020. "Predictive ability and economic gains from volatility forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 200-219, March.
    39. Mohammad Alomari & David. M. Power & Nongnuch Tantisantiwong, 2018. "Determinants of equity return correlations: a case study of the Amman Stock Exchange," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 33-66, January.
    40. Tran, Thuy Nhung, 2022. "The Volatility of the Stock Market and Financial Cycle: GARCH Family Models," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 56(1), pages 151-168.
    41. 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.
    42. 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.
    43. Tobias Fissler & Yannick Hoga, 2024. "How to Compare Copula Forecasts?," Papers 2410.04165, arXiv.org.
    44. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    45. Manabu Asai & Michael McAleer, 2022. "Bayesian Analysis of Realized Matrix-Exponential GARCH Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 103-123, January.
    46. Jeroen Rombouts & Lars Stentoft & Francesco Violente, 2012. "The Value of Multivariate Model Sophistication: An Application to pricing Dow Jones Industrial Average Options," CIRANO Working Papers 2012s-05, CIRANO.
    47. Lu, Xinjie & Ma, Feng & Li, Haibo & Wang, Jianqiong, 2023. "INE oil futures volatility prediction: Exchange rates or international oil futures volatility?," Energy Economics, Elsevier, vol. 126(C).
    48. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    49. Noori, Mohammad & Hitaj, Asmerilda, 2023. "Dissecting hedge funds' strategies," International Review of Financial Analysis, Elsevier, vol. 85(C).
    50. Fu, Yang & Zheng, Zeyu, 2020. "Volatility modeling and the asymmetric effect for China’s carbon trading pilot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    51. 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.
    52. 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.
    53. Adam E Clements & Mark Doolan & Stan Hurn & Ralf Becker, 2012. "Selecting forecasting models for portfolio allocation," NCER Working Paper Series 85, National Centre for Econometric Research.
    54. Fresoli, Diego E. & Ruiz, Esther, 2016. "The uncertainty of conditional returns, volatilities and correlations in DCC models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 170-185.
    55. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2019. "Volatility-dependent correlations: further evidence of when, where and how," Empirical Economics, Springer, vol. 57(2), pages 505-540, August.
    56. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling and Estimation," Papers 2206.14275, arXiv.org, revised Jan 2025.
    57. 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.
    58. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2025. "The Role of Uncertainty in Forecasting Realized Covariance of US State-Level Stock Returns: A Reverse-MIDAS Approach," Working Papers 202501, University of Pretoria, Department of Economics.
    59. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    60. Ralf Becker & Adam Clements & Robert O'Neill, 2018. "A Multivariate Kernel Approach to Forecasting the Variance Covariance of Stock Market Returns," Econometrics, MDPI, vol. 6(1), pages 1-27, February.
    61. Adam E Clements & Ayesha Scott & Annastiina Silvennoinen, 2012. "Forecasting multivariate volatility in larger dimensions: some practical issues," NCER Working Paper Series 80, National Centre for Econometric Research.
    62. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael & Pauwels, Laurent, 2019. "Asymptotic Theory for Rotated Multivariate GARCH Models," Working Papers BAWP-2019-03, University of Sydney Business School, Discipline of Business Analytics.
    63. 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.
    64. Ralf Becker & Adam Clements & Robert O'Neill, 2010. "A Kernel Technique for Forecasting the Variance-Covariance Matrix," NCER Working Paper Series 66, National Centre for Econometric Research.
    65. Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2018. "Networks in risk spillovers: A multivariate GARCH perspective," SAFE Working Paper Series 225, Leibniz Institute for Financial Research SAFE.
    66. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    67. Köchling, Gerrit & Schmidtke, Philipp & Posch, Peter N., 2020. "Volatility forecasting accuracy for Bitcoin," Economics Letters, Elsevier, vol. 191(C).
    68. Lakshina, Valeriya, 2014. "Is it possible to break the «curse of dimensionality»? Spatial specifications of multivariate volatility models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 36(4), pages 61-78.
    69. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "COVID-19 and stock returns: Evidence from the Markov switching dependence approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    70. Khalfaoui, R & Boutahar, M, 2012. "Portfolio risk evaluation: An approach based on dynamic conditional correlations models and wavelet multiresolution analysis," MPRA Paper 41624, University Library of Munich, Germany.
    71. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2014. "On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 26-40.
    72. Roland Weigand, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," Working Papers 144, Bavarian Graduate Program in Economics (BGPE).
    73. Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
    74. Helmut Lütkepohl & Thore Schlaak, 2018. "Choosing Between Different Time‐Varying Volatility Models for Structural Vector Autoregressive Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(4), pages 715-735, August.
    75. 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.
    76. 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.
    77. 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).
    78. Manabu Asai & Chia-Lin Chang & Michael McAleer & Laurent Pauwels, 2021. "Asymptotic and Finite Sample Properties for Multivariate Rotated GARCH Models," Econometrics, MDPI, vol. 9(2), pages 1-21, May.
    79. 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.
    80. 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.
    81. Sylvain Barde, 2015. "A fast algorithm for finding the confidence set of large collections of models," Studies in Economics 1519, School of Economics, University of Kent.
    82. Christian Francq & Lajos Horváth & Jean-Michel Zakoïan, 2016. "Variance Targeting Estimation of Multivariate GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 353-382.
    83. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    84. 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.
    85. 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.
    86. Ahmed, Shamim & Bu, Ziwen & Symeonidis, Lazaros & Tsvetanov, Daniel, 2023. "Which factor model? A systematic return covariation perspective," Journal of International Money and Finance, Elsevier, vol. 136(C).
    87. Feng Ma & M. I. M. Wahab & Julien Chevallier & Ziyang Li, 2023. "A tug of war of forecasting the US stock market volatility: Oil futures overnight versus intraday information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 60-75, January.
    88. 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.
    89. Zhang, Lixia & Bai, Jiancheng & Zhang, Yueyan & Cui, Can, 2023. "Global economic uncertainty and the Chinese stock market: Assessing the impacts of global indicators," Research in International Business and Finance, Elsevier, vol. 65(C).
    90. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2013. "On the Benefits of Equicorrelation for Portfolio Allocation," NCER Working Paper Series 99, National Centre for Econometric Research.
    91. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    92. Becker, R. & Clements, A.E. & Doolan, M.B. & Hurn, A.S., 2015. "Selecting volatility forecasting models for portfolio allocation purposes," International Journal of Forecasting, Elsevier, vol. 31(3), pages 849-861.
    93. Zhu, Jiaji & Han, Wei & Zhang, Junchao, 2023. "Does climate risk matter for gold price volatility?," Finance Research Letters, Elsevier, vol. 58(PC).
    94. Kim, Myeong Hyeon & Sun, Lingxia, 2017. "Dynamic conditional correlations between Chinese sector returns and the S&P 500 index: An interpretation based on investment shocks," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 309-325.
    95. Liu, Yue & Sun, Huaping & Zhang, Jijian & Taghizadeh-Hesary, Farhad, 2020. "Detection of volatility regime-switching for crude oil price modeling and forecasting," Resources Policy, Elsevier, vol. 69(C).
    96. Carroll, Rachael & Conlon, Thomas & Cotter, John & Salvador, Enrique, 2017. "Asset allocation with correlation: A composite trade-off," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1164-1180.
    97. Roberto Savona & Cesare Orsini, 2019. "Taking the right course navigating the ERC universe," Journal of Asset Management, Palgrave Macmillan, vol. 20(3), pages 157-174, May.
    98. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2016. "Volatility Dependent Dynamic Equicorrelation," NCER Working Paper Series 111, National Centre for Econometric Research.
    99. Christian Francq & Jean-Michel Zakoïan, 2016. "Estimating multivariate volatility models equation by equation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 613-635, June.
    100. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
    101. 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.
    102. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    103. Jiqian Wang & Feng Ma & Chao Liang & Zhonglu Chen, 2022. "Volatility forecasting revisited using Markov‐switching with time‐varying probability transition," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1387-1400, January.
    104. Tan, Jinghua & Li, Zhixi & Zhang, Chuanhui & Shi, Long & Jiang, Yuansheng, 2024. "A multiscale time-series decomposition learning for crude oil price forecasting," Energy Economics, Elsevier, vol. 136(C).
    105. Jentsch, Carsten & Subba Rao, Suhasini, 2015. "A test for second order stationarity of a multivariate time series," Journal of Econometrics, Elsevier, vol. 185(1), pages 124-161.
    106. Yannick Hoga, 2023. "The Estimation Risk in Extreme Systemic Risk Forecasts," Papers 2304.10349, arXiv.org.
    107. Dimitrios P. Louzis, 2015. "The economic value of flexible dynamic correlation models," Economics Bulletin, AccessEcon, vol. 35(1), pages 774-782.
    108. 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, January-A.
    109. 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.
    110. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    111. 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.
    112. Yudong Wang & Chongfeng Wu & Li Yang, 2015. "Hedging with Futures: Does Anything Beat the Naïve Hedging Strategy?," Management Science, INFORMS, vol. 61(12), pages 2870-2889, December.
    113. Al Mamun, Md & Uddin, Gazi Salah & Suleman, Muhammad Tahir & Kang, Sang Hoon, 2020. "Geopolitical risk, uncertainty and Bitcoin investment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    114. G. C. Livingston & Darfiana Nur, 2023. "Bayesian inference of multivariate-GARCH-BEKK models," Statistical Papers, Springer, vol. 64(5), pages 1749-1774, October.
    115. Dimitris P. Louzis, 2014. "Macroeconomic and credit forecasts in a small economy during crisis: A large Bayesian VAR approach," Working Papers 184, Bank of Greece.
    116. Yuqing Feng & Yaojie Zhang & Yudong Wang, 2024. "Out‐of‐sample volatility prediction: Rolling window, expanding window, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 567-582, April.
    117. 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.
    118. Dark, Jonathan, 2018. "Multivariate models with long memory dependence in conditional correlation and volatility," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 162-180.
    119. Cristiana Tudor & Robert Sova, 2025. "An automated adaptive trading system for enhanced performance of emerging market portfolios," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-39, December.

  25. GIOT, Pierre & LAURENT, Sébastien & PETITJEAN, Mikael, 2010. "Trading activity, realized volatility and jumps," LIDAM Reprints CORE 2223, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. 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.
    2. Fredj Jawadi & Wael Louhichi & Hachmi Ben Ameur & Abdoulkarim Idi Cheffou, 2017. "On Oil-US Exchange Rate Volatility Relationships: an Intradaily Analysis," Working Papers hal-04141662, HAL.
    3. Rangan Gupta & Patrick Kanda & Mark E. Wohar, 2021. "Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 324-335, March.
    4. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    5. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2023. "Forecasting the Realized Volatility of Agricultural Commodity Prices: Does Sentiment Matter?," Working Papers 202316, University of Pretoria, Department of Economics.
    6. Senarathne, Chamil W & Jayasinghe, Prabhath, 2017. "Information Flow Interpretation of Heteroskedasticity for Capital Asset Pricing: An Expectation-based View of Risk," MPRA Paper 78771, University Library of Munich, Germany, revised 04 Apr 2017.
    7. 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.
    8. Ding, Shusheng & Cui, Tianxiang & Zhang, Yongmin, 2022. "Futures volatility forecasting based on big data analytics with incorporating an order imbalance effect," International Review of Financial Analysis, Elsevier, vol. 83(C).
    9. Daniel Cahill & Kingsley Fong & Marvin Wee & Joey Wenling Yang, 2020. "The role of implied volatility in liquidity provision," Australian Journal of Management, Australian School of Business, vol. 45(1), pages 45-71, February.
    10. Go, You-How & Lau, Wee-Yeap, 2020. "The impact of global financial crisis on informational efficiency: Evidence from price-volume relation in crude palm oil futures market," Journal of Commodity Markets, Elsevier, vol. 17(C).
    11. Ezzat, Hassan & Kirkulak, Berna, 2014. "Information Arrival and Volatility: Evidence from the Saudi Arabia Stock Exchange (Tadawul)," MPRA Paper 61160, University Library of Munich, Germany.
    12. 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.
    13. Riza Demirer & Rangan Gupta & Asli Yuksel & Aydin Yuksel, 2020. "The U.S. Term Structure and Return Volatility in Global REIT Markets," Working Papers 202069, University of Pretoria, Department of Economics.
    14. Evans, Kevin P., 2011. "Intraday jumps and US macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2511-2527, October.
    15. 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.
    16. 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).
    17. Byun, Suk Joon & Kim, Jun Sik, 2013. "The information content of risk-neutral skewness for volatility forecasting," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 142-161.
    18. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Business applications and state‐level stock market realized volatility: A forecasting experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 456-472, March.
    19. Julien Chevallier & Benoît Sévi, 2011. "On the volatility-volume relationship in energy futures markets using intraday data," Working Papers hal-04140997, HAL.
    20. Konstantinos Gkillas & Rangan Gupta & Mark E. Wohar, 2018. "Oil Shocks and Volatility Jumps," Working Papers 201825, University of Pretoria, Department of Economics.
    21. 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).
    22. 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.
    23. 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).
    24. 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.
    25. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2016. "Volatility Jumps and Their Economic Determinants," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 29-80.
    26. 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.
    27. Ma, Chaoqun & Mi, Xianhua & Cai, Zongwu, 2020. "Nonlinear and time-varying risk premia," China Economic Review, Elsevier, vol. 62(C).
    28. Jan Hanousek & Ev??en Ko??enda & Jan Novotn??, 2013. "Price Jumps on European Stock Markets," William Davidson Institute Working Papers Series wp1059, William Davidson Institute at the University of Michigan.
    29. Alekseev, Oleg & Janda, Karel & Petit, Mathieu & Zilberman, David, 2024. "Return and volatility spillovers between the raw material and electric vehicles markets," Energy Economics, Elsevier, vol. 137(C).
    30. Richard Mawulawoea Ahadzie & Dan Daugaard & Moses Kangogo & Faisal Khan & Joaquin Vespignani, 2023. "COVID-19, Mobility Restriction Policies and Stock Market Volatility: A Cross-Country Empirical Study," CAMA Working Papers 2023-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    31. 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.
    32. 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.
    33. Liu, Li & Pan, Zhiyuan, 2020. "Forecasting stock market volatility: The role of technical variables," Economic Modelling, Elsevier, vol. 84(C), pages 55-65.
    34. Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Energies, MDPI, vol. 14(14), pages 1-15, July.
    35. 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.
    36. 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.
    37. 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.
    38. Luo, Dan & Mao, Yipeng, 2021. "Fundamental volatility and informative trading volume in a rational expectations equilibrium," Economic Modelling, Elsevier, vol. 105(C).
    39. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian & Yoon, Seong-Min, 2021. "OPEC news and jumps in the oil market," Energy Economics, Elsevier, vol. 96(C).
    40. 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.
    41. 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.
    42. Hervé, Fabrice & Zouaoui, Mohamed & Belvaux, Bertrand, 2019. "Noise traders and smart money: Evidence from online searches," Economic Modelling, Elsevier, vol. 83(C), pages 141-149.
    43. Boudt, Kris & Petitjean, Mikael, 2014. "Intraday liquidity dynamics and news releases around price jumps: Evidence from the DJIA stocks," LIDAM Reprints LFIN 2014006, Université catholique de Louvain, Louvain Finance (LFIN).
    44. Shin, Dong Wan & Hwang, Eunju, 2015. "A Lagrangian multiplier test for market microstructure noise with applications to sampling interval determination for realized volatilities," Economics Letters, Elsevier, vol. 129(C), pages 95-99.
    45. 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.
    46. Mehmet Balcilar & Elie Bouri & Rangan Gupta & Christian Pierdzioch, 2021. "El Nino, La Nina, and the Forecastability of the Realized Variance of Heating Oil Price Movements," Working Papers 202138, University of Pretoria, Department of Economics.
    47. Zied Ftiti & Fredj Jawadi & Waël Louhichi, 2017. "Modelling the relationship between future energy intraday volatility and trading volume with wavelet," Applied Economics, Taylor & Francis Journals, vol. 49(20), pages 1981-1993, April.
    48. Chevallier, Julien & Sévi, Benoît, 2012. "On the volatility–volume relationship in energy futures markets using intraday data," Energy Economics, Elsevier, vol. 34(6), pages 1896-1909.
    49. Zied Ftiti & Wael Louhichi & Hachmi Ben Ameur, 2023. "Cryptocurrency volatility forecasting: What can we learn from the first wave of the COVID-19 outbreak?," Annals of Operations Research, Springer, vol. 330(1), pages 665-690, November.
    50. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Climate Risks and State-Level Stock-Market Realized Volatility," Working Papers 202246, University of Pretoria, Department of Economics.
    51. 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.
    52. Zhao, X. & Hong, S. Y. & Linton, O. B., 2024. "Jumps Versus Bursts: Dissection and Origins via a New Endogenous Thresholding Approach," Cambridge Working Papers in Economics 2449, Faculty of Economics, University of Cambridge.
    53. Carlo Rosa, 2013. "The financial market effect of FOMC minutes," Economic Policy Review, Federal Reserve Bank of New York, issue Dec, pages 67-81.
    54. Liu, Xinghua & Liu, Xin & Liang, Xiaobei, 2015. "Information-driven trade and price–volume relationship in artificial stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 73-80.
    55. 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.
    56. Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2020. "Forecasting Realized Stock-Market Volatility: Do Industry Returns have Predictive Value?," Working Papers 2020107, University of Pretoria, Department of Economics.
    57. 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.
    58. 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).
    59. 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.
    60. 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.
    61. Koubaa, Yosra & Slim, Skander, 2019. "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, vol. 82(C), pages 168-184.
    62. Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2023. "Drivers of Realized Volatility for Emerging Countries with a Focus on South Africa: Fundamentals versus Sentiment," Mathematics, MDPI, vol. 11(6), pages 1-26, March.
    63. 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.
    64. 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.
    65. 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.
    66. 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.
    67. Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2021. "Investor Confidence and Forecastability of US Stock Market Realized Volatility : Evidence from Machine Learning," Working Papers 202118, University of Pretoria, Department of Economics.
    68. 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.
    69. Shu-Fang Yuan, 2024. "Realized higher moments and trading activity," Review of Quantitative Finance and Accounting, Springer, vol. 62(3), pages 971-1005, April.
    70. 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.
    71. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market instability and technical trading at high frequency: Evidence from NASDAQ stocks," Economic Modelling, Elsevier, vol. 102(C).
    72. Hooy, Chee-Wooi & Lee, Meng-Horng & Chong, Terence Tai Leung, 2017. "The Sources of Country and Industry Variations in ASEAN Stock Returns," MPRA Paper 80574, University Library of Munich, Germany.
    73. Thomas Dimpfl & Stefania Odelli, 2020. "Bitcoin Price Risk—A Durations Perspective," JRFM, MDPI, vol. 13(7), pages 1-18, July.
    74. Gkillas, Konstantinos & Gupta, Rangan & Wohar, Mark E., 2018. "Volatility jumps: The role of geopolitical risks," Finance Research Letters, Elsevier, vol. 27(C), pages 247-258.
    75. Çepni, Oğuzhan & Gupta, Rangan & Pienaar, Daniel & Pierdzioch, Christian, 2022. "Forecasting the realized variance of oil-price returns using machine learning: Is there a role for U.S. state-level uncertainty?," Energy Economics, Elsevier, vol. 114(C).
    76. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "How does trading volume affect financial return distributions?," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 190-206.
    77. Maki, Daiki, 2024. "Asymmetric effect of trading volume on realized volatility," International Review of Economics & Finance, Elsevier, vol. 94(C).
    78. Sensoy, Ahmet & Serdengeçti, Süleyman, 2019. "Intraday volume-volatility nexus in the FX markets: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 1-12.
    79. 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.
    80. 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.
    81. Xiao, Xijuan & Yamamoto, Ryuichi, 2024. "Realized volatility, price informativeness, and tick size: A market microstructure approach," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 410-426.
    82. 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).
    83. Zhenwei Li & Jing Han & Yuping Song, 2020. "On the forecasting of high‐frequency financial time series based on ARIMA model improved by deep learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1081-1097, November.
    84. Riza Demirer & Asli Yuksel & Aydin Yuksel, 2020. "The U.S. term structure and return volatility in emerging stock markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(4), pages 687-707, October.
    85. Beata Szetela & Grzegorz Mentel & Yuriy Bilan & Urszula Mentel, 2021. "The relationship between trend and volume on the bitcoin market," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(1), pages 25-42, March.
    86. Kerr Hatrick & Mike So & S. Chung & R. Deng, 2011. "Dynamic Relationship among Intraday Realized Volatility, Volume and Number of Trades," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 18(3), pages 291-317, September.
    87. Kearney, Fearghal & Murphy, Finbarr & Cummins, Mark, 2015. "An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 199-216.
    88. 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.
    89. Wang, Zhenxin & Wang, Shaoping & Yan, Yayi & Xia, Yingcun, 2025. "Examining Chinese volume–volatility nexus: A regime-switching perspective," Economic Modelling, Elsevier, vol. 144(C).
    90. Maki, Daiki, 2024. "Forecasting downside and upside realized volatility: The role of asymmetric information," The Journal of Economic Asymmetries, Elsevier, vol. 29(C).
    91. Jawadi Fredj & Ureche-Rangau Loredana, 2013. "Threshold linkages between volatility and trading volume: evidence from developed and emerging markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 313-333, May.
    92. Louhichi, Waël, 2011. "What drives the volume-volatility relationship on Euronext Paris?," International Review of Financial Analysis, Elsevier, vol. 20(4), pages 200-206, August.
    93. Chen, Chin-Ho, 2019. "Downside jump risk and the levels of futures-cash basis," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    94. 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.
    95. 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).

  26. LAURENT, Sebastien & ROMBOUTS, Jeroen V.K. & VIOLANTE, FRANCESCO, 2009. "Consistent ranking of multivariate volatility models," LIDAM Discussion Papers CORE 2009002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    5. 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.
    6. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    7. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    8. Kevin Sheppard & Wen Xu, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    9. Manner, Hans & Reznikova, Olga, 2010. "Forecasting international stock market correlations: does anything beat a CCC?," Discussion Papers in Econometrics and Statistics 7/10, University of Cologne, Institute of Econometrics and Statistics.

  27. Sébastien Laurent & Jeroen Rombouts & Francesco Violente, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," CIRANO Working Papers 2009s-45, CIRANO.

    Cited by:

    1. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    2. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2010. "On the Forecasting Accuracy of Multivariate GARCH Models," Cahiers de recherche 1021, CIRPEE.
    3. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. 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.
    5. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," DEM Working Papers Series 145, University of Pavia, Department of Economics and Management.
    6. Hartl, Tobias & Weigand, Roland, 2019. "Multivariate Fractional Components Analysis," University of Regensburg Working Papers in Business, Economics and Management Information Systems 38283, University of Regensburg, Department of Economics.
    7. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    8. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    9. Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
    10. 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).
    11. Radovan Parrák, 2013. "The Economic Valuation of Variance Forecasts: An Artificial Option Market Approach," Working Papers IES 2013/09, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2013.
    12. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    13. 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.
    14. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Discussion Papers CORE 2016001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Ralf Becker & Adam Clements & Robert O'Neill, 2010. "A Cholesky-MIDAS model for predicting stock portfolio volatility," NCER Working Paper Series 60, National Centre for Econometric Research.
    16. Sui, Bo & Chang, Chun-Ping & Jang, Chyi-Lu & Gong, Qiang, 2021. "Analyzing causality between epidemics and oil prices: Role of the stock market," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 148-158.
    17. Pawel Janus & Siem Jan Koopman & André Lucas, 2011. "Long Memory Dynamics for Multivariate Dependence under Heavy Tails," Tinbergen Institute Discussion Papers 11-175/2/DSF28, Tinbergen Institute.
    18. Alessandra Amendola & Vincenzo Candila & Antonio Naimoli & Giuseppe Storti, 2024. "Adaptive combinations of tail-risk forecasts," Papers 2406.06235, arXiv.org.
    19. Bauwens, Luc & Xu, Yongdeng, 2023. "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
    20. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    21. Jérémy Leymarie & Christophe Hurlin & Antoine Patin, 2018. "Loss Functions for LGD Models Comparison," Post-Print hal-01923050, HAL.
    22. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    23. Gian Piero Aielli & Massimiliano Caporin, 2011. "Variance Clustering Improved Dynamic Conditional Correlation MGARCH Estimators," "Marco Fanno" Working Papers 0133, Dipartimento di Scienze Economiche "Marco Fanno".
    24. BAUWENS Luc, & XU Yongdeng,, 2019. "DCC-HEAVY: A multivariate GARCH model based on realized variances and correlations," LIDAM Discussion Papers CORE 2019025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. 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).
    26. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
    27. Jacobs, Michael & Karagozoglu, Ahmet K., 2014. "On the characteristics of dynamic correlations between asset pairs," Research in International Business and Finance, Elsevier, vol. 32(C), pages 60-82.
    28. Yan, Han & Liu, Bin & Zhu, Xingting & Wu, Yan, 2024. "Systemic risk monitoring model from the perspective of public information arrival," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    29. 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.
    30. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    31. Tobias Fissler & Yannick Hoga, 2024. "How to Compare Copula Forecasts?," Papers 2410.04165, arXiv.org.
    32. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    33. 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.
    34. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Attention to oil prices and its impact on the oil, gold and stock markets and their covariance," Energy Economics, Elsevier, vol. 120(C).
    35. Caporin, M. & McAleer, M.J., 2010. "Ranking multivariate GARCH models by problem dimension," Econometric Institute Research Papers EI 2010-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    36. Jeroen Rombouts & Lars Stentoft & Francesco Violente, 2012. "The Value of Multivariate Model Sophistication: An Application to pricing Dow Jones Industrial Average Options," CIRANO Working Papers 2012s-05, CIRANO.
    37. 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).
    38. Kawakatsu Hiroyuki, 2021. "Simple Multivariate Conditional Covariance Dynamics Using Hyperbolically Weighted Moving Averages," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 33-52, January.
    39. Yu‐Sheng Lai, 2022. "Use of high‐frequency data to evaluate the performance of dynamic hedging strategies," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 104-124, January.
    40. Adam E Clements & Mark Doolan & Stan Hurn & Ralf Becker, 2012. "Selecting forecasting models for portfolio allocation," NCER Working Paper Series 85, National Centre for Econometric Research.
    41. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    42. Andrea Bucci & Michele Palma & Chao Zhang, 2024. "Geometric Deep Learning for Realized Covariance Matrix Forecasting," Papers 2412.09517, arXiv.org.
    43. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    44. 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.
    45. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    46. Ralf Becker & Adam Clements & Robert O'Neill, 2018. "A Multivariate Kernel Approach to Forecasting the Variance Covariance of Stock Market Returns," Econometrics, MDPI, vol. 6(1), pages 1-27, February.
    47. E. Ngounda & K. C. Patidar & E. Pindza, 2014. "A Robust Spectral Method for Solving Heston’s Model," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 164-178, April.
    48. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Series Working Papers 533, University of Oxford, Department of Economics.
    49. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2012. "The conditional autoregressive Wishart model for multivariate stock market volatility," Journal of Econometrics, Elsevier, vol. 167(1), pages 211-223.
    50. Brownlees, Christian & Llorens-Terrazas, Jordi, 2024. "Empirical risk minimization for time series: Nonparametric performance bounds for prediction," Journal of Econometrics, Elsevier, vol. 244(1).
    51. Ralf Becker & Adam Clements & Robert O'Neill, 2010. "A Kernel Technique for Forecasting the Variance-Covariance Matrix," NCER Working Paper Series 66, National Centre for Econometric Research.
    52. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    53. Carlo Drago & Andrea Scozzari, 2022. "Evaluating conditional covariance estimates via a new targeting approach and a networks-based analysis," Papers 2202.02197, arXiv.org.
    54. Jianqing Fan & Donggyu Kim & Minseok Shin & Yazhen Wang, 2024. "Factor and Idiosyncratic VAR-Ito Volatility Models for Heavy-Tailed High-Frequency Financial Data," Working Papers 202415, University of California at Riverside, Department of Economics.
    55. Bauwens, Luc & Dzuverovic, Emilija & Hafner, Christian, 2024. "Asymmetric Models for Realized Covariances," LIDAM Discussion Papers ISBA 2024022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    56. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    57. Massimiliano Caporin & Michael McAleer, 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," KIER Working Papers 724, Kyoto University, Institute of Economic Research.
    58. Elena Ivona Dumitrescu & Georgiana-Denisa Banulescu, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," Post-Print hal-03331122, HAL.
    59. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2014. "On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 26-40.
    60. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    61. Roland Weigand, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," Working Papers 144, Bavarian Graduate Program in Economics (BGPE).
    62. Denisa Georgiana Banulescu & Ferrara Laurent & Marsilli Clément, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," Working Papers hal-03563168, HAL.
    63. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
    64. Gneiting, Tilmann, 2011. "Making and Evaluating Point Forecasts," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 746-762.
    65. Gong, Xu & Lin, Boqiang, 2018. "Structural changes and out-of-sample prediction of realized range-based variance in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 27-39.
    66. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    67. Wenjing Wang & Minjing Tao, 2020. "Forecasting Realized Volatility Matrix With Copula-Based Models," Papers 2002.08849, arXiv.org.
    68. 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.
    69. Mohammad Ahsan Uddin & ASM Maksud Kamal & Shamsuddin Shahid & Eun-Sung Chung, 2020. "Volatility in Rainfall and Predictability of Droughts in Northwest Bangladesh," Sustainability, MDPI, vol. 12(23), pages 1-20, November.
    70. 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.
    71. 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.
    72. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Reprints CORE 2923, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    73. Xu Gong & Boqiang Lin, 2021. "Effects of structural changes on the prediction of downside volatility in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1124-1153, July.
    74. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
    75. 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.
    76. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    77. 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.
    78. 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.
    79. Laura Capera Romero & Anne Opschoor, 2024. "Realized Variances vs. Correlations: Unlocking the Gains in Multivariate Volatility Forecasting," Tinbergen Institute Discussion Papers 24-059/III, Tinbergen Institute.
    80. 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.
    81. 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.
    82. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    83. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    84. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    85. Becker, R. & Clements, A.E. & Doolan, M.B. & Hurn, A.S., 2015. "Selecting volatility forecasting models for portfolio allocation purposes," International Journal of Forecasting, Elsevier, vol. 31(3), pages 849-861.
    86. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    87. Chini, Emilio Zanetti, 2023. "Can we estimate macroforecasters’ mis-behavior?," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    88. Carroll, Rachael & Conlon, Thomas & Cotter, John & Salvador, Enrique, 2017. "Asset allocation with correlation: A composite trade-off," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1164-1180.
    89. Xu, Yongdeng, 2024. "Extended multivariate EGARCH model: A model for zero†return and negative spillovers," Cardiff Economics Working Papers E2024/24, Cardiff University, Cardiff Business School, Economics Section.
    90. Wang, Weichen & An, Ran & Zhu, Ziwei, 2024. "Volatility prediction comparison via robust volatility proxies: An empirical deviation perspective," Journal of Econometrics, Elsevier, vol. 239(2).
    91. 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.
    92. Jingwei Pan, 0000. "Evaluating Correlation Forecasts Under Asymmetric Loss," Proceedings of Economics and Finance Conferences 11413234, International Institute of Social and Economic Sciences.
    93. 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.
    94. Emilija Dzuverovic & Matteo Barigozzi, 2023. "Hierarchical DCC-HEAVY Model for High-Dimensional Covariance Matrices," Papers 2305.08488, arXiv.org, revised Jul 2024.
    95. Llorens-Terrazas, Jordi & Brownlees, Christian, 2023. "Projected Dynamic Conditional Correlations," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1761-1776.

  28. 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," LIDAM Reprints CORE 2136, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Michel Beine & Oscar Bernal & Jean-Yves Gnabo & Christelle Lecourt, 2007. "Intervention Policy of the BoJ: a Unified Approach," LSF Research Working Paper Series 07-19, Luxembourg School of Finance, University of Luxembourg.
    2. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    3. Hans DEWACHTER & Deniz ERDEMLIOGLU & Jean-Yves GNABO & Christelle LECOURT, 2013. "The intra-day impact of communication on euro-dollar volatility and jumps," Working Papers of Department of Economics, Leuven ces13.04, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    4. Chang, Mei-Ching & Suardi, Sandy & Chang, Yuanchen, 2017. "Foreign exchange intervention in Asian countries: What determine the odds of success during the credit crisis?," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 370-390.
    5. 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.
    6. Jean-Yves Gnabo & Christelle Lecourt, 2008. "Foreign Exchange Intervention Policy: With or Without Transparency? The Case of Japan," Economie Internationale, CEPII research center, issue 113, pages 5-34.
    7. Ricardo T. Fernholz, 2015. "Exchange Rate Manipulation And Constructive Ambiguity," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1323-1348, November.
    8. Kentaro Iwatsubo & Satoshi Kawanishi, 2011. "The Information Improving Channel of Exchange Rate Intervention: How Do Official Announcements Work?," Discussion Papers 1116, Graduate School of Economics, Kobe University.
    9. Robert Dixon & Zhichao Zhang & Yang Dai, 2016. "Exchange Rate Flexibility in China: Measurement, Regime Shifts and Driving Forces of Change," Review of International Economics, Wiley Blackwell, vol. 24(5), pages 875-892, November.
    10. Bernal, Oscar & Gnabo, Jean-Yves, 2009. "Announcements, financial operations or both? Generalizing central banks' FX reaction functions," Journal of the Japanese and International Economies, Elsevier, vol. 23(4), pages 367-394, December.
    11. Stephanos Papadamou & Moïse Sidiropoulos & Eleftherios Spyromitros, 2014. "Does central bank transparency affect stock market volatility?," Post-Print hal-03692261, HAL.
    12. Oscar Bernal Diaz & Jean-Yves Gnabo, 2007. "Talks, financial operations or both? Generalizing central banks' FX reaction functions," DULBEA Working Papers 07-03.RS, ULB -- Universite Libre de Bruxelles.

  29. 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.

    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. Sujay Mukhoti & Pritam Ranjan, 2019. "A new class of discrete-time stochastic volatility model with correlated errors," Applied Economics, Taylor & Francis Journals, vol. 51(3), pages 259-277, January.
    3. Huang, Alex YiHou & Peng, Sheng-Pen & Li, Fangjhy & Ke, Ching-Jie, 2011. "Volatility forecasting of exchange rate by quantile regression," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 591-606, October.
    4. Abdul Jalil Khan & Parvez Azim & Shabib Haider Syed, 2014. "The Impact of Exchange Rate Volatility on Trade: A Panel Study on Pakistan’s Trading Partners," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 19(1), pages 31-66, Jan-June.
    5. Alessandra Pasqualina Viola & Marcelo Cabus Klotzle & Antonio Carlos Figueiredo Pinto & Wagner Piazza Gaglianone, 2017. "Predicting Exchange Rate Volatility in Brazil: an approach using quantile autoregression," Working Papers Series 466, Central Bank of Brazil, Research Department.
    6. Costantini, Mauro & Cuaresma, Jesus Crespo & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Economics Series 305, Institute for Advanced Studies.
    7. 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).
    8. Peter Andersen & Suk-Joong Kim, 2018. "Intraday Timing of AUD Intervention by the Reserve Bank of Australia: Evidence from Microstructural Analyses," World Scientific Book Chapters, in: Information Spillovers and Market Integration in International Finance Empirical Analyses, chapter 2, pages 43-71, World Scientific Publishing Co. Pte. Ltd..
    9. Gabriele Galati & Patrick C. Higgins & Owen F. Humpage & William R. Melick, 2006. "Option prices, exchange market intervention, and the higher moment expectations channel: a user’s guide," Working Papers (Old Series) 0618, Federal Reserve Bank of Cleveland.
    10. 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.
    11. 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.
    12. 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.
    13. 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).
    14. Christian Bauer & Paul De Grauwe & Stefan Reitz, 2007. "Exchange Rates Dynamics in a Target Zone – A Heterogeneous Expectations Approach," CESifo Working Paper Series 2080, CESifo.
    15. João Barata Ribeiro Blanco Barroso, 2018. "Realized Volatility as an Instrument to Official Intervention," Investigación Conjunta-Joint Research, in: Alberto Ortiz-Bolaños (ed.), Monetary Policy and Financial Stability in Latin America and the Caribbean, edition 1, volume 1, chapter 8, pages 259-281, Centro de Estudios Monetarios Latinoamericanos, CEMLA.
    16. Smita Roy Trivedi & P. G. Apte, 2016. "Central Bank Intervention in USD/INR Market: Estimating Its Reaction Function and Impact on Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 23(3), pages 263-279, September.
    17. Hautsch, Nikolaus & Hess, Dieter E. & Veredas, David, 2010. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," CFS Working Paper Series 2010/01, Center for Financial Studies (CFS).
    18. 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.
    19. 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.
    20. 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.
    21. Anupam Dutta & Elie Bouri & David Roubaud, 2021. "Modelling the volatility of crude oil returns: Jumps and volatility forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 889-897, January.
    22. 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).
    23. Federici, Daniela & Gandolfo, Giancarlo, 2012. "The Euro/Dollar exchange rate: Chaotic or non-chaotic? A continuous time model with heterogeneous beliefs," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 670-681.
    24. Roy Trivedi, Smita, 2018. "Exchange rate volatility: Trader's beliefs and the role of news," MPRA Paper 89330, University Library of Munich, Germany.
    25. 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.
    26. 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.
    27. Douglas, Christopher C. & Kolar, Marek, 2009. "Capturing the time dynamics of central bank intervention," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(5), pages 950-968, December.
    28. Xu Gong & Boqiang Lin, 2022. "Predicting the volatility of crude oil futures: The roles of leverage effects and structural changes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 610-640, January.
    29. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight Momentum, Informational Shocks, and Late-Informed Trading in China," MPRA Paper 96784, University Library of Munich, Germany.
    30. Ozili, Peterson K, 2024. "Exchange Rate Unification in Nigeria: Benefits and Implications," MPRA Paper 120441, University Library of Munich, Germany.
    31. Rasmus Fatum & Yohei Yamamoto, 2012. "Does foreign exchange intervention volume matter?," Globalization Institute Working Papers 115, Federal Reserve Bank of Dallas.
    32. Muteba Mwamba, John & Dube, Sandile, 2014. "The impact of exchange rate volatility on international trade between South Africa, China and USA: The case of the manufacturing sector," MPRA Paper 64389, University Library of Munich, Germany.
    33. Arturo Lorenzo-Valdés & Antonio Ruiz-Porras, 2012. "Los rendimientos cambiarios latinoamericanos y la (a)simetría de los shocks informacionales: un análisis econométrico," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 87-113, November.
    34. Ghysels, Eric & Manganelli, Simone & , & Idier, Julien, 2013. "A high frequency assessment of the ECB Securities Markets Programme," CEPR Discussion Papers 9778, C.E.P.R. Discussion Papers.
    35. H. Kent Baker & Satish Kumar & Kirti Goyal & Prashant Gupta, 2023. "International journal of finance and economics: A bibliometric overview," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 9-46, January.
    36. Daniel Stavarek, 2011. "European exchange rates volatility and its asymmetrical components during the financial crisis," MENDELU Working Papers in Business and Economics 2011-17, Mendel University in Brno, Faculty of Business and Economics.
    37. Andres Felipe García-Suaza & José E. Gómez González, 2011. "A simple test of momentum in foreign exchange markets," Documentos de Trabajo 8170, Universidad del Rosario.
    38. 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.
    39. Štefan Lyócsa & Roman Horváth, 2018. "Stock Market Contagion: a New Approach," Open Economies Review, Springer, vol. 29(3), pages 547-577, July.
    40. Daniela Federici & Giancarlo Gandolfo, 2011. "The Euro/Dollar Exchange Rate: Chaotic or Non-Chaotic?," DEGIT Conference Papers c016_035, DEGIT, Dynamics, Economic Growth, and International Trade.
    41. Alexandre Cunha, 2013. "On the relevance of floating exchange rate policies," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 53(2), pages 357-382, June.
    42. Rulu Huang, 2012. "Studies on the Change Mechanism of RMB Exchange Rate with Non-Recurrent Events," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 3(1), pages 49-56, January.
    43. 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.
    44. Bernal, Oscar & Gnabo, Jean-Yves, 2009. "Announcements, financial operations or both? Generalizing central banks' FX reaction functions," Journal of the Japanese and International Economies, Elsevier, vol. 23(4), pages 367-394, December.
    45. Toshio Utsunomiya, 2013. "A new approach to the effect of intervention frequency on the foreign exchange market: evidence from Japan," Applied Economics, Taylor & Francis Journals, vol. 45(26), pages 3742-3759, September.
    46. Smita Roy Trivedi & Bobby Srinivasan, 2016. "Impact of Central Bank Intervention in the Foreign Exchange Market: Evidence from India Using an Event Study Approach," Economic Papers, The Economic Society of Australia, vol. 35(4), pages 389-402, December.
    47. Christopher J. Neely, 2011. "A foreign exchange intervention in an era of restraint," Review, Federal Reserve Bank of St. Louis, vol. 93(Sep), pages 303-324.
    48. Christopher J. Neely, 2011. "A survey of announcement effects on foreign exchange volatility and jumps," Review, Federal Reserve Bank of St. Louis, vol. 93(Sep), pages 361-385.
    49. Oscar Bernal Diaz & Jean-Yves Gnabo, 2007. "Talks, financial operations or both? Generalizing central banks' FX reaction functions," DULBEA Working Papers 07-03.RS, ULB -- Universite Libre de Bruxelles.
    50. Smita Roy Trivedi, 2020. "The Moses effect: can central banks really guide foreign exchange markets?," Empirical Economics, Springer, vol. 58(6), pages 2837-2865, June.

  30. 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).

    Cited by:

    1. Costantini, Mauro & Cuaresma, Jesus Crespo & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Economics Series 305, Institute for Advanced Studies.
    2. 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.
    3. Michel Beine & Charles Bos & Serge Coulombe, 2009. "Does the Canadian economy suffer from Dutch Disease?," DEM Discussion Paper Series 09-06, Department of Economics at the University of Luxembourg.
    4. Georgios Chortareas & Ying Jiang & John C. Nankervis, 2013. "Volatility and Spillover Effects of Yen Interventions," Review of International Economics, Wiley Blackwell, vol. 21(4), pages 671-689, September.
    5. Ferhan SALMAN & Tolga CASKURLU & Mustafa PINAR & Aslihan SALIH, 2008. "Can Central Bank Interventions Affect the Exchange Rate Volatility? Multivariate GARCH Approach Using Constrained Nonlinear Programming," EcoMod2008 23800121, EcoMod.
    6. Christopher J. Neely, 2005. "An analysis of recent studies of the effect of foreign exchange intervention," Review, Federal Reserve Bank of St. Louis, vol. 87(Nov), pages 685-718.
    7. Holmes, Mark J. & Iregui, Ana María & Otero, Jesús, 2021. "The effects of FX-interventions on forecasters disagreement: A mixed data sampling view," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    8. Christopher J. Neely, 2007. "Central bank authorities’ beliefs about foreign exchange intervention," Working Papers 2006-045, Federal Reserve Bank of St. Louis.
    9. Kazım Berk Küçüklerli & Veysel Ulusoy, 2024. "Sentiment-Driven Exchange Rate Forecasting: Integrating Twitter Analysis with Economic Indicators," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 14(3), pages 1-4.
    10. Kunze, Frederik, 2017. "Predicting exchange rates in Asia: New insights on the accuracy of survey forecasts," University of Göttingen Working Papers in Economics 326, University of Goettingen, Department of Economics.
    11. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.

  31. BAUWENS, Luc & LAURENT, Sébastien, 2005. "A new class of multivariate skew densities, with application to generalized autoregressive conditional heteroscedasticity models," LIDAM Reprints CORE 1793, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. N.S. Al-Nassar & Sabri Boubaker & A. Chaibi & B. Makram, 2023. "In Search of Hedges and Safe Havens during the COVID-19 Pandemic: Gold versus Bitcoin, Oil, and Oil Uncertainty," Post-Print hal-04435437, HAL.
    2. Lee, Tae-Hwy & Long, Xiangdong, 2009. "Copula-based multivariate GARCH model with uncorrelated dependent errors," Journal of Econometrics, Elsevier, vol. 150(2), pages 207-218, June.
    3. Mun, Kyung-Chun, 2016. "Hedging bank market risk with futures and forwards," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 112-125.
    4. Drew Creal & Siem Jan Koopman & André Lucas, 2011. "A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 552-563, October.
    5. Allen, David & Lizieri, Colin & Satchell, Stephen, 2020. "A comparison of non-Gaussian VaR estimation and portfolio construction techniques," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 356-368.
    6. Christophe Ley, 2014. "Flexible Modelling in Statistics: Past, present and Future," Working Papers ECARES ECARES 2014-42, ULB -- Universite Libre de Bruxelles.
    7. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).
    8. Canan G. Corlu & Alper Corlu, 2015. "Modelling exchange rate returns: which flexible distribution to use?," Quantitative Finance, Taylor & Francis Journals, vol. 15(11), pages 1851-1864, November.
    9. Mark J. Jensen & John M. Maheu, 2012. "Bayesian Semiparametric Multivariate GARCH Modeling," Working Paper series 48_12, Rimini Centre for Economic Analysis.
    10. Tsuji, Chikashi, 2020. "Correlation and spillover effects between the US and international banking sectors: New evidence and implications for risk management," International Review of Financial Analysis, Elsevier, vol. 70(C).
    11. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
    12. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
    13. Rossi, Eduardo & Spazzini, Filippo, 2008. "Model and distribution uncertainty in multivariate GARCH estimation: a Monte Carlo analysis," MPRA Paper 12260, University Library of Munich, Germany.
    14. 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.
    15. Tsuji, Chikashi, 2018. "New DCC analyses of return transmission, volatility spillovers, and optimal hedging among oil futures and oil equities in oil-producing countries," Applied Energy, Elsevier, vol. 229(C), pages 1202-1217.
    16. Javier Mencía & Enrique Sentana, 2009. "Multivariate location-scale mixtures of normals and mean-variance-skewness portfolio allocation," Working Papers 0909, Banco de España.
    17. 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 69-94, January.
    18. Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," LSE Research Online Documents on Economics 66365, London School of Economics and Political Science, LSE Library.
    19. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    20. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    21. Yu, Honghai & Du, Donglei & Fang, Libing & Yan, Panpan, 2018. "Risk contribution of crude oil to industry stock returns," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 179-199.
    22. Abdul Hakim & Michael McAleer, 2009. "VaR Forecasts and Dynamic Conditional Correlations for Spot and Futures Returns on Stocks and Bonds," CARF F-Series CARF-F-178, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    23. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    24. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    25. Tafakori, Laleh & Pourkhanali, Armin & Fard, Farzad Alavi, 2018. "Forecasting spikes in electricity return innovations," Energy, Elsevier, vol. 150(C), pages 508-526.
    26. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    27. Audrone Virbickaite & M. Concepci'on Aus'in & Pedro Galeano, 2013. "A Bayesian Non-Parametric Approach to Asymmetric Dynamic Conditional Correlation Model With Application to Portfolio Selection," Papers 1301.5129, arXiv.org, revised Jan 2014.
    28. Kuang, Wei, 2022. "The economic value of high-frequency data in equity-oil hedge," Energy, Elsevier, vol. 239(PA).
    29. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    30. 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.
    31. Ogata, Hiroaki, 2013. "Estimation for multivariate stable distributions with generalized empirical likelihood," Journal of Econometrics, Elsevier, vol. 172(2), pages 248-254.
    32. Jos� A. Fioruci & Ricardo S. Ehlers & Marinho G. Andrade Filho, 2014. "Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 320-331, February.
    33. Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
    34. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2012. "Independent Factor Autoregressive Conditional Density Model," DEM Working Papers Series 021, University of Pavia, Department of Economics and Management.
    35. M. Hashem Pesaran & Bahram Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series 2056, CESifo.
    36. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2011. "Multivariate semi-nonparametric distributions with dynamic conditional correlations," International Journal of Forecasting, Elsevier, vol. 27(2), pages 347-364, April.
    37. Storti, Giuseppe & Wang, Chao, 2022. "A multivariate semi-parametric portfolio risk optimization and forecasting framework," MPRA Paper 115266, University Library of Munich, Germany.
    38. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    39. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2021. "Hedging stocks with oil," Energy Economics, Elsevier, vol. 93(C).
    40. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    41. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    42. Fresoli, Diego E. & Ruiz, Esther, 2016. "The uncertainty of conditional returns, volatilities and correlations in DCC models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 170-185.
    43. Tshikalange, Mulanga & Bonga-Bonga, Lumengo, 2023. "The determinants of the dynamic correlation between foreign exchange and equity markets: Cross-Country comparisons," MPRA Paper 118401, University Library of Munich, Germany.
    44. Luis García-Álvarez & Richard Luger, 2011. "Dynamic Correlations, Estimation Risk, and Porfolio Management During the Financial Crisis," Working Papers wp2011_1103, CEMFI, revised Sep 2011.
    45. Kinateder, Harald & Campbell, Ross & Choudhury, Tonmoy, 2021. "Safe haven in GFC versus COVID-19: 100 turbulent days in the financial markets," Finance Research Letters, Elsevier, vol. 43(C).
    46. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility," CIRJE F-Series CIRJE-F-488, CIRJE, Faculty of Economics, University of Tokyo.
    47. Wei Kuang, 2024. "High-frequency enhanced VaR: A robust univariate realized volatility model for diverse portfolios and market conditions," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-35, May.
    48. 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.
    49. Yue Peng & Wing Ng, 2012. "Analysing financial contagion and asymmetric market dependence with volatility indices via copulas," Annals of Finance, Springer, vol. 8(1), pages 49-74, February.
    50. Giuseppe Storti & Chao Wang, 2022. "A semi-parametric dynamic conditional correlation framework for risk forecasting," Papers 2207.04595, arXiv.org, revised Dec 2024.
    51. Vellachami, Sanggetha & Hasanov, Akram Shavkatovich & Brooks, Robert, 2023. "Risk transmission from the energy markets to the carbon market: Evidence from the recursive window approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
    52. Mori Kogid & Jaratin Lily & Rozilee Asid & James M. Alin & Dullah Mulok, 2022. "Volatility spillover and dynamic co-movement of foreign direct investment between Malaysia and China and developed countries," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(1), pages 131-148, February.
    53. 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.
    54. Ryo Kinoshita, 2015. "Asset allocation under higher moments with the GARCH filter," Empirical Economics, Springer, vol. 49(1), pages 235-254, August.
    55. Anatolyev Stanislav, 2009. "Multi-Market Direction-of-Change Modeling Using Dependence Ratios," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-24, March.
    56. Julio Mulero & Miguel A. Sordo & Marilia C. de Souza & Alfonso Suárez‐LLorens, 2017. "Two stochastic dominance criteria based on tail comparisons," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(6), pages 575-589, November.
    57. Karanasos, M. & Kartsaklas, A., 2009. "Dual long-memory, structural breaks and the link between turnover and the range-based volatility," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 838-851, December.
    58. Deschamps, Philippe J., 2012. "Bayesian estimation of generalized hyperbolic skewed student GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3035-3054.
    59. Emmanuel Afuecheta & Artur Semeyutin & Stephen Chan & Saralees Nadarajah & Diego Andrés Pérez Ruiz, 2020. "Compound distributions for financial returns," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-25, October.
    60. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    61. Javier Mencía & Enrique Sentana, 2009. "Distributional tests in multivariate dynamic models with Normal and Student t innovations," Working Papers 0929, Banco de España.
    62. Kim, Gunky & Silvapulle, Mervyn J. & Silvapulle, Paramsothy, 2007. "Comparison of semiparametric and parametric methods for estimating copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2836-2850, March.
    63. Kirt Butler & Katsushi Okada, 2009. "The relative contribution of conditional mean and volatility in bivariate returns to international stock market indices," Applied Financial Economics, Taylor & Francis Journals, vol. 19(1), pages 1-15.
    64. Tsukuda, Yoshihiko & Shimada, Junji & Miyakoshi, Tatsuyoshi, 2017. "Bond market integration in East Asia: Multivariate GARCH with dynamic conditional correlations approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 193-213.
    65. Ole E. Barndorff-Nielsen & Neil Shephard, 2012. "Basics of Levy processes," Economics Papers 2012-W06, Economics Group, Nuffield College, University of Oxford.
    66. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
    67. Valeriane Jokhadze & Wolfgang M. Schmidt, 2020. "Measuring Model Risk In Financial Risk Management And Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 1-37, April.
    68. Josip Arneric & Elza Jurun & Snježana Pivac, 2008. "Multivariate Risk-Return Decision Making Within Dynamic Estimation," Economic Analysis Working Papers (2002-2010). Atlantic Review of Economics (2011-2016), Colexio de Economistas de A Coruña, Spain and Fundación Una Galicia Moderna, vol. 7, pages 1-11, October.
    69. C. Alexander & M. Coulon & Y. Han & X. Meng, 2024. "Evaluating the discrimination ability of proper multi-variate scoring rules," Annals of Operations Research, Springer, vol. 334(1), pages 857-883, March.
    70. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    71. Kai Dong & Ching-Ter Chang & Shaonan Wang & Xiaoxi Liu, 2021. "The Dynamic Correlation among Financial Leverage, House Price, and Consumer Expenditure in China," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    72. Kris Boudt & Dries Cornilly & Tim Verdonck, 2019. "Nearest Comoment Estimation With Unobserved Factors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/970, Ghent University, Faculty of Economics and Business Administration.
    73. Zhu, Ke & Li, Wai Keung, 2013. "A new Pearson-type QMLE for conditionally heteroskedastic models," MPRA Paper 52344, University Library of Munich, Germany.
    74. Rainer Jobst & Daniel Rösch & Harald Scheule & Martin Schmelzle, 2015. "A Simple Econometric Approach for Modeling Stress Event Intensities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 300-320, April.
    75. Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.
    76. Cao, Yufei, 2022. "Extreme risk spillovers across financial markets under different crises," Economic Modelling, Elsevier, vol. 116(C).
    77. Yip, Iris W.H. & So, Mike K.P., 2009. "Simplified specifications of a multivariate generalized autoregressive conditional heteroscedasticity model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(2), pages 327-340.
    78. Fang, Libing & Chen, Baizhu & Yu, Honghai & Qian, Yichuo, 2018. "Identifying systemic important markets from a global perspective: Using the ADCC ΔCoVaR approach with skewed-t distribution," Finance Research Letters, Elsevier, vol. 24(C), pages 137-144.
    79. Zouheir Mighri, 2018. "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 427-473, June.
    80. Luca Merlo & Lea Petrella & Valentina Raponi, 2021. "Forecasting VaR and ES using a joint quantile regression and implications in portfolio allocation," Papers 2106.06518, arXiv.org.
    81. Guangyang Chen & Kai Dong & Shaonan Wang & Xiuli Du & Ronghua Zhou & Zhongwei Yang, 2022. "The Dynamic Relationship among Bank Credit, House Prices and Carbon Dioxide Emissions in China," IJERPH, MDPI, vol. 19(16), pages 1-18, August.
    82. Carnero M. Angeles & Eratalay M. Hakan, 2014. "Estimating VAR-MGARCH models in multiple steps," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 339-365, May.
    83. Ramzi Nekhili & Jahangir Sultan, 2020. "Jump Driven Risk Model Performance in Cryptocurrency Market," IJFS, MDPI, vol. 8(2), pages 1-18, April.
    84. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    85. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2022. "The influence of the COVID-19 pandemic on the hedging functionality of Chinese financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    86. Li, Xindan & Yu, Honghai & Fang, Libing & Xiong, Cheng, 2019. "Do firm-level factors play forward-looking role for financial systemic risk: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    87. Donghang Luo & Ke Zhu & Huan Gong & Dong Li, 2020. "Testing error distribution by kernelized Stein discrepancy in multivariate time series models," Papers 2008.00747, arXiv.org.
    88. 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.
    89. Wenwen Zhang, 2022. "Stock Market Co-movements in RCEP Participating Countries," Economics Bulletin, AccessEcon, vol. 42(2), pages 1180-1191.
    90. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
    91. Jiangyu Ji & Andre Lucas, 2012. "A New Semiparametric Volatility Model," Tinbergen Institute Discussion Papers 12-055/2/DSF35, Tinbergen Institute.
    92. Zouheir Mighri & Faysal Mansouri, 2014. "Modeling international stock market contagion using multivariate fractionally integrated APARCH approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-25, December.
    93. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    94. Tsuji, Chikashi, 2018. "Return transmission and asymmetric volatility spillovers between oil futures and oil equities: New DCC-MEGARCH analyses," Economic Modelling, Elsevier, vol. 74(C), pages 167-185.
    95. Yu, Honghai & Fang, Libing & Sun, Boyang & Du, Donglei, 2018. "Risk contribution of the Chinese stock market to developed markets in the post-crisis period," Emerging Markets Review, Elsevier, vol. 34(C), pages 87-97.
    96. Arellano-Valle, Reinaldo B. & Azzalini, Adelchi & Ferreira, Clécio S. & Santoro, Karol, 2020. "A two-piece normal measurement error model," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    97. Joo, Young C. & Park, Sung Y., 2017. "Oil prices and stock markets: Does the effect of uncertainty change over time?," Energy Economics, Elsevier, vol. 61(C), pages 42-51.
    98. Massacci, Daniele, 2014. "A two-regime threshold model with conditional skewed Student t distributions for stock returns," Economic Modelling, Elsevier, vol. 43(C), pages 9-20.
    99. Tomáš Jeøábek, 2020. "The Efficiency of GARCH Models in Realizing Value at Risk Estimates," ACTA VSFS, University of Finance and Administration, vol. 14(1), pages 32-50.
    100. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    101. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    102. Xin Zhang & Drew Creal & Siem Jan Koopman & Andre Lucas, 2011. "Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails," Tinbergen Institute Discussion Papers 11-078/2/DSF22, Tinbergen Institute.
    103. Gregory, Gadzinski & Alessio, Castello & Vito, Liuzzi & Patrice, Sargenti, 2024. "Break a peg! A study of stablecoin co-instability," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    104. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    105. Hassan, M. Kabir & Djajadikerta, Hadrian Geri & Choudhury, Tonmoy & Kamran, Muhammad, 2022. "Safe havens in Islamic financial markets: COVID-19 versus GFC," Global Finance Journal, Elsevier, vol. 54(C).
    106. Al-Nassar, Nassar S. & Boubaker, Sabri & Chaibi, Anis & Makram, Beljid, 2023. "In search of hedges and safe havens during the COVID─19 pandemic: Gold versus Bitcoin, oil, and oil uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 318-332.
    107. Alexey Balaev, 2011. "Modeling multivariate parametric densities of financial returns (in Russian)," Quantile, Quantile, issue 9, pages 39-60, July.
    108. Arturo Leccadito & Alessandro Staino & Pietro Toscano, 2024. "A novel robust method for estimating the covariance matrix of financial returns with applications to risk management," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-28, December.
    109. Merlo, Luca & Petrella, Lea & Raponi, Valentina, 2021. "Forecasting VaR and ES using a joint quantile regression and its implications in portfolio allocation," Journal of Banking & Finance, Elsevier, vol. 133(C).
    110. Zouheir Mighri & Faysal Mansouri, 2013. "Dynamic Conditional Correlation Analysis of Stock Market Contagion: Evidence from the 2007-2010 Financial Crises," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 637-661.
    111. Ehlers, Ricardo S., 2012. "Computational tools for comparing asymmetric GARCH models via Bayes factors," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 858-867.
    112. Shimizu, Katsutoshi & Ly, Kim Cuong, 2017. "Were regulatory interventions effective in lowering systemic risk during the financial crisis in Japan?," Journal of Multinational Financial Management, Elsevier, vol. 41(C), pages 80-91.
    113. Balaev , Alexey, 2011. "Multivariate skewed t-distribution with degrees of freedom vector and its application to financial modeling," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 23(3), pages 79-97.
    114. Wu, Ximing, 2010. "Exponential Series Estimator of multivariate densities," Journal of Econometrics, Elsevier, vol. 156(2), pages 354-366, June.

  32. Michel Beine & Sébastien Laurent & Franz Palm, 2004. "Have sequential interventions of Central Banks in foreign exchange been effective ?," ULB Institutional Repository 2013/10429, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Oscar Bernal Diaz, 2006. "Do interactions between political authorities and central banks influence FX interventions? Evidence from Japan," DULBEA Working Papers 06-03.RS, ULB -- Universite Libre de Bruxelles.
    2. Michel Beine & Ariane Szafarz, 2006. "Size matters: Central bank interventions on the Yen/Dollar exchange rate," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 49(1), pages 5-20.
    3. Kim, Suk-Joong & Pham, Cyril Minh Dao, 2006. "Is foreign exchange intervention by central banks bad news for debt markets?: A case of Reserve Bank of Australia's interventions 1986-2003," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(5), pages 446-467, December.

  33. LAURENT, Sébastien & URBAIN, Jean-Pierre, 2004. "Bridging the gap between Ox and Gauss using OxGauss," LIDAM Discussion Papers CORE 2004012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Maus, Stefan & Peters, Hans & Storcken, Ton, 2007. "Anonymous voting and minimal manipulability," Journal of Economic Theory, Elsevier, vol. 135(1), pages 533-544, July.
    2. Lok, R.B. & Romero Morales, D. & Vermeulen, A.J., 2005. "The agents-are-substitutes property in continuous generalized assignment problems," Research Memorandum 009, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    3. Benoit Bellone, 2005. "Classical Estimation of Multivariate Markov-Switching Models using MSVARlib," Econometrics 0508017, University Library of Munich, Germany.

  34. GIOT, Pierre & LAURENT, Sébastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," LIDAM Reprints CORE 1708, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. 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.
    2. Li, Longqing, 2017. "A Comparative Study of GARCH and EVT Model in Modeling Value-at-Risk," MPRA Paper 85645, University Library of Munich, Germany.
    3. Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
    4. Taewook Lee & Moosup Kim & Changryong Baek, 2015. "Tests for Volatility Shifts in Garch Against Long-Range Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 127-153, March.
    5. Degiannakis, Stavros & Floros, Christos & Dent, Pamela, 2013. "Forecasting Value-at-Risk and Expected Shortfall using Fractionally Integrated Models of Conditional Volatility: International Evidence," MPRA Paper 80433, University Library of Munich, Germany.
    6. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    7. Berger, Theo & Gençay, Ramazan, 2018. "Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 30-46.
    8. 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.
    9. Kawakami, Tabito, 2023. "Quantile prediction for Bitcoin returns using financial assets’ realized measures," Finance Research Letters, Elsevier, vol. 55(PA).
    10. BELTRAN, Helena & DURRE, Alain & GIOT, Pierre, 2005. "Volatility regimes and the provision of liquidity in order book markets," LIDAM Discussion Papers CORE 2005012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It's all about volatility of volatility: evidence from a two-factor stochastic volatility model," Studies in Economics 1404, School of Economics, University of Kent.
    12. John M Maheu & Thomas H McCurdy, 2008. "Do high-frequency measures of volatility improve forecasts of return distributions?," Working Papers tecipa-324, University of Toronto, Department of Economics.
    13. 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-921, CIRJE, Faculty of Economics, University of Tokyo.
    14. Naeem, Muhammad & Shahbaz, Muhammad & Saleem, Kashif & Mustafa, Faisal, 2019. "Risk analysis of high frequency precious metals returns by using long memory model," Resources Policy, Elsevier, vol. 61(C), pages 399-409.
    15. Paolo Capelli & Federica Ielasi & Angeloantonio Russo, 2021. "Forecasting volatility by integrating financial risk with environmental, social, and governance risk," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(5), pages 1483-1495, September.
    16. Dionne, Georges & Duchesne, Pierre & Pacurar, Maria, 2005. "Intraday Value at Risk (IVaR) using tick-by-tick data with application to the Toronto Stock Exchange," Working Papers 05-9, HEC Montreal, Canada Research Chair in Risk Management.
    17. 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.
    18. 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.
    19. Shawkat Hammoudeh & Farooq Malik & Michael McAleer, 2010. "Risk Management of Precious Metals," Working Papers in Economics 10/37, University of Canterbury, Department of Economics and Finance.
    20. Zhimin Wu & Guanghui Cai, 2024. "Can intraday data improve the joint estimation and prediction of risk measures? Evidence from a variety of realized measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1956-1974, September.
    21. Radovan Parrák, 2013. "The Economic Valuation of Variance Forecasts: An Artificial Option Market Approach," Working Papers IES 2013/09, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2013.
    22. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    23. Anupam Dutta, 2025. "Assessing the Risk of Bitcoin Futures Market: New Evidence," Annals of Data Science, Springer, vol. 12(2), pages 481-497, April.
    24. Mei, Dexiang & Xie, Yutang, 2022. "U.S. grain commodity futures price volatility: Does trade policy uncertainty matter?," Finance Research Letters, Elsevier, vol. 48(C).
    25. Degiannakis, Stavros & Potamia, Artemis, 2017. "Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 176-190.
    26. Javier Sánchez García & Salvador Cruz Rambaud, 2022. "A GARCH approach to model short‐term interest rates: Evidence from Spanish economy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1621-1632, April.
    27. Grané, A. & Veiga, H., 2008. "Accurate minimum capital risk requirements: A comparison of several approaches," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2482-2492, November.
    28. 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.
    29. Stavros Degiannakis, 2008. "ARFIMAX and ARFIMAX-TARCH realized volatility modeling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(10), pages 1169-1180.
    30. Angelidis, Timotheos & Degiannakis, Stavros, 2008. "Volatility forecasting: Intra-day versus inter-day models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 449-465, December.
    31. 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.
    32. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    33. Jeroen Rombouts & E.W. Rengifo, 2004. "Dynamic Optimal Portfolio Selection in a VaR Framework," Cahiers de recherche 04-05, HEC Montréal, Institut d'économie appliquée.
    34. Helena Beltran & Alain Durré & Pierre Giot, 2004. "How does liquidity react to stress periods in a limit order market?," Working Paper Research 49, National Bank of Belgium.
    35. Bradley T. Ewing & Farooq Malik & Hassan Anjum, 2019. "Forecasting value‐at‐risk in oil prices in the presence of volatility shifts," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 341-350, July.
    36. 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.
    37. 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.
    38. Lima, Luiz Renato & Néri, Breno Pinheiro, 2007. "Comparing Value-at-Risk Methodologies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 27(1), May.
    39. Zhu, Ke, 2015. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," MPRA Paper 61930, University Library of Munich, Germany.
    40. Ke Yang & Langnan Chen & Fengping Tian, 2015. "Realized Volatility Forecast of Stock Index Under Structural Breaks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(1), pages 57-82, January.
    41. Degiannakis, Stavros & Dent, Pamela & Floros, Christos, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," MPRA Paper 80431, University Library of Munich, Germany.
    42. Maghyereh Aktham Issa & Awartani Basel, 2012. "Modeling and Forecasting Value-at-Risk in the UAE Stock Markets: The Role of Long Memory, Fat Tails and Asymmetries in Return Innovations," Review of Middle East Economics and Finance, De Gruyter, vol. 8(1), pages 1-22, August.
    43. 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.
    44. Härdle, Wolfgang Karl & Mungo, Julius, 2008. "Value-at-risk and expected shortfall when there is long range dependence," SFB 649 Discussion Papers 2008-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    45. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 volatility using ultra-high frequency data," Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
    46. 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.
    47. 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.
    48. Niguez, Trino-Manuel & Perote, Javier, 2004. "Forecasting the density of asset returns," LSE Research Online Documents on Economics 6845, London School of Economics and Political Science, LSE Library.
    49. Emrah Ismail Cevik & Sel Dibooglu & Atif Awad Abdallah & Eisa Abdulrahman Al-Eisa, 2021. "Oil prices, stock market returns, and volatility spillovers: evidence from Saudi Arabia," International Economics and Economic Policy, Springer, vol. 18(1), pages 157-175, February.
    50. Ke Yang & Langnan Chen, 2014. "Realized Volatility Forecast: Structural Breaks, Long Memory, Asymmetry, and Day-of-the-Week Effect," International Review of Finance, International Review of Finance Ltd., vol. 14(3), pages 345-392, September.
    51. Fengler, Matthias R. & Okhrin, Ostap, 2012. "Realized copula," SFB 649 Discussion Papers 2012-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    52. Frantiv{s}ek v{C}ech & Jozef Barun'ik, 2018. "Panel quantile regressions for estimating and predicting the Value--at--Risk of commodities," Papers 1807.11823, arXiv.org.
    53. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    54. 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.
    55. Sinha, Pankaj & Agnihotri, Shalini, 2014. "Sensitivity of Value at Risk estimation to NonNormality of returns and Market capitalization," MPRA Paper 56307, University Library of Munich, Germany, revised 26 May 2014.
    56. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    57. 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.
    58. Kuang, Wei, 2022. "The economic value of high-frequency data in equity-oil hedge," Energy, Elsevier, vol. 239(PA).
    59. Reza Habibi, 2011. "A Simple Estimate of VAR under Garch Modelling," Ekonomia, Cyprus Economic Society and University of Cyprus, vol. 14(2), pages 127-136, Winter.
    60. Cyril Coste & Raphaël Douady & Ilija I Zovko, 2010. "The StressVaR: A New Risk Concept for Extreme Risk and Fund Allocation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-02488591, HAL.
    61. 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.
    62. Grané Chávez, 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.
    63. Viviana Fernandez & Brian M. Lucey, 2006. "Portfolio management implications of volatility shifts: Evidence from simulated data," The Institute for International Integration Studies Discussion Paper Series iiisdp131, IIIS.
    64. Jian Zhou, 2012. "Extreme risk measures for REITs: a comparison among alternative methods," Applied Financial Economics, Taylor & Francis Journals, vol. 22(2), pages 113-126, January.
    65. Vasiliki D. Skintzi & Spyros Xanthopoulos-Sisinis, 2007. "Evaluation of correlation forecasting models for risk management," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 497-526.
    66. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    67. Hartz, Christoph & Mittnik, Stefan & Paolella, Marc, 2006. "Accurate value-at-risk forecasting based on the normal-GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2295-2312, December.
    68. Bams, Dennis & Blanchard, Gildas & Lehnert, Thorsten, 2017. "Volatility measures and Value-at-Risk," International Journal of Forecasting, Elsevier, vol. 33(4), pages 848-863.
    69. Xiao-Ming Li & Qing Xu, 2007. "Evaluating density forecasts of the model with a conditional skewed-t distribution for China's stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 18(3), pages 213-227.
    70. Dimitrios P. Louzis & Spyros Xanthopoulos - Sissinis & Apostolos P. Refenes, 2012. "Stock index Value-at-Risk forecasting: A realized volatility extreme value theory approach," Economics Bulletin, AccessEcon, vol. 32(1), pages 981-991.
    71. Hung, Jui-Cheng & Lee, Ming-Chih & Liu, Hung-Chun, 2008. "Estimation of value-at-risk for energy commodities via fat-tailed GARCH models," Energy Economics, Elsevier, vol. 30(3), pages 1173-1191, May.
    72. Ivana Komunjer, 2004. "Asymmetric Power Distribution: Theory and Applications to Risk Measurement," Econometric Society 2004 Latin American Meetings 44, Econometric Society.
    73. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    74. Stefano Grassi & Paolo Santucci de Magistris, 2011. "When Long Memory Meets the Kalman Filter: A Comparative Study," CREATES Research Papers 2011-14, Department of Economics and Business Economics, Aarhus University.
    75. Cheong, Chin Wen, 2009. "Modeling and forecasting crude oil markets using ARCH-type models," Energy Policy, Elsevier, vol. 37(6), pages 2346-2355, June.
    76. Clements, Michael P. & Galvao, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," Economic Research Papers 269747, University of Warwick - Department of Economics.
    77. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    78. Branco, Rafael R. & Rubesam, Alexandre & Zevallos, Mauricio, 2024. "Forecasting realized volatility: Does anything beat linear models?," Journal of Empirical Finance, Elsevier, vol. 78(C).
    79. 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.
    80. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    81. 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.
    82. Wen Cheong, Chin & Hassan Shaari Mohd Nor, Abu & Isa, Zaidi, 2007. "Asymmetry and long-memory volatility: Some empirical evidence using GARCH," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 651-664.
    83. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    84. 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.
    85. Wei Kuang, 2024. "High-frequency enhanced VaR: A robust univariate realized volatility model for diverse portfolios and market conditions," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-35, May.
    86. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    87. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    88. Kawakatsu, Hiroyuki, 2007. "Specification and estimation of discrete time quadratic stochastic volatility models," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 424-442, June.
    89. 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.
    90. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2012. "Forecasting Realized (Co)Variances with a Bloc Structure Wishart Autoregressive Model," Working Papers on Finance 1211, University of St. Gallen, School of Finance.
    91. Paolella, Marc S. & Taschini, Luca, 2008. "An econometric analysis of emission allowance prices," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2022-2032, October.
    92. 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.
    93. 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.
    94. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2021. "The realized volatility of commodity futures: Interconnectedness and determinants#," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 139-151.
    95. 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.
    96. Halbleib, Roxana & Pohlmeier, Winfried, 2012. "Improving the value at risk forecasts: Theory and evidence from the financial crisis," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1212-1228.
    97. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    98. Christian T. Brownlees & Giampiero M. Gallo, 2007. "Comparison of Volatility Measures: a Risk Management Perspective," Econometrics Working Papers Archive wp2007_15, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    99. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    100. 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).
    101. 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.
    102. 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.
    103. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
    104. Eugenie Hol & Siem Jan Koopman & Borus Jungbacker, 2004. "Forecasting daily variability of the S\&P 100 stock index using historical, realised and implied volatility measurements," Computing in Economics and Finance 2004 342, Society for Computational Economics.
    105. 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.
    106. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
    107. J. Hambuckers & C. Heuchenne, 2017. "A robust statistical approach to select adequate error distributions for financial returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 137-161, January.
    108. 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.
    109. 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.
    110. Shijia Song & Handong Li, 2023. "A new model for forecasting VaR and ES using intraday returns aggregation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1039-1054, August.
    111. 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.
    112. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    113. Kwangmin Jung & Donggyu Kim & Seunghyeon Yu, 2021. "Next Generation Models for Portfolio Risk Management: An Approach Using Financial Big Data," Papers 2102.12783, arXiv.org, revised Feb 2022.
    114. Lazar, Emese & Xue, Xiaohan, 2020. "Forecasting risk measures using intraday data in a generalized autoregressive score framework," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1057-1072.
    115. 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.
    116. Köksal, Bülent & Orhan, Mehmet, 2012. "Market risk of developed and developing countries during the global financial crisis," MPRA Paper 37523, University Library of Munich, Germany.
    117. Degiannakis, Stavros, 2008. "Forecasting Vix," MPRA Paper 96307, University Library of Munich, Germany.
    118. Slim, Skander & Koubaa, Yosra & BenSaïda, Ahmed, 2017. "Value-at-Risk under Lévy GARCH models: Evidence from global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 30-53.
    119. P. Herings & Kirsten Rohde, 2006. "Time-inconsistent preferences in a general equilibrium model," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 29(3), pages 591-619, November.
    120. Wang Yu-Jen & Chung Huimin & Guo Jia-Hau, 2013. "A value-at-risk analysis of carry trades using skew-GARCH models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 439-459, September.
    121. 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.
    122. 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.
    123. Dilip Kumar, 2016. "Estimating and forecasting value-at-risk using the unbiased extreme value volatility estimator," Proceedings of Economics and Finance Conferences 3205528, International Institute of Social and Economic Sciences.
    124. Huarng, Kunhuang & Yu, Hui-Kuang, 2005. "A Type 2 fuzzy time series model for stock index forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 445-462.
    125. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2016. "Intraday volatility interaction between the crude oil and equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 1-13.
    126. 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.
    127. Wong, Woon K., 2010. "Backtesting value-at-risk based on tail losses," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 526-538, June.
    128. Mehmet Sahiner & David G. McMillan & Dimos Kambouroudis, 2023. "Do artificial neural networks provide improved volatility forecasts: Evidence from Asian markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(3), pages 723-762, September.
    129. Stefano Grassi & Nima Nonejad & Paolo Santucci de Magistris, 2014. "Forecasting with the Standardized Self-Perturbed Kalman Filter," CREATES Research Papers 2014-12, Department of Economics and Business Economics, Aarhus University.
    130. Christophe Chorro & Dominique Guegan & Florian Ielpo & Hanjarivo Lalaharison, 2014. "Testing for Leverage Effects in the Returns of US Equities," Documents de travail du Centre d'Economie de la Sorbonne 14022r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jan 2017.
    131. Chaker Aloui, 2015. "Volatility forecasting and risk management in some MENA stock markets: a nonlinear framework," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 5(2), pages 160-192.
    132. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 594-616.
    133. 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.
    134. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    135. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    136. Malin Song & Zixu Sui & Xin Zhao, 2023. "A risk measurement study evaluating the impact of COVID-19 on China's financial market using the QR-SGED-EGARCH model," Annals of Operations Research, Springer, vol. 330(1), pages 787-806, November.
    137. Kurita, Takamitsu, 2014. "Dynamic characteristics of the daily yen–dollar exchange rate," Research in International Business and Finance, Elsevier, vol. 30(C), pages 72-82.
    138. Shao, Xi-Dong & Lian, Yu-Jun & Yin, Lian-Qian, 2009. "Forecasting Value-at-Risk using high frequency data: The realized range model," Global Finance Journal, Elsevier, vol. 20(2), pages 128-136.
    139. 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.
    140. Chaker Aloui & Hela BEN HAMIDA, 2015. "Estimation and Performance Assessment of Value-at-Risk and Expected Shortfall Based on Long-Memory GARCH-Class Models," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 30-54, January.
    141. 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).
    142. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "Emerging versus developed volatility indices. The comparison of VIW20 and VIX indices," Working Papers 2009-11, Faculty of Economic Sciences, University of Warsaw.
    143. Angelidis, Timotheos & Degiannakis, Stavros, 2008. "Volatility forecasting: intra-day vs. inter-day models," MPRA Paper 80434, University Library of Munich, Germany.
    144. Trung H. Le, 2024. "Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 402-414, March.
    145. Talpsepp, Tõnn & Rieger, Marc Oliver, 2010. "Explaining asymmetric volatility around the world," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 938-956, December.
    146. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    147. Stavros Degiannakis & Andreas Andrikopoulos & Timotheos Angelidis & Christos Floros, 2013. "Return dispersion, stock market liquidity and aggregate economic activity," Working Papers 166, Bank of Greece.
    148. 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.
    149. Eunho Koo & Geonwoo Kim, 2023. "A New Neural Network Approach for Predicting the Volatility of Stock Market," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1665-1679, April.
    150. André A. P. Santos & Francisco J. Nogales & Esther Ruiz, 2013. "Comparing Univariate and Multivariate Models to Forecast Portfolio Value-at-Risk," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 400-441, March.
    151. 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.
    152. 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.
    153. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
    154. Hamidreza Arian & Hossein Poorvasei & Azin Sharifi & Shiva Zamani, 2020. "The Uncertain Shape of Grey Swans: Extreme Value Theory with Uncertain Threshold," Papers 2011.06693, arXiv.org.
    155. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
    156. Huang, Chuangxia & Cai, Yaqian & Yang, Xiaoguang & Deng, Yanchen & Yang, Xin, 2023. "Laplacian-energy-like measure: Does it improve the Cross-Sectional Absolute Deviation herding model?," Economic Modelling, Elsevier, vol. 127(C).
    157. Dilip Kumar, 2020. "Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 587-610, September.
    158. 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.
    159. Araújo Santos, P. & Fraga Alves, M.I., 2013. "Forecasting Value-at-Risk with a duration-based POT method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 295-309.
    160. Anjum, Hassan & Malik, Farooq, 2020. "Forecasting risk in the US Dollar exchange rate under volatility shifts," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    161. Tully, Edel & Lucey, Brian M., 2007. "A power GARCH examination of the gold market," Research in International Business and Finance, Elsevier, vol. 21(2), pages 316-325, June.
    162. 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.
    163. Benoît Sévi, 2014. "Forecasting the volatility of crude oil futures using intraday data," Working Papers 2014-53, Department of Research, Ipag Business School.
    164. Sobreira, Nuno & Louro, Rui, 2020. "Evaluation of volatility models for forecasting Value-at-Risk and Expected Shortfall in the Portuguese stock market," Finance Research Letters, Elsevier, vol. 32(C).
    165. 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.
    166. 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.
    167. 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.
    168. Grané Chávez, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    169. 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).
    170. Jouchi Nakajima, 2008. "EGARCH and Stochastic Volatility: Modeling Jumps and Heavy-tails for Stock Returns," IMES Discussion Paper Series 08-E-23, Institute for Monetary and Economic Studies, Bank of Japan.
    171. Hallam, Mark & Olmo, Jose, 2014. "Forecasting daily return densities from intraday data: A multifractal approach," International Journal of Forecasting, Elsevier, vol. 30(4), pages 863-881.
    172. Hartz, Christoph & Mittnik, Stefan & Paolella, Marc S., 2006. "Accurate Value-at-Risk forecast with the (good old) normal-GARCH model," CFS Working Paper Series 2006/23, Center for Financial Studies (CFS).
    173. Fernandez, Viviana & Lucey, Brian M., 2007. "Portfolio management under sudden changes in volatility and heterogeneous investment horizons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 612-624.
    174. Harvey, Andrew & Sucarrat, Genaro, 2014. "EGARCH models with fat tails, skewness and leverage," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 320-338.
    175. Sang Hoon Kang & Seong-Min Yoon, 2009. "Value-at-Risk Analysis for Asian Emerging Markets: Asymmetry and Fat Tails in Returns Innovation," Korean Economic Review, Korean Economic Association, vol. 25, pages 387-411.
    176. Hood, Matthew & Malik, Farooq, 2018. "Estimating downside risk in stock returns under structural breaks," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 102-112.
    177. 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.
    178. Ibrahim Ergen, 2015. "Two-step methods in VaR prediction and the importance of fat tails," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1013-1030, June.
    179. Huang, Jingjing & Shang, Pengjian & Zhao, Xiaojun, 2012. "Multifractal diffusion entropy analysis on stock volatility in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5739-5745.
    180. Y. C. Su & H. C. Huang & Y. J. Lin, 2011. "GJR-GARCH model in value-at-risk of financial holdings," Applied Financial Economics, Taylor & Francis Journals, vol. 21(24), pages 1819-1829, December.
    181. Mendes, Beatriz Vaz de Melo & Accioly, Victor Bello, 2012. "On the dependence structure of realized volatilities," International Review of Financial Analysis, Elsevier, vol. 22(C), pages 1-9.
    182. Kalnina, Ilze, 2011. "Subsampling high frequency data," Journal of Econometrics, Elsevier, vol. 161(2), pages 262-283, April.
    183. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    184. Orla McCullagh & Mark Cummins & Sheila Killian, 2023. "Decoupling VaR and regulatory capital: an examination of practitioners’ experience of market risk regulation," Journal of Banking Regulation, Palgrave Macmillan, vol. 24(3), pages 321-336, September.
    185. Chien-Liang Chiu & Ming-Chih Lee & Jui-Cheng Hung, 2005. "Estimation of Value-at-Risk under jump dynamics and asymmetric information," Applied Financial Economics, Taylor & Francis Journals, vol. 15(15), pages 1095-1106.
    186. 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.
    187. Dariusz Gołȩbiewski & Tomasz Barszcz & Wioletta Skrodzka & Igor Wojnicki & Andrzej Bielecki, 2022. "A New Approach to Risk Management in the Power Industry Based on Systems Theory," Energies, MDPI, vol. 15(23), pages 1-19, November.
    188. Bogdan, Dima & Ştefana Maria, Dima & Roxana, Ioan, 2022. "A Value-at-Risk forecastability indicator in the framework of a Generalized Autoregressive Score with “Asymmetric Laplace Distribution”," Finance Research Letters, Elsevier, vol. 45(C).
    189. Mauricio Zevallos, 2019. "A Note on Forecasting Daily Peruvian Stock Market VolatilityRisk Using Intraday Returns," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 42(84), pages 94-101.
    190. 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, June.
    191. Ané, Thierry & Métais, Carole, 2009. "The distribution of realized variances: Marginal behaviors, asymmetric dependence and contagion effects," International Review of Financial Analysis, Elsevier, vol. 18(3), pages 134-150, June.
    192. Zhang, Heng-Guo & Su, Chi-Wei & Song, Yan & Qiu, Shuqi & Xiao, Ran & Su, Fei, 2017. "Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model," Economic Modelling, Elsevier, vol. 67(C), pages 355-367.
    193. Ane, Thierry, 2006. "An analysis of the flexibility of Asymmetric Power GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1293-1311, November.
    194. 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.

  35. Maus, S. & Peters, H.J.M. & Storcken, A.J.A., 2004. "Minimal manipulability: anonymity and surjectivity," Research Memorandum 007, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).

    Cited by:

    1. Maus, Stefan & Peters, Hans & Storcken, Ton, 2007. "Anonymous voting and minimal manipulability," Journal of Economic Theory, Elsevier, vol. 135(1), pages 533-544, July.

  36. BEINE, Michel & LAURENT, Sébastien & PALM, Franz, 2004. "Central Bank forex interventions assessed using realized moments," LIDAM Discussion Papers CORE 2004001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Peter Andersen & Suk-Joong Kim, 2018. "Intraday Timing of AUD Intervention by the Reserve Bank of Australia: Evidence from Microstructural Analyses," World Scientific Book Chapters, in: Information Spillovers and Market Integration in International Finance Empirical Analyses, chapter 2, pages 43-71, World Scientific Publishing Co. Pte. Ltd..
    2. Michel Beine & Charles Bos & Sébastien Laurent, 2007. "The impact of Central Bank FX interventions on currency components," ULB Institutional Repository 2013/10419, ULB -- Universite Libre de Bruxelles.
    3. Suk-Joong Kim & Anh Tu Le, 2018. "Secrecy of Bank of Japan’s Yen Intervention: Evidence of Efficacy from Intra-daily Data," World Scientific Book Chapters, in: Information Spillovers and Market Integration in International Finance Empirical Analyses, chapter 4, pages 107-147, World Scientific Publishing Co. Pte. Ltd..
    4. João Barata Ribeiro Blanco Barroso, 2018. "Realized Volatility as an Instrument to Official Intervention," Investigación Conjunta-Joint Research, in: Alberto Ortiz-Bolaños (ed.), Monetary Policy and Financial Stability in Latin America and the Caribbean, edition 1, volume 1, chapter 8, pages 259-281, Centro de Estudios Monetarios Latinoamericanos, CEMLA.
    5. BEINE, Michel & LAURENT, Sébastien & PALM, Franz C., 2009. "Central bank FOREX interventions assessed using realized moments," LIDAM Reprints CORE 2135, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Georgios Chortareas & Ying Jiang & John C. Nankervis, 2013. "Volatility and Spillover Effects of Yen Interventions," Review of International Economics, Wiley Blackwell, vol. 21(4), pages 671-689, September.
    7. Kathryn M. E. Dominguez & Freyan Panthaki, 2007. "The Influence of Actual and Unrequited Interventions," Working Papers 561, Research Seminar in International Economics, University of Michigan.
    8. Michel Beine & Oscar Bernal Diaz, 2007. "Why do Central Banks intervene secretly ?preliminary evidence of the BoJ," ULB Institutional Repository 2013/10421, ULB -- Universite Libre de Bruxelles.
    9. 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.
    10. 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.
    11. Douglas, Christopher C. & Kolar, Marek, 2009. "Capturing the time dynamics of central bank intervention," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(5), pages 950-968, December.
    12. Charles S. Bos & Neil Shephard, 2004. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Economics Papers 2004-W02, Economics Group, Nuffield College, University of Oxford.
    13. Darmoul Mokhtar & Nizar Harrathi, 2007. "Monetary information arrivals and intraday exchange rate volatility: a comparison of the GARCH and the EGARCH models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00174996, HAL.
    14. 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.
    15. 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.
    16. Vithessonthi, Chaiporn, 2014. "Monetary policy and the first- and second-moment exchange rate change during the global financial crisis: Evidence from Thailand," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 29(C), pages 170-194.
    17. Morel, Christophe & Teïletche, Jérôme, 2008. "Do interventions in foreign exchange markets modify investors' expectations? The experience of Japan between 1992 and 2004," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 211-231, March.
    18. Vithessonthi, Chaiporn & Tongurai, Jittima, 2013. "Unremunerated reserve requirements, exchange rate volatility, and firm value," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 358-378.
    19. Srđan Marinković, 2014. "Non-Parametric Sign Test And Paired Samples Test Of Effectiveness Of Official Fx Intervention," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 59(202), pages 107-130, July – Se.
    20. Grossmann, Axel & Orlov, Alexei G., 2012. "Exchange rate misalignments in frequency domain," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 185-199.
    21. Vithessonthi, Chaiporn & Tongurai, Jittima, 2013. "The perils of a central bank's capital control: How substantial is the effect on firm value?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 111-135.

  37. BEINE, Michel & LAURENT, Sébastien, 2003. "Central bank interventions and jumps in double long memory models of daily exchange rates," LIDAM Reprints CORE 1706, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Oscar Bernal Diaz, 2006. "Do interactions between political authorities and central banks influence FX interventions? Evidence from Japan," DULBEA Working Papers 06-03.RS, ULB -- Universite Libre de Bruxelles.
    2. 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.
    3. Fischer, Andreas M. & Isakova, Gulzina & Termechikov, Ulanbek, 2009. "Do FX traders in Bishkek have similar perceptions to their London colleagues?: Survey evidence of market practitioners' views," Journal of Asian Economics, Elsevier, vol. 20(2), pages 98-109, March.
    4. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2017. "Can energy commodity futures add to the value of carbon assets?," Economic Modelling, Elsevier, vol. 62(C), pages 194-206.
    5. Massimiliano Caporin & Juliusz Pres, 2010. "Modelling and forecasting wind speed intensity for weather risk management," "Marco Fanno" Working Papers 0106, Dipartimento di Scienze Economiche "Marco Fanno".
    6. Bouri, Elie & Awartani, Basel & Maghyereh, Aktham, 2016. "Crude oil prices and sectoral stock returns in Jordan around the Arab uprisings of 2010," Energy Economics, Elsevier, vol. 56(C), pages 205-214.
    7. Juan Manuel Julio & Norberto Rodríguez & Hector Zárate, 2005. "Estimating the COP Exchange Rate Volatility Smile and the Market Effect of Central Bank Interventions: A CHARN Approach," Borradores de Economia 347, Banco de la Republica de Colombia.
    8. Young Wook Han, 2010. "The Effects of US Macroeconomic Surprises on the Intraday Movements of Foreign Exchange Rates: Cases of USD-EUR and USD-JPY Exchange Rates," International Economic Journal, Taylor & Francis Journals, vol. 24(3), pages 375-396.
    9. Bertholon, H. & Alain Monfort & Fulvio Pegoraro, 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    10. Bouri, Elie & Chen, Qian & Lien, Donald & Lv, Xin, 2017. "Causality between oil prices and the stock market in China: The relevance of the reformed oil product pricing mechanism," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 34-48.
    11. BEINE, Michel & LAURENT, Sébastien & PALM, Franz C., 2009. "Central bank FOREX interventions assessed using realized moments," LIDAM Reprints CORE 2135, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Kathryn M. E. Dominguez & Freyan Panthaki, 2007. "The Influence of Actual and Unrequited Interventions," Working Papers 561, Research Seminar in International Economics, University of Michigan.
    13. Bouri, Elie & Jalkh, Naji & Roubaud, David, 2019. "Commodity volatility shocks and BRIC sovereign risk: A GARCH-quantile approach," Resources Policy, Elsevier, vol. 61(C), pages 385-392.
    14. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2006. "Assessing central bank credibility during the ERM crises: Comparing option and spot market-based forecasts," Journal of Financial Stability, Elsevier, vol. 2(1), pages 28-54, April.
    15. Owen F. Humpage, 2003. "Government intervention in the foreign exchange market," Working Papers (Old Series) 0315, Federal Reserve Bank of Cleveland.
    16. Douglas, Christopher C. & Kolar, Marek, 2009. "Capturing the time dynamics of central bank intervention," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(5), pages 950-968, December.
    17. Christopher J. Neely, 2005. "An analysis of recent studies of the effect of foreign exchange intervention," Review, Federal Reserve Bank of St. Louis, vol. 87(Nov), pages 685-718.
    18. P. A. Nazarov & Kazakova, Maria, 2014. "Methodological Principles of Prediction of Tax Revenues of Budgetary System," Published Papers r90219, Russian Presidential Academy of National Economy and Public Administration.
    19. Maria Eugenia Sanin & Francesco Violante & Maria Mansanet-Bataller, 2015. "Understanding volatility dynamics in the EU-ETS market," Post-Print hal-02878047, HAL.
    20. Sang Hoon Kang & SEONG-MIN YOON, 2008. "Asymmetry and Long Memory Features in Volatility: Evidence From Korean Stock Market," Korean Economic Review, Korean Economic Association, vol. 24, pages 383-412.
    21. Kathryn M. E. Dominguez, 2003. "When Do Central Bank Interventions Influence Intra-Daily and Longer-Term Exchange Rate Movements?," Working Papers 506, Research Seminar in International Economics, University of Michigan.
    22. Osamah Al-Khazali & Elie Bouri & David Roubaud & Taisier Zoubi, 2017. "The impact of religious practice on stock returns and volatility," Post-Print hal-02008554, HAL.
    23. Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 551-565.
    24. Veiga, Helena, 2006. "Are feedback factors important in modelling financial data?," DES - Working Papers. Statistics and Econometrics. WS ws060101, Universidad Carlos III de Madrid. Departamento de Estadística.
    25. Kang, Sang Hoon & Yoon, Seong-Min, 2007. "Long memory properties in return and volatility: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 591-600.
    26. Bouri, Elie & de Boyrie, Maria E. & Pavlova, Ivelina, 2017. "Volatility transmission from commodity markets to sovereign CDS spreads in emerging and frontier countries," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 155-165.
    27. Christopher J. Neely, 2007. "Central bank authorities’ beliefs about foreign exchange intervention," Working Papers 2006-045, Federal Reserve Bank of St. Louis.
    28. Guo, Yanfeng & Wen, Xiaoqian & Wu, Yanrui & Guo, Xiumei, 2016. "How is China's coke price related with the world oil price? The role of extreme movements," Economic Modelling, Elsevier, vol. 58(C), pages 22-33.
    29. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2018. "Does oil product pricing reform increase returns and uncertainty in the Chinese stock market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 23-30.
    30. John Goddard & Enrico Onali, 2016. "Long memory and multifractality: A joint test," Papers 1601.00903, arXiv.org.
    31. Quan-Hoang Vuong, 2004. "Analyses on Gold and US Dollar in Vietnam's Transitional Economy," Working Papers CEB 04-033.RS, ULB -- Universite Libre de Bruxelles.
    32. Bouri, Elie, 2015. "Oil volatility shocks and the stock markets of oil-importing MENA economies: A tale from the financial crisis," Energy Economics, Elsevier, vol. 51(C), pages 590-598.
    33. Nikkinen, Jussi & Vähämaa, Sami, 2009. "Central bank interventions and implied exchange rate correlations," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 862-873, December.
    34. Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
    35. Bernal, Oscar & Gnabo, Jean-Yves, 2009. "Announcements, financial operations or both? Generalizing central banks' FX reaction functions," Journal of the Japanese and International Economies, Elsevier, vol. 23(4), pages 367-394, December.
    36. Mauricio Lopera Castano & Ramón Javier Mesa Callejas & Sergio Iván Restrepo Ochoa & Charle Augusto Londono Henao, 2013. "Modelando el esquema de intervenciones del tipo de cambio para Colombia. una aplicación empírica de la técnica de regresión del cuantil bajo redes neu," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, May.
    37. Junior A. Ojeda Cunya & Gabriel Rodríguez, 2016. "An application of a random level shifts model to the volatility of Peruvian stock and exchange rate returns," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 9(1), pages 34-55, March.
    38. Malinda & Maya & Jo-Hui & Chen, 2022. "Testing for the Long Memory and Multiple Structural Breaks in Consumer ETFs," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-6.
    39. López-Herrera, Francisco & Rodríguez-Nava, Abigail & Venegas-Martínez, Francisco, 2011. "Efectos en las decisiones de consumo y portafolio del riesgo cambiario con discontinuidades," Sección de Estudios de Posgrado e Investigación de la Escuela Superios de Economía del Instituto Politécnico Nacional, in: Perrotini-Hernández, Ignacio (ed.), Crecimiento y Desarrollo Económico en México, volume 1, chapter 12, pages 172-182, Escuela Superior de Economía, Instituto Politécnico Nacional.
    40. Oscar Bernal Diaz & Jean-Yves Gnabo, 2007. "Talks, financial operations or both? Generalizing central banks' FX reaction functions," DULBEA Working Papers 07-03.RS, ULB -- Universite Libre de Bruxelles.
    41. 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.
    42. Kang, Sang Hoon & Kang, Sang-Mok & Yoon, Seong-Min, 2009. "Forecasting volatility of crude oil markets," Energy Economics, Elsevier, vol. 31(1), pages 119-125, January.
    43. Chang, Jui-Chuan Della & Chang, Kuang-Liang, 2018. "The asymmetric effects of U.S. large-scale asset purchases on the volatility of the Canadian dollar futures market," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 15-28.

  38. GIOT, Pierre & LAURENT, Sébastien, 2003. "Market risk in commodity markets: a VaR approach," LIDAM Discussion Papers CORE 2003028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    2. Chiu, Yen-Chen & Chuang, I-Yuan & Lai, Jing-Yi, 2010. "The performance of composite forecast models of value-at-risk in the energy market," Energy Economics, Elsevier, vol. 32(2), pages 423-431, March.
    3. Dilip Kumar & S. Maheswaran, 2013. "Return, Volatility and Risk Spillover from Oil Prices and the US Dollar Exchange Rate to the Indian Industrial Sectors," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 7(1), pages 61-91, February.
    4. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2023. "Forecasting the Realized Volatility of Agricultural Commodity Prices: Does Sentiment Matter?," Working Papers 202316, University of Pretoria, Department of Economics.
    5. 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.
    6. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2020. "Risk quantification for commodity ETFs: Backtesting value-at-risk and expected shortfall," International Review of Financial Analysis, Elsevier, vol. 70(C).
    7. Fu, Tong & Huang, Dasen & Feng, Lingbing & Tang, Xiaoping, 2024. "More is better? The impact of predictor choice on the INE oil futures volatility forecasting," Energy Economics, Elsevier, vol. 134(C).
    8. Kulp-Tåg, Sofie, 2007. "An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions," Working Papers 526, Hanken School of Economics.
    9. Bernardina Algieri & Arturo Leccadito, 2020. "CARL and His POT: Measuring Risks in Commodity Markets," Risks, MDPI, vol. 8(1), pages 1-15, March.
    10. Degiannakis, Stavros & Potamia, Artemis, 2017. "Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 176-190.
    11. Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2019. "Forecasting Realized Volatility of Agricultural Commodities," MPRA Paper 96267, University Library of Munich, Germany.
    12. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    13. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
    14. Joëts, Marc, 2014. "Energy price transmissions during extreme movements," Economic Modelling, Elsevier, vol. 40(C), pages 392-399.
    15. Małgorzata Just & Aleksandra Łuczak, 2020. "Assessment of Conditional Dependence Structures in Commodity Futures Markets Using Copula-GARCH Models and Fuzzy Clustering Methods," Sustainability, MDPI, vol. 12(6), pages 1-22, March.
    16. Lyu, Yongjian & Wang, Peng & Wei, Yu & Ke, Rui, 2017. "Forecasting the VaR of crude oil market: Do alternative distributions help?," Energy Economics, Elsevier, vol. 66(C), pages 523-534.
    17. Degiannakis, Stavros & Dent, Pamela & Floros, Christos, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," MPRA Paper 80431, University Library of Munich, Germany.
    18. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models," MPRA Paper 53229, University Library of Munich, Germany.
    19. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    20. Naseem Al Rahahleh & Robert Kao, 2018. "Forecasting Volatility: Evidence from the Saudi Stock Market," JRFM, MDPI, vol. 11(4), pages 1-18, November.
    21. Songjiao Chen & William Wilson & Ryan Larsen & Bruce Dahl, 2016. "Risk Management for Grain Processors and “Copulas”," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(2), pages 365-382, June.
    22. Frantiv{s}ek v{C}ech & Jozef Barun'ik, 2018. "Panel quantile regressions for estimating and predicting the Value--at--Risk of commodities," Papers 1807.11823, arXiv.org.
    23. 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).
    24. Alfonso Novales & Laura Garcia-Jorcano, 2019. "Backtesting Extreme Value Theory models of expected shortfall," Documentos de Trabajo del ICAE 2019-24, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    25. Chang, Kuang-Liang, 2012. "The time-varying and asymmetric dependence between crude oil spot and futures markets: Evidence from the Mixture copula-based ARJI–GARCH model," Economic Modelling, Elsevier, vol. 29(6), pages 2298-2309.
    26. Chang, Kuang-Liang, 2012. "Volatility regimes, asymmetric basis effects and forecasting performance: An empirical investigation of the WTI crude oil futures market," Energy Economics, Elsevier, vol. 34(1), pages 294-306.
    27. Gkillas, Konstantinos & Konstantatos, Christoforos & Papathanasiou, Spyros & Wohar, Mark, 2023. "Estimation of value at risk for copper," Journal of Commodity Markets, Elsevier, vol. 32(C).
    28. Matteo Manera & Alessandro Lanza & Michael McAleer, 2004. "Modelling Dynamic Conditional Correlations in WTI Oil Forward and Futures Returns," Working Papers 2004.72, Fondazione Eni Enrico Mattei.
    29. Angelidis, Timotheos & Benos, Alexandros & Degiannakis, Stavros, 2004. "The Use of GARCH Models in VaR Estimation," MPRA Paper 96332, University Library of Munich, Germany.
    30. González-Pedraz, Carlos & Moreno, Manuel & Peña, Juan Ignacio, 2014. "Tail risk in energy portfolios," Energy Economics, Elsevier, vol. 46(C), pages 422-434.
    31. Lyu, Yongjian & Qin, Fanshu & Ke, Rui & Wei, Yu & Kong, Mengzhen, 2024. "Does mixed frequency variables help to forecast value at risk in the crude oil market?," Resources Policy, Elsevier, vol. 88(C).
    32. Timotheos Angelidis & Stavros Degiannakis, 2005. "Modeling risk for long and short trading positions," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 6(3), pages 226-238, July.
    33. Hung, Jui-Cheng & Lee, Ming-Chih & Liu, Hung-Chun, 2008. "Estimation of value-at-risk for energy commodities via fat-tailed GARCH models," Energy Economics, Elsevier, vol. 30(3), pages 1173-1191, May.
    34. Chunyang Zhou & Xiao Qin & Xundi Diao & Yingchen He, 2016. "Estimating multi-period Value at Risk of oil futures prices," Applied Economics, Taylor & Francis Journals, vol. 48(32), pages 2994-3004, July.
    35. Cheong, Chin Wen, 2009. "Modeling and forecasting crude oil markets using ARCH-type models," Energy Policy, Elsevier, vol. 37(6), pages 2346-2355, June.
    36. Amira Akl Ahmed & Doaa Akl Ahmed, 2016. "Modelling Conditional Volatility and Downside Risk for Istanbul Stock Exchange," Working Papers 1028, Economic Research Forum, revised Jul 2016.
    37. Al Janabi, Mazin A.M., 2012. "Optimal commodity asset allocation with a coherent market risk modeling," Review of Financial Economics, Elsevier, vol. 21(3), pages 131-140.
    38. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2010. "Forecasting crude oil market volatility: Further evidence using GARCH-class models," Energy Economics, Elsevier, vol. 32(6), pages 1477-1484, November.
    39. Huang, Zhuo & Liang, Fang & Wang, Tianyi & Li, Chao, 2021. "Modeling dynamic higher moments of crude oil futures," Finance Research Letters, Elsevier, vol. 39(C).
    40. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo, 2008. "Short-term predictability of crude oil markets: A detrended fluctuation analysis approach," Energy Economics, Elsevier, vol. 30(5), pages 2645-2656, September.
    41. Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018. "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, vol. 74(C), pages 628-643.
    42. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    43. Wei, Yu, 2012. "Forecasting volatility of fuel oil futures in China: GARCH-type, SV or realized volatility models?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5546-5556.
    44. 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.
    45. Timotheos Angelidis & Alexandros Benos, 2006. "Liquidity adjusted value-at-risk based on the components of the bid-ask spread," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 835-851.
    46. Tarek Bouazizi & Mongi Lassoued & Zouhaier Hadhek, 2021. "Oil Price Volatility Models during Coronavirus Crisis: Testing with Appropriate Models Using Further Univariate GARCH and Monte Carlo Simulation Models," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 281-292.
    47. Zhi-Fu Mi & Yi-Ming Wei & Bao-Jun Tang & Rong-Gang Cong & Hao Yu & Hong Cao & Dabo Guan, 2017. "Risk assessment of oil price from static and dynamic modelling approaches," CEEP-BIT Working Papers 102, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    48. Lin, Xiaoqiang & Fei, Fangyu, 2013. "Long memory revisit in Chinese stock markets: Based on GARCH-class models and multiscale analysis," Economic Modelling, Elsevier, vol. 31(C), pages 265-275.
    49. Cheng, Wan-Hsiu & Hung, Jui-Cheng, 2011. "Skewness and leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 160-173, January.
    50. Wu, Chih-Chiang & Chung, Huimin & Chang, Yu-Hsien, 2012. "The economic value of co-movement between oil price and exchange rate using copula-based GARCH models," Energy Economics, Elsevier, vol. 34(1), pages 270-282.
    51. Laura Garcia‐Jorcano & Alfonso Novales, 2021. "Volatility specifications versus probability distributions in VaR forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 189-212, March.
    52. Charfeddine, Lanouar, 2016. "Breaks or long range dependence in the energy futures volatility: Out-of-sample forecasting and VaR analysis," Economic Modelling, Elsevier, vol. 53(C), pages 354-374.
    53. Westgaard, Sjur & Fleten, Stein-Erik & Negash, Ahlmahz & Botterud, Audun & Bogaard, Katinka & Verling, Trude Haugsvaer, 2021. "Performing price scenario analysis and stress testing using quantile regression: A case study of the Californian electricity market," Energy, Elsevier, vol. 214(C).
    54. Zouheir Mighri & Raouf Jaziri, 2023. "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 41-97, March.
    55. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
    56. Rehman, Mobeen Ur & Owusu Junior, Peterson & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Time-varying risk analysis for commodity futures," Resources Policy, Elsevier, vol. 78(C).
    57. Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.
    58. Nicolas Merener, 2016. "Concentrated Production and Conditional Heavy Tails in Commodity Returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 46-65, January.
    59. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
    60. Mabrouk, Samir & Saadi, Samir, 2012. "Parametric Value-at-Risk analysis: Evidence from stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(3), pages 305-321.
    61. Angelidis, Timotheos & Degiannakis, Stavros, 2007. "Backtesting VaR Models: A Τwo-Stage Procedure," MPRA Paper 80418, University Library of Munich, Germany.
    62. Chkili, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Energy Economics, Elsevier, vol. 41(C), pages 1-18.
    63. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.
    64. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Value-at-risk methodologies for effective energy portfolio risk management," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 197-212.
    65. Zhou, Liyun & Zhang, Rixin & Huang, Jialiang, 2019. "Investor trading behavior on agricultural future prices," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 365-379.
    66. Köksal, Bülent & Orhan, Mehmet, 2012. "Market risk of developed and developing countries during the global financial crisis," MPRA Paper 37523, University Library of Munich, Germany.
    67. Samet Gunay & Audil Rashid Khaki, 2018. "Best Fitting Fat Tail Distribution for the Volatilities of Energy Futures: Gev, Gat and Stable Distributions in GARCH and APARCH Models," JRFM, MDPI, vol. 11(2), pages 1-19, June.
    68. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics.
    69. Fan, Ying & Zhang, Yue-Jun & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach," Energy Economics, Elsevier, vol. 30(6), pages 3156-3171, November.
    70. Huang, Dashan & Yu, Baimin & Fabozzi, Frank J. & Fukushima, Masao, 2009. "CAViaR-based forecast for oil price risk," Energy Economics, Elsevier, vol. 31(4), pages 511-518, July.
    71. Angelidis, Timotheos & Benos, Alexandros & Degiannakis, Stavros, 2007. "A Robust VaR Model under Different Time Periods and Weighting Schemes," MPRA Paper 80466, University Library of Munich, Germany.
    72. Haugom, Erik & Ray, Rina & Ullrich, Carl J. & Veka, Steinar & Westgaard, Sjur, 2016. "A parsimonious quantile regression model to forecast day-ahead value-at-risk," Finance Research Letters, Elsevier, vol. 16(C), pages 196-207.
    73. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Non-linear volatility dynamics and risk management of precious metals," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 183-202.
    74. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
    75. Roland Füss & Zeno Adams & Dieter G Kaiser, 2010. "The predictive power of value-at-risk models in commodity futures markets," Journal of Asset Management, Palgrave Macmillan, vol. 11(4), pages 261-285, October.
    76. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    77. Trung H. Le, 2024. "Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 402-414, March.
    78. Timotheos Angelidis & Alexandros Benos, 2008. "Value-at-Risk for Greek Stocks," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 67-104, March-Jun.
    79. Cerqueti, Roy & Giacalone, Massimiliano & Panarello, Demetrio, 2019. "A Generalized Error Distribution Copula-based method for portfolios risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 687-695.
    80. 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.
    81. 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.
    82. He, Kaijian & Lai, Kin Keung & Yen, Jerome, 2011. "Value-at-risk estimation of crude oil price using MCA based transient risk modeling approach," Energy Economics, Elsevier, vol. 33(5), pages 903-911, September.
    83. Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
    84. Auer, Benjamin R., 2014. "Daily seasonality in crude oil returns and volatilities," Energy Economics, Elsevier, vol. 43(C), pages 82-88.
    85. Derek Bunn, Arne Andresen, Dipeng Chen, Sjur Westgaard, 2016. "Analysis and Forecasting of Electricty Price Risks with Quantile Factor Models," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    86. Lyu, Yongjian & Qin, Fanshu & Ke, Rui & Yang, Mo & Chang, Jianing, 2024. "Forecasting the VaR of the crude oil market: A combination of mixed data sampling and extreme value theory," Energy Economics, Elsevier, vol. 133(C).
    87. Wong, Mei Kait, 2019. "An Analysis of the Effects of Operating Margin and Beta for Performance on Ford Motor Company," MPRA Paper 97251, University Library of Munich, Germany, revised 28 Nov 2019.
    88. Victoria Gabriela ANGHELACHE & Dumitru Cristian OANEA & Bogdan ZUGRAVU, 2013. "General Aspects Regarding the Methodology for Prediction Risk," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 61(2), pages 66-72, May.
    89. Hasanov, Akram Shavkatovich & Poon, Wai Ching & Al-Freedi, Ajab & Heng, Zin Yau, 2018. "Forecasting volatility in the biofuel feedstock markets in the presence of structural breaks: A comparison of alternative distribution functions," Energy Economics, Elsevier, vol. 70(C), pages 307-333.
    90. Qiu Lianshi, 2024. "The Relationship Between Stock Performance and Money Supply Based on VAR Model in the Context of E-commerce," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 18(1), pages 1-12.
    91. Jung-Bin Su, 2014. "How to mitigate the impact of inappropriate distributional settings when the parametric value-at-risk approach is used," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 305-325, February.
    92. Steven J. Cochran & Iqbal Mansur & Babatunde Odusami, 2016. "Conditional higher order moments in metal asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 16(1), pages 151-167, January.
    93. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2014. "Energy portfolio risk management using time-varying extreme value copula methods," Economic Modelling, Elsevier, vol. 38(C), pages 470-485.
    94. Mazin A.M. Al Janabi, 2012. "Optimal commodity asset allocation with a coherent market risk modeling," Review of Financial Economics, John Wiley & Sons, vol. 21(3), pages 131-140, September.
    95. Walid Chkili & Shawkat Hammoudeh & Duc Khuong Nguyen, 2013. "Long memory and asymmetry in the volatility of commodity markets and Basel Accord: choosing between models," Working Papers 2013-9, Department of Research, Ipag Business School.
    96. Benoît Sévi, 2014. "Forecasting the volatility of crude oil futures using intraday data," Working Papers 2014-53, Department of Research, Ipag Business School.
    97. Higgs, Helen & Lien, Gudbrand & Worthington, Andrew C., 2015. "Australian evidence on the role of interregional flows, production capacity, and generation mix in wholesale electricity prices and price volatility," Economic Analysis and Policy, Elsevier, vol. 48(C), pages 172-181.
    98. Costello, Alexandra & Asem, Ebenezer & Gardner, Eldon, 2008. "Comparison of historically simulated VaR: Evidence from oil prices," Energy Economics, Elsevier, vol. 30(5), pages 2154-2166, September.
    99. Feng, Lingbing & Rao, Haicheng & Lucey, Brian & Zhu, Yiying, 2024. "Volatility forecasting on China's oil futures: New evidence from interpretable ensemble boosting trees," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 1595-1615.
    100. F. Acebes & J. M. González-Varona & A. López-Paredes & J. Pajares, 2024. "Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    101. Morelli, Giacomo, 2023. "Stochastic ordering of systemic risk in commodity markets," Energy Economics, Elsevier, vol. 117(C).
    102. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
    103. Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," MPRA Paper 96446, University Library of Munich, Germany.
    104. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2012. "Asymmetric effects and long memory in dynamic volatility relationships between stock returns and exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 738-757.
    105. Hung, Jui-Cheng & Yi-Hsien Wang, & Chang, Matthew C. & Shih, Kuang-Hsun & Hsiu-Hsueh Kao,, 2011. "Minimum variance hedging with bivariate regime-switching model for WTI crude oil," Energy, Elsevier, vol. 36(5), pages 3050-3057.
    106. Wang, Yudong & Wu, Chongfeng & Wei, Yu, 2011. "Can GARCH-class models capture long memory in WTI crude oil markets?," Economic Modelling, Elsevier, vol. 28(3), pages 921-927, May.
    107. Marc Joëts, 2012. "Energy price transmissions during extreme movements," Working Papers hal-04141047, HAL.
    108. Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
    109. de Araújo, André da Silva & Garcia, Maria Teresa Medeiros, 2013. "Risk contagion in the north-western and southern European stock markets," Journal of Economics and Business, Elsevier, vol. 69(C), pages 1-34.
    110. Enrique Molina‐Muñoz & Andrés Mora‐Valencia & Javier Perote, 2021. "Backtesting expected shortfall for world stock index ETFs with extreme value theory and Gram–Charlier mixtures," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4163-4189, July.
    111. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2011. "A copula–multifractal volatility hedging model for CSI 300 index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4260-4272.
    112. López Cabrera, Brenda & Schulz, Franziska, 2016. "Time-adaptive probabilistic forecasts of electricity spot prices with application to risk management," SFB 649 Discussion Papers 2016-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    113. Chevallier, Julien & Ielpo, Florian, 2017. "Investigating the leverage effect in commodity markets with a recursive estimation approach," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 763-778.
    114. Chang, Ting-Huan & Su, Hsin-Mei & Chiu, Chien-Liang, 2011. "Value-at-risk estimation with the optimal dynamic biofuel portfolio," Energy Economics, Elsevier, vol. 33(2), pages 264-272, March.
    115. Prachi Jain & Debasish Maitra, 2025. "Commodity Price Crash Risk and Crash Risk Contagion," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(4), pages 343-378, April.
    116. Dariusz Gołȩbiewski & Tomasz Barszcz & Wioletta Skrodzka & Igor Wojnicki & Andrzej Bielecki, 2022. "A New Approach to Risk Management in the Power Industry Based on Systems Theory," Energies, MDPI, vol. 15(23), pages 1-19, November.
    117. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    118. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    119. Liao, Huei-Chu & Lee, Yi-Huey & Suen, Yu-Bo, 2008. "Electronic trading system and returns volatility in the oil futures market," Energy Economics, Elsevier, vol. 30(5), pages 2636-2644, September.
    120. Kostas Andriosopoulos & Nikos Nomikos, 2012. "Risk management in the energy markets and Value-at-Risk modelling: a Hybrid approach," RSCAS Working Papers 2012/47, European University Institute.
    121. Kang, Sang Hoon & Kang, Sang-Mok & Yoon, Seong-Min, 2009. "Forecasting volatility of crude oil markets," Energy Economics, Elsevier, vol. 31(1), pages 119-125, January.

  39. BEINE, Michel & LAURENT, Sébastien & LECOURT, Christelle, 2003. "Official central bank interventions and exchange rate volatility: Evidence from a regime-switching analysis," LIDAM Reprints CORE 1705, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Michel Beine & Christelle Lecourt, 2004. "Reported and secret interventions in the foreign exchange market," ULB Institutional Repository 2013/10427, ULB -- Universite Libre de Bruxelles.
    2. Alberto Humala & Gabriel Rodriguez, 2010. "Foreign exchange intervention and exchange rate volatility in Peru," Applied Economics Letters, Taylor & Francis Journals, vol. 17(15), pages 1485-1491.
    3. Gabriele Galati & Patrick C. Higgins & Owen F. Humpage & William R. Melick, 2006. "Option prices, exchange market intervention, and the higher moment expectations channel: a user’s guide," Working Papers (Old Series) 0618, Federal Reserve Bank of Cleveland.
    4. Michel Beine & Charles Bos & Sébastien Laurent, 2007. "The impact of Central Bank FX interventions on currency components," ULB Institutional Repository 2013/10419, ULB -- Universite Libre de Bruxelles.
    5. Beine, Michel, 2004. "Conditional covariances and direct central bank interventions in the foreign exchange markets," Journal of Banking & Finance, Elsevier, vol. 28(6), pages 1385-1411, June.
    6. Jaqueline Terra Moura Marins & Gustavo Silva Araujo & José Valentim Machado Vicente, 2015. "As Atuações Cambiais do Banco Central Afetam as Expectativas de Mercado?," Working Papers Series 393, Central Bank of Brazil, Research Department.
    7. 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.
    8. Lukas Menkhoff, 2008. "High-Frequency Analysis of Foreign Exchange Interventions: What do we learn?," CESifo Working Paper Series 2473, CESifo.
    9. Pami Dua & Ritu Suri, 2019. "Interlinkages Between USD–INR, EUR–INR, GBP–INR and JPY–INR Exchange Rate Markets and the Impact of RBI Intervention," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(1_suppl), pages 102-136, April.
    10. Michel Beine & Agnes Bénassy-Quéré & Ronald MacDonald, 2007. "The impact of Central Bank intervention on exchange rate forecasts heterogeneity," ULB Institutional Repository 2013/10423, ULB -- Universite Libre de Bruxelles.
    11. Fratzscher, Marcel, 2008. "Communication and exchange rate policy," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1651-1672, December.
    12. Jara, Alejandro & Piña, Marco, 2023. "Exchange rate volatility and the effectiveness of FX interventions: The case of Chile," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
    13. Michel Beine & Paul De Grauwe & Marianna Grimaldi, 2008. "The impact of FX Central Bank Intervention in a Noise Trading Framework," DEM Discussion Paper Series 08-15, Department of Economics at the University of Luxembourg.
    14. Smita Roy Trivedi & P. G. Apte, 2016. "Central Bank Intervention in USD/INR Market: Estimating Its Reaction Function and Impact on Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 23(3), pages 263-279, September.
    15. Соломія Бричка & Денис Клиновський & Дмитро Круковець & Артем Огарков, 2019. "Мета-аналіз: ефект fx-інтервенцій на валютний курс," Suchasni ekonomichni doslidzhennja, Kyiv School of Economics, vol. 2(1), pages 24-47.
    16. BEINE, Michel & LAURENT, Sébastien & PALM, Franz C., 2009. "Central bank FOREX interventions assessed using realized moments," LIDAM Reprints CORE 2135, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Rasmus Fatum, 2005. "Daily Effects of Foreign Exchange Intervention: Evidence from Official Bank of Canada Data," EPRU Working Paper Series 05-07, Economic Policy Research Unit (EPRU), University of Copenhagen. Department of Economics.
    18. Georgios Chortareas & Ying Jiang & John C. Nankervis, 2013. "Volatility and Spillover Effects of Yen Interventions," Review of International Economics, Wiley Blackwell, vol. 21(4), pages 671-689, September.
    19. Kathryn M. E. Dominguez & Freyan Panthaki, 2007. "The Influence of Actual and Unrequited Interventions," Working Papers 561, Research Seminar in International Economics, University of Michigan.
    20. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2006. "Assessing central bank credibility during the ERM crises: Comparing option and spot market-based forecasts," Journal of Financial Stability, Elsevier, vol. 2(1), pages 28-54, April.
    21. Lee, Hsiu-Yun, 2011. "Nonlinear exchange rate dynamics under stochastic official intervention," Economic Modelling, Elsevier, vol. 28(4), pages 1510-1518, July.
    22. Abdul Rishad & Sanjeev Gupta & Akhil Sharma, 2021. "Official Intervention and Exchange Rate Determination: Evidence from India," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 13(3), pages 357-379, September.
    23. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2014. "Understanding the Impact of Monetary Policy Shocks on the Corporate Bond Market in Good and Bad Times: A Markov Switching Model," BAFFI CAREFIN Working Papers 1623, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    24. Roy Trivedi, Smita, 2018. "Exchange rate volatility: Trader's beliefs and the role of news," MPRA Paper 89330, University Library of Munich, Germany.
    25. Khemiri, Rim & Ali, Mohamed Sami Ben, 2013. "Exchange rate pass-through and inflation dynamics in Tunisia: A Markov-switching approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 7, pages 1-30.
    26. Richard D. F. Harris & Murat Mazibas, 2022. "A component Markov regime‐switching autoregressive conditional range model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 650-683, April.
    27. Gravelle, Toni & Kichian, Maral & Morley, James, 2006. "Detecting shift-contagion in currency and bond markets," Journal of International Economics, Elsevier, vol. 68(2), pages 409-423, March.
    28. Chmelarova, Viera & Schnabl, Gunther, 2006. "Exchange rate stabilization in developed and underdeveloped capital markets," Working Paper Series 636, European Central Bank.
    29. Mark Trede & Bernd Wilfling, 2007. "Estimating exchange rate dynamics with diffusion processes: an application to Greek EMU data," Empirical Economics, Springer, vol. 33(1), pages 23-39, July.
    30. Thomas Chuffart & Emmanuel Flachaire & Anne Péguin-Feissolle, 2017. "Testing for misspecification in the short-run component of GARCH-type models," Post-Print hal-03157205, HAL.
    31. Kathryn M. E. Dominguez, 2003. "When Do Central Bank Interventions Influence Intra-Daily and Longer-Term Exchange Rate Movements?," Working Papers 506, Research Seminar in International Economics, University of Michigan.
    32. Solomiia Brychka & Denys Klynovskyi & Dmytro Krukovets & Artem Oharkov, 2019. "Meta-Analysis: Meta-Analysis: Effect of FX interventions on the exchange rate," Modern Economic Studies, Kyiv School of Economics, vol. 2(1), pages 24-44.
    33. Liu, Yue & Tian, Lixin & Sun, Huaping & Zhang, Xiling & Kong, Chuimin, 2022. "Option pricing of carbon asset and its application in digital decision-making of carbon asset," Applied Energy, Elsevier, vol. 310(C).
    34. Morel, Christophe & Teïletche, Jérôme, 2008. "Do interventions in foreign exchange markets modify investors' expectations? The experience of Japan between 1992 and 2004," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 211-231, March.
    35. Artem Prokhorov, 2008. "Nonlinear dynamics and chaos theory in economics: a historical perspective (in Russian)," Quantile, Quantile, issue 4, pages 79-92, March.
    36. Quan-Hoang Vuong, 2004. "Analyses on Gold and US Dollar in Vietnam's Transitional Economy," Working Papers CEB 04-033.RS, ULB -- Universite Libre de Bruxelles.
    37. Hasan Murat Ertugrul & Huseyin Ozturk, 2013. "The Drivers of Credit Default Swap Prices: Evidence from Selected Emerging Market Countries," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S5), pages 228-249, November.
    38. Nikkinen, Jussi & Vähämaa, Sami, 2009. "Central bank interventions and implied exchange rate correlations," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 862-873, December.
    39. Bernal, Oscar & Gnabo, Jean-Yves, 2009. "Announcements, financial operations or both? Generalizing central banks' FX reaction functions," Journal of the Japanese and International Economies, Elsevier, vol. 23(4), pages 367-394, December.
    40. Mr. Aleš Bulíř, 2004. "Liberalized Markets Have More Stable Exchange Rates: Short-Run Evidence From Four Transition Countries," IMF Working Papers 2004/035, International Monetary Fund.
    41. Lee, Hsiu-Yun & Lai, Hung-Pin, 2011. "A structural threshold model of the exchange rate under optimal intervention," Journal of International Money and Finance, Elsevier, vol. 30(6), pages 931-946, October.
    42. Hoshikawa, Takeshi, 2008. "The effect of intervention frequency on the foreign exchange market: The Japanese experience," Journal of International Money and Finance, Elsevier, vol. 27(4), pages 547-559, June.
    43. Suardi, Sandy, 2008. "Central bank intervention, threshold effects and asymmetric volatility: Evidence from the Japanese yen-US dollar foreign exchange market," Economic Modelling, Elsevier, vol. 25(4), pages 628-642, July.
    44. Pippenger, John, 2018. "Forward Bias, Uncovered Interest Parity and Related Puzzles," University of California at Santa Barbara, Economics Working Paper Series qt2cm6p186, Department of Economics, UC Santa Barbara.
    45. Eria Hisali, 2012. "The Efficacy Of Central Bank Intervention On The Foreign Exchange Market: Uganda'S Experience," Journal of International Development, John Wiley & Sons, Ltd., vol. 24(2), pages 185-207, March.
    46. Liu, Yue & Sun, Huaping & Zhang, Jijian & Taghizadeh-Hesary, Farhad, 2020. "Detection of volatility regime-switching for crude oil price modeling and forecasting," Resources Policy, Elsevier, vol. 69(C).
    47. Christelle Lecourt & Helene Raymond, 2006. "Central bank interventions in industrialized countries: a characterization based on survey results," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(2), pages 123-138.
    48. Sandun Perera & Winston Buckley & Hongwei Long, 2018. "Market-reaction-adjusted optimal central bank intervention policy in a forex market with jumps," Annals of Operations Research, Springer, vol. 262(1), pages 213-238, March.
    49. Grossmann, Axel & Orlov, Alexei G., 2012. "Exchange rate misalignments in frequency domain," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 185-199.
    50. Oscar Bernal Diaz & Jean-Yves Gnabo, 2007. "Talks, financial operations or both? Generalizing central banks' FX reaction functions," DULBEA Working Papers 07-03.RS, ULB -- Universite Libre de Bruxelles.
    51. P. Fulya Gebeşoğlu & Hasan Murat Ertuğrul, 2014. "GDP Volatility Spillovers from the US and EU to Turkey: A Dynamic Investigation," Ekonomi-tek - International Economics Journal, Turkish Economic Association, vol. 3(2), pages 51-66, May.
    52. Smita Roy Trivedi, 2020. "The Moses effect: can central banks really guide foreign exchange markets?," Empirical Economics, Springer, vol. 58(6), pages 2837-2865, June.
    53. 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.

  40. BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen, 2003. "Multivariate GARCH models: a survey," LIDAM Discussion Papers CORE 2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Michele Leonardo Bianchi & Federica Pallante, 2025. "Comparing the systemic risk of Italian insurers and banks," Questioni di Economia e Finanza (Occasional Papers) 922, Bank of Italy, Economic Research and International Relations Area.
    2. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    3. Hautsch, Nikolaus & Kyj, Lada. M. & Malec, Peter, 2013. "Do high-frequency data improve high-dimensional portfolio allocations?," SFB 649 Discussion Papers 2013-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Park, Sung Y. & Bera, Anil K., 2009. "Maximum entropy autoregressive conditional heteroskedasticity model," Journal of Econometrics, Elsevier, vol. 150(2), pages 219-230, June.
    5. Oberndorfer, Ulrich, 2008. "EU Emission Allowances and the Stock Market: Evidence from the Electricity Industry," ZEW Discussion Papers 08-059, ZEW - Leibniz Centre for European Economic Research.
    6. Kyritsis, Evangelos & Serletis, Apostolos, 2017. "The Zero Lower Bound and Market Spillovers: Evidence from the G7 and Norway," Discussion Papers 2017/7, Norwegian School of Economics, Department of Business and Management Science.
    7. Faruk, Balli & Syed Abul, Basher & Hassan, Ghassan & Hassan, Hajhoj, 2015. "An Analysis of Returns and Volatility Spillovers and their Determinants in Emerging Asian and Middle Eastern Countries," MPRA Paper 63847, University Library of Munich, Germany.
    8. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2010. "On the Forecasting Accuracy of Multivariate GARCH Models," Cahiers de recherche 1021, CIRPEE.
    9. Ajay Singh & Dinghai Xu, 2016. "Random matrix application to correlations amongst the volatility of assets," Quantitative Finance, Taylor & Francis Journals, vol. 16(1), pages 69-83, January.
    10. Fuentes Vélez, Mariana & Pinilla Barrera, Alejandro, 2021. "Transmisión de volatilidad en el Mercado Integrado Latinoamericano (MILA): una evidencia del grado de integración. || Transmission of volatility in the Latin American Integrated Market (MILA): evidenc," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 31(1), pages 301-328, June.
    11. Joanna Olbrys, 2013. "Price and Volatility Spillovers in the Case of Stock Markets Located in Different Time Zones," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S2), pages 145-157, March.
    12. Crawley, Andrew & Welch, Sarah & Yung, Julieta, 2021. "Improving estimates of job matching efficiency with different measures of unemployment," Journal of Macroeconomics, Elsevier, vol. 67(C).
    13. Sbrana, Giacomo & Poloni, Federico, 2013. "A closed-form estimator for the multivariate GARCH(1,1) model," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 152-162.
    14. Peter Boswijk, H. & van der Weide, Roy, 2011. "Method of moments estimation of GO-GARCH models," Journal of Econometrics, Elsevier, vol. 163(1), pages 118-126, July.
    15. Cornelis Gardebroek & Manuel A. Hernandez & Miguel Robles, 2016. "Market interdependence and volatility transmission among major crops," Agricultural Economics, International Association of Agricultural Economists, vol. 47(2), pages 141-155, March.
    16. 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.
    17. Zexuan Yin & Paolo Barucca, 2022. "Neural Generalised AutoRegressive Conditional Heteroskedasticity," Papers 2202.11285, arXiv.org.
    18. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    19. 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.
    20. M. Raddant & T. Di Matteo, 2023. "A Look at Financial Dependencies by Means of Econophysics and Financial Economics," Papers 2302.08208, arXiv.org.
    21. Francq, Christian & Zakoian, Jean-Michel, 2014. "Estimating multivariate GARCH and stochastic correlation models equation by equation," MPRA Paper 54250, University Library of Munich, Germany.
    22. Alexander Aue & Lajos Horváth & Daniel F. Pellatt, 2017. "Functional Generalized Autoregressive Conditional Heteroskedasticity," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 3-21, January.
    23. Ángel López-Oriona & José A. Vilar, 2021. "F4: An All-Purpose Tool for Multivariate Time Series Classification," Mathematics, MDPI, vol. 9(23), pages 1-26, November.
    24. Seyed Mehrzad Asaad Sajadi & Pouya Khodaee & Ehsan Hajizadeh & Sabri Farhadi & Sohaib Dastgoshade & Bo Du, 2022. "Deep Learning-Based Methods for Forecasting Brent Crude Oil Return Considering COVID-19 Pandemic Effect," Energies, MDPI, vol. 15(21), pages 1-23, October.
    25. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    26. GIOT, Pierre & LAURENT, Sébastien, 2003. "Value-at-Risk for long and short trading positions," LIDAM Reprints CORE 1707, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    27. Andrea Silvestrini & David Veredas, 2008. "Temporal Aggregation Of Univariate And Multivariate Time Series Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(3), pages 458-497, July.
    28. Marno Verbeek & Jeroen VK Rombouts, 2005. "Evaluating Portfolio Value-at-Risk using Semi-Parametric GARCH Models," Computing in Economics and Finance 2005 40, Society for Computational Economics.
    29. Algieri, Bernardina, 2014. "The influence of biofuels, economic and financial factors on daily returns of commodity futures prices," Energy Policy, Elsevier, vol. 69(C), pages 227-247.
    30. Drew Creal & Siem Jan Koopman & André Lucas, 2011. "A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 552-563, October.
    31. Allen, David & Lizieri, Colin & Satchell, Stephen, 2020. "A comparison of non-Gaussian VaR estimation and portfolio construction techniques," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 356-368.
    32. Henryk Gurgul & Robert Syrek, 2023. "Contagion between selected European indexes during the Covid-19 pandemic," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(1), pages 47-59.
    33. Tejeda, Hernan A. & Goodwin, Barry K. & Pelletier, Denis, 2009. "A State Dependent Regime Switching Model of Dynamic Correlations," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49370, Agricultural and Applied Economics Association.
    34. Rasmus Søndergaard Pedersen & Anders Rahbek, 2012. "Multivariate Variance Targeting in the BEKK-GARCH Model," Discussion Papers 12-23, University of Copenhagen. Department of Economics.
    35. Haniff, Mohd Nizal & Pok, Wee Ching, 2010. "Intraday volatility and periodicity in the Malaysian stock returns," Research in International Business and Finance, Elsevier, vol. 24(3), pages 329-343, September.
    36. Kurose, Yuta & Omori, Yasuhiro, 2016. "Dynamic equicorrelation stochastic volatility," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 795-813.
    37. Aboura, Sofiane & Chevallier, Julien, 2015. "Volatility returns with vengeance: Financial markets vs. commodities," Research in International Business and Finance, Elsevier, vol. 33(C), pages 334-354.
    38. Karl Oton Rudolf & Samer Ajour El Zein & Nicola Jackman Lansdowne, 2021. "Bitcoin as an Investment and Hedge Alternative. A DCC MGARCH Model Analysis," Risks, MDPI, vol. 9(9), pages 1-22, August.
    39. Hafner, Christian & Reznikova, Olga, 2010. "Efficient estimation of a semiparametric dynamic copula model," LIDAM Reprints ISBA 2010033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    40. Mehmet Balcilar & NICO KATZKE & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 15-05, Eastern Mediterranean University, Department of Economics.
    41. Gu, Huaying & Liu, Zhixue & Weng, Yingliang, 2017. "Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 460-472.
    42. Yegnanew A. Shiferaw, 2019. "Multivariate Analysis of East African Currency Exchange Rate Dynamics," Annals of Economics and Finance, Society for AEF, vol. 20(2), pages 587-610, November.
    43. Manabu Asai & Michael McAleer, 2011. "Dynamic Conditional Correlations for Asymmetric Processes," Documentos de Trabajo del ICAE 2011-30, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    44. Haoren Zhu & Pengfei Zhao & Wilfred Siu Hung NG & Dik Lun Lee, 2024. "Financial Assets Dependency Prediction Utilizing Spatiotemporal Patterns," Papers 2406.11886, arXiv.org.
    45. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
    46. Hecq Alain & Laurent Sébastien & Palm Franz C., 2016. "On the Univariate Representation of BEKK Models with Common Factors," Journal of Time Series Econometrics, De Gruyter, vol. 8(2), pages 91-113, July.
    47. Andrew J. Patton, 2009. "Are "Market Neutral" Hedge Funds Really Market Neutral?," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2295-2330, July.
    48. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2013. "Estimation and Inference in Univariate and Multivariate Log-GARCH-X Models When the Conditional Density is Unknown," MPRA Paper 49344, University Library of Munich, Germany.
    49. Kasper Johansson & Mehmet Giray Ogut & Markus Pelger & Thomas Schmelzer & Stephen Boyd, 2023. "A Simple Method for Predicting Covariance Matrices of Financial Returns," Papers 2305.19484, arXiv.org, revised Nov 2023.
    50. Vozlyublennaia, Nadia & Meshcheryakov, Artem, 2014. "Dynamic correlation structure and security risk," Journal of Economics and Business, Elsevier, vol. 73(C), pages 48-64.
    51. 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.
    52. Jacek Osiewalski & Krzysztof Osiewalski, 2016. "Hybrid MSV-MGARCH Models – General Remarks and the GMSF-SBEKK Specification," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(4), pages 241-271, December.
    53. Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
    54. Weber, Enzo, 2008. "Simultaneous stochastic volatility transmission across American equity markets," SFB 649 Discussion Papers 2008-049, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    55. Nabil Maghrebi & Mark J. Holmes & Eric J. Pentecost, 2006. "Are There Asymmetries in the Relationship Between Exchange Rate Fluctuations and Stock Market Volatility in Pacific Basin Countries?," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 229-256.
    56. Chen, Yufeng & Zheng, Biao & Qu, Fang, 2020. "Modeling the nexus of crude oil, new energy and rare earth in China: An asymmetric VAR-BEKK (DCC)-GARCH approach," Resources Policy, Elsevier, vol. 65(C).
    57. Philippe Charlot & Olivier Darné & Zakaria Moussa, 2014. "Commodity returns co-movements: Fundamentals or "style" effect?," Working Papers hal-01093631, HAL.
    58. Maki, Daiki, 2015. "Wild bootstrap testing for cointegration in an ESTAR error correction model," Economic Modelling, Elsevier, vol. 47(C), pages 292-298.
    59. Cui, Xueting & Zhu, Shushang & Sun, Xiaoling & Li, Duan, 2013. "Nonlinear portfolio selection using approximate parametric Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2124-2139.
    60. Lukanima, Benedicto Kulwizira & Sanchez-Barrios, Luis Javier & Gómez-Bravo, Yuli Paola, 2024. "Towards understanding MILA stock markets integration beyond MILA: New evidence between the pre-Global financial crisis and the COVID19 periods," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 478-497.
    61. Fotis Papailias & Dimitrios Thomakos, 2015. "Covariance averaging for improved estimation and portfolio allocation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 29(1), pages 31-59, February.
    62. Noureddine Benlagha, 2014. "Volatility Linkage of Nominal and Index-linked Bond Returns: A Multivariate BEKK-GARCH Approach," Review of Economics & Finance, Better Advances Press, Canada, vol. 4, pages 49-60, November.
    63. Bakhtiar, Tiam & Luo, Xiaojun & Adelopo, Ismail, 2023. "Network effects and store-of-value features in the cryptocurrency market," Technology in Society, Elsevier, vol. 74(C).
    64. Ralf Brüggemann & Carsten Jentsch & Carsten Trenkler, 2014. "Inference in VARs with Conditional Heteroskedasticity of Unknown Form," Working Paper Series of the Department of Economics, University of Konstanz 2014-13, Department of Economics, University of Konstanz.
    65. Gao, Guangyuan & Ho, Kin-Yip & Shi, Yanlin, 2020. "Long memory or regime switching in volatility? Evidence from high-frequency returns on the U.S. stock indices," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    66. Nikolaos Antonakakis & Rangan Gupta & Christos Kollias & Stephanos Papadamou, 2017. "Geopolitical Risks and the Oil-Stock Nexus Over 1899-2016," Working Papers 201702, University of Pretoria, Department of Economics.
    67. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).
    68. Rizvi, Syed Aun R. & Arshad, Shaista, 2017. "Analysis of the efficiency–integration nexus of Japanese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 296-308.
    69. Markus Bibinger & Jun Yu & Chen Zhang, 2025. "Modeling and Forecasting Realized Volatility with Multivariate Fractional Brownian Motion," Working Papers 202528, University of Macau, Faculty of Business Administration.
    70. Mark J. Jensen & John M. Maheu, 2012. "Bayesian Semiparametric Multivariate GARCH Modeling," Working Paper series 48_12, Rimini Centre for Economic Analysis.
    71. Costas Karfakis & Theodore Panagiotidis, 2015. "The effects of global monetary policy and Greek debt crisis on the dynamic conditional correlations of currency markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(4), pages 795-811, November.
    72. Tsuji, Chikashi, 2020. "Correlation and spillover effects between the US and international banking sectors: New evidence and implications for risk management," International Review of Financial Analysis, Elsevier, vol. 70(C).
    73. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
    74. Neslihan Fidan Keçeci & Viktor Kuzmenko & Stan Uryasev, 2016. "Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios," JRFM, MDPI, vol. 9(4), pages 1-14, October.
    75. Jiang, Wei & Hu, Yanhui & Zhao, Xiangyu, 2025. "The impact of artificial intelligence on carbon market in China: Evidence from quantile-on-quantile regression approach," Technological Forecasting and Social Change, Elsevier, vol. 212(C).
    76. Henri Audigé, 2013. "A new approach of contagion based on smooth transition conditional correlation GARCH models: An empirical application to the Greek crisis," EconomiX Working Papers 2013-2, University of Paris Nanterre, EconomiX.
    77. Colavecchio, Roberta & Funke, Michael, 2008. "Volatility transmissions between renminbi and Asia-Pacific on-shore and off-shore U.S. dollar futures," China Economic Review, Elsevier, vol. 19(4), pages 635-648, December.
    78. Theis Lange, 2009. "First and second order non-linear cointegration models," CREATES Research Papers 2009-04, Department of Economics and Business Economics, Aarhus University.
    79. Michael McAleer & David Allen & Ron Amram, 2011. "Volatility Spillovers from the Chinese Stock Market to Economic Neighbours," KIER Working Papers 805, Kyoto University, Institute of Economic Research.
    80. Adams, Zeno & Füss, Roland & Glück, Thorsten, 2017. "Are correlations constant? Empirical and theoretical results on popular correlation models in finance," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 9-24.
    81. Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-953, CIRJE, Faculty of Economics, University of Tokyo.
    82. Jin Guo & Tetsuji Tanaka, 2019. "Determinants of international price volatility transmissions: the role of self-sufficiency rates in wheat-importing countries," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-13, December.
    83. Lehkonen, Heikki & Heimonen, Kari, 2014. "Timescale-dependent stock market comovement: BRICs vs. developed markets," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 90-103.
    84. Koulakiotis, Athanasios & Kartalis, Nikos & Lyroudi, Katerina & Papasyriopoulos, Nicholas, 2012. "Asymmetric and threshold effects on comovements among Germanic cross-listed equities," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 327-342.
    85. Matteo Barigozzi & Marc Hallin, 2014. "Generalized Dynamic Factor Models and Volatilities. Recovering the Market Volatility Shocks," Working Papers ECARES ECARES 2014-52, ULB -- Universite Libre de Bruxelles.
    86. Irfan Akbar Kazi & Suzanne Salloy, 2014. "Dynamics in the correlations of the Credit Default Swaps’ G14 dealers: Are there any contagion effects due to Lehman Brothers’ bankruptcy and the global financial crisis?," Working Papers 2014-237, Department of Research, Ipag Business School.
    87. Stelios D. Bekiros, 2013. "Decoupling and the Spillover Effects of the US Financial Crisis: Evidence from the BRIC Markets," Working Paper series 21_13, Rimini Centre for Economic Analysis.
    88. 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.
    89. Laurini, Márcio Poletti & Mauad, Roberto Baltieri & Aiube, Fernando Antônio Lucena, 2020. "The impact of co-jumps in the oil sector," Research in International Business and Finance, Elsevier, vol. 52(C).
    90. Pedro Godinho & Pedro Cerqueira, 2018. "The Impact of Expectations, Match Importance, and Results in the Stock Prices of European Football Teams," Journal of Sports Economics, , vol. 19(2), pages 230-278, February.
    91. 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.
    92. Serge Darolles & Christian Francq & Sebastien Laurent, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-04590180, HAL.
    93. Alessio Ciarlone & Andrea Colabella, 2018. "Asset price volatility in EU-6 economies: how large is the role played by the ECB?," Temi di discussione (Economic working papers) 1175, Bank of Italy, Economic Research and International Relations Area.
    94. Jacek Osiewalski & Anna Pajor, 2009. "Bayesian Analysis for Hybrid MSF-SBEKK Models of Multivariate Volatility," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(2), pages 179-202, November.
    95. Cheung, Yin-Wong & Chung, Sang-Kuck, 2009. "A Long Memory Model with Mixed Normal GARCH for US Inflation Data," Santa Cruz Department of Economics, Working Paper Series qt94r403d2, Department of Economics, UC Santa Cruz.
    96. Hafner, C.M. & Rombouts, J.V.K., 2004. "Semiparametric multivariate volatility models," Econometric Institute Research Papers EI 2004-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    97. 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.
    98. Van Cauwenberge, Annelies & Vancauteren, Mark & Braekers, Roel & Vandemaele, Sigrid, 2019. "International trade, foreign direct investments, and firms’ systemic risk : Evidence from the Netherlands," Economic Modelling, Elsevier, vol. 81(C), pages 361-386.
    99. Tsuji, Chikashi, 2018. "New DCC analyses of return transmission, volatility spillovers, and optimal hedging among oil futures and oil equities in oil-producing countries," Applied Energy, Elsevier, vol. 229(C), pages 1202-1217.
    100. Belke, Ansgar & Gokus, Christian, 2011. "Volatility Patterns of CDS, Bond and Stock Markets Before and During the Financial Crisis – Evidence from Major Financial Institutions," Ruhr Economic Papers 243, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    101. Tule, Moses K. & Ndako, Umar B. & Onipede, Samuel F., 2017. "Oil price shocks and volatility spillovers in the Nigerian sovereign bond market," Review of Financial Economics, Elsevier, vol. 35(C), pages 57-65.
    102. Roman Horvath & Dragan Petrovski, 2012. "International Stock Market Integration : Central and South Eastern Europe Compared," Working Papers 317, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
    103. Jean Marcelin B. Brou & Mbodja Mougoué & Eugene Kouassi & Kebaabetswe Thulaganyo & Benjamin K. Acquah, 2022. "Effects of diamond price volatility on stock returns: Evidence from a developing economy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1025-1043, January.
    104. Caporin, M. & McAleer, M.J., 2013. "Ten Things You Should Know About DCC," Econometric Institute Research Papers EI 2013-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    105. Juan Pablo Domínguez H., 2007. "Cost of Equity Capital and Country Risk: An econometric analysis of the expected rate of return for four Latin American countries," Economía, Instituto de Investigaciones Económicas y Sociales (IIES). Facultad de Ciencias Económicas y Sociales. Universidad de Los Andes. Mérida, Venezuela, vol. 32(23), pages 63-90, january-j.
    106. Luiz De Mello & Diego Moccero, 2009. "Monetary Policy and Inflation Expectations in Latin America: Long‐Run Effects and Volatility Spillovers," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(8), pages 1671-1690, December.
    107. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    108. Manuel Hernandez & Raul Ibarra & Danilo Trupkin, 2011. "How far do shocks move across borders?Examining volatility transmission in major agricultural futures markets," Documentos de Trabajo/Working Papers 1109, Facultad de Ciencias Empresariales y Economia. Universidad de Montevideo..
    109. M. Hakan Eratalay; Evgenii V. Vladimirov, 2018. "Mapping The Stocks In Micex: Who Is Central To The Moscow Stock Exchange?," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 111, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    110. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    111. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    112. Javier Sánchez García & Salvador Cruz Rambaud, 2022. "A GARCH approach to model short‐term interest rates: Evidence from Spanish economy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1621-1632, April.
    113. Joanna Olbrys, 2013. "Asymmetric impact of innovations on volatility in the case of the US and CEEC-3 markets: EGARCH based approach," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 13, pages 33-50.
    114. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    115. Grydaki, Maria & Bezemer, Dirk J., 2012. "The Role of Credit in Great Moderation: a Multivariate GARCH Approach," MPRA Paper 39813, University Library of Munich, Germany.
    116. Roengchai Tansuchat & Chia-Lin Chang & Michael McAleer, 2010. "Conditional Correlations and Volatility Spillovers Between Crude Oil and Stock Index Returns," CIRJE F-Series CIRJE-F-706, CIRJE, Faculty of Economics, University of Tokyo.
    117. 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.
    118. Koenig, P., 2011. "Modelling Correlation in Carbon and Energy Markets," Cambridge Working Papers in Economics 1123, Faculty of Economics, University of Cambridge.
    119. Chow, William W. & Fung, Michael K., 2008. "Volatility of stock price as predicted by patent data: An MGARCH perspective," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 64-79, January.
    120. Piero Mazzarisi & Fabrizio Lillo & Stefano Marmi, 2018. "When panic makes you blind: a chaotic route to systemic risk," Papers 1805.00785, arXiv.org.
    121. Vo, Minh T., 2009. "Regime-switching stochastic volatility: Evidence from the crude oil market," Energy Economics, Elsevier, vol. 31(5), pages 779-788, September.
    122. Sadýk Cukur & Yusuf Volkan Topuz, 2005. "Exchange Rate Exposure: An Empirical Application for Textile Industry on the Istanbul Stock Exchange," Istanbul Stock Exchange Review, Research and Business Development Department, Borsa Istanbul, vol. 8(30), pages 19-30.
    123. 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.
    124. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    125. Christian Dreger & Jarko Fidrmuc & Konstantin Kholodilin & Dirk Ulbricht, 2015. "The Ruble between the Hammer and the Anvil: Oil Prices and Economic Sanctions," Discussion Papers of DIW Berlin 1488, DIW Berlin, German Institute for Economic Research.
    126. de Oliveira, Felipe A. & Maia, Sinézio F. & de Jesus, Diego P. & Besarria, Cássio da N., 2018. "Which information matters to market risk spreading in Brazil? Volatility transmission modelling using MGARCH-BEKK, DCC, t-Copulas," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 83-100.
    127. Tanin, Tauhidul Islam & Hasanov, Akram Shavkatovich & Shaiban, Mohammed Sharaf Mohsen & Brooks, Robert, 2022. "Risk transmission from the oil market to Islamic and conventional banks in oil-exporting and oil-importing countries," Energy Economics, Elsevier, vol. 115(C).
    128. Xu, Yongdeng & Taylor, Nick & Lu, Wenna, 2018. "Illiquidity and volatility spillover effects in equity markets during and after the global financial crisis: An MEM approach," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 208-220.
    129. Connor, Gregory & Hagmann, Matthias & Linton, Oliver, 2007. "Efficient estimation of a semiparametric characteristic-based factor model of security returns," LSE Research Online Documents on Economics 24504, London School of Economics and Political Science, LSE Library.
    130. Liu, Xiaoxing & Shehzad, Khurram & Kocak, Emrah & Zaman, Umer, 2022. "Dynamic correlations and portfolio implications across stock and commodity markets before and during the COVID-19 era: A key role of gold," Resources Policy, Elsevier, vol. 79(C).
    131. Pawel Janus & Siem Jan Koopman & André Lucas, 2011. "Long Memory Dynamics for Multivariate Dependence under Heavy Tails," Tinbergen Institute Discussion Papers 11-175/2/DSF28, Tinbergen Institute.
    132. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH model," SSE/EFI Working Paper Series in Economics and Finance 0652, Stockholm School of Economics.
    133. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    134. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    135. Kate Phylaktis & Antonis Aristidou, 2013. "Margin Changes and Futures Trading Activity: a New Approach," European Financial Management, European Financial Management Association, vol. 19(1), pages 45-71, January.
    136. Zolotko, Mikhail & Okhrin, Ostap, 2012. "Modelling general dependence between commodity forward curves," SFB 649 Discussion Papers 2012-060, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    137. Neifar, Malika, 2020. "Multivariate GARCH Approaches: case of major sectorial Tunisian stock markets," MPRA Paper 99658, University Library of Munich, Germany.
    138. Bauwens, Luc & Xu, Yongdeng, 2023. "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
    139. Jean-David Fermanian & Benjamin Poignard & Panos Xidonas, 2025. "Model-based vs. agnostic methods for the prediction of time-varying covariance matrices," Annals of Operations Research, Springer, vol. 346(1), pages 511-548, March.
    140. Boussama, Farid & Fuchs, Florian & Stelzer, Robert, 2011. "Stationarity and geometric ergodicity of BEKK multivariate GARCH models," Stochastic Processes and their Applications, Elsevier, vol. 121(10), pages 2331-2360, October.
    141. Das, Mahamitra & Kundu, Srikanta & Sarkar, Nityananda, 2019. "Mean and Volatility Spillovers between REIT and Stocks Returns A STVAR-BTGARCH-M Model," MPRA Paper 94707, University Library of Munich, Germany.
    142. Torro, Hipolit, 2009. "Assessing the influence of spot price predictability on electricity futures hedging," MPRA Paper 18892, University Library of Munich, Germany.
    143. Damek, Ewa & Matsui, Muneya, 2022. "Tails of bivariate stochastic recurrence equation with triangular matrices," Stochastic Processes and their Applications, Elsevier, vol. 150(C), pages 147-191.
    144. Sarantis Tsiaplias & Chew Lian Chua, 2013. "A Multivariate GARCH Model Incorporating the Direct and Indirect Transmission of Shocks," Econometric Reviews, Taylor & Francis Journals, vol. 32(2), pages 244-271, February.
    145. Yujia Hu, 2023. "A Heuristic Approach to Forecasting and Selection of a Portfolio with Extra High Dimensions," Mathematics, MDPI, vol. 11(6), pages 1-21, March.
    146. Edoardo Otranto & Massimo Mucciardi & Pietro Bertuccelli, 2016. "Spatial effects in dynamic conditional correlations," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(4), pages 604-626, March.
    147. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    148. Aboura, Sofiane & Chevallier, Julien, 2014. "Cross-market spillovers with ‘volatility surprise’," Review of Financial Economics, Elsevier, vol. 23(4), pages 194-207.
    149. Małgorzata Just & Aleksandra Łuczak, 2020. "Assessment of Conditional Dependence Structures in Commodity Futures Markets Using Copula-GARCH Models and Fuzzy Clustering Methods," Sustainability, MDPI, vol. 12(6), pages 1-22, March.
    150. Kamel Malik Bensafta, 2014. "A Regional Analysis of Markets Uncertainty Spillovers," Working Papers halshs-01015435, HAL.
    151. Rasmus Søndergaard Pedersen & Olivier Wintenberger, 2017. "On the tail behavior of a class of multivariate conditionally heteroskedastic processes," Post-Print hal-01436267, HAL.
    152. Chulwoo Han & Frank C. Park & Jangkoo Kang, 2017. "A geometric treatment of time-varying volatilities," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 1121-1141, November.
    153. Jose Arreola Hernandez & Sang Hoon Kang & Seong-Min Yoon, 2022. "Spillovers and portfolio optimization of precious metals and global/regional equity markets," Applied Economics, Taylor & Francis Journals, vol. 54(20), pages 2320-2342, April.
    154. 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.
    155. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    156. Jianqing Fan & Mingjin Wang & Qiwei Yao, 2008. "Modelling multivariate volatilities via conditionally uncorrelated components," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 679-702, September.
    157. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2023. "Asymmetric volatility spillover between crude oil and other asset markets," Cardiff Economics Working Papers E2023/27, Cardiff University, Cardiff Business School, Economics Section.
    158. Piao, Xiaorui & Mei, Bin & Xue, Yuan, 2016. "Comparing the financial performance of timber REITs and other REITs," Forest Policy and Economics, Elsevier, vol. 72(C), pages 115-121.
    159. 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.
    160. Tansuchat, R. & Chang, C-L. & McAleer, M.J., 2010. "Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH," Econometric Institute Research Papers EI 2010-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    161. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," Tinbergen Institute Discussion Papers 13-003/III, Tinbergen Institute.
    162. Yi-Ting Chen, 2008. "A unified approach to standardized-residuals-based correlation tests for GARCH-type models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 111-133.
    163. Karanasos, M. & Yfanti, S., 2021. "On the Economic fundamentals behind the Dynamic Equicorrelations among Asset classes: Global evidence from Equities, Real estate, and Commodities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    164. Maghyereh Aktham Issa & Awartani Basel, 2012. "Modeling and Forecasting Value-at-Risk in the UAE Stock Markets: The Role of Long Memory, Fat Tails and Asymmetries in Return Innovations," Review of Middle East Economics and Finance, De Gruyter, vol. 8(1), pages 1-22, August.
    165. Hafner, Christian M. & Linton, Oliver, 2010. "Efficient estimation of a multivariate multiplicative volatility model," Journal of Econometrics, Elsevier, vol. 159(1), pages 55-73, November.
    166. Simos Meintanis & Bojana Milošević & Marko Obradović & Mirjana Veljović, 2024. "Goodness‐of‐fit tests for the multivariate Student‐t distribution based on i.i.d. data, and for GARCH observations," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(2), pages 298-319, March.
    167. Psaradakis, Zacharias & Vávra, Marián, 2014. "On testing for nonlinearity in multivariate time series," Economics Letters, Elsevier, vol. 125(1), pages 1-4.
    168. Julien Idier, 2008. "Long term vs. short term comovements in stock markets: the use of Markov-switching multifractal models," Working papers 218, Banque de France.
    169. Wahab, Mahmoud, 2012. "Asymmetric effects of U.S. stock returns on European equities," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 156-172.
    170. Ariana Paola Cortés Ángel & Mustafa Hakan Eratalay, 2022. "Deep diving into the S&P Europe 350 index network and its reaction to COVID-19," Journal of Computational Social Science, Springer, vol. 5(2), pages 1343-1408, November.
    171. Busse, S. & Brümmer, B. & Ihle, R., 2011. "Investigating rapeseed price volatilities in the course of the food crisis," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 46, March.
    172. Ndiweni, Zinzile Lorna & Bonga-Bonga, Lumengo, 2022. "Contagion or decoupling? Evidence from emerging stock markets," MPRA Paper 115170, University Library of Munich, Germany.
    173. Pier Francesco Procacci & Tomaso Aste, 2022. "Portfolio optimization with sparse multivariate modeling," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 445-465, October.
    174. BAUWENS Luc, & XU Yongdeng,, 2019. "DCC-HEAVY: A multivariate GARCH model based on realized variances and correlations," LIDAM Discussion Papers CORE 2019025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    175. Hafner, Christian M. & Herwartz, Helmut & Maxand, Simone, 2022. "Identification of structural multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 227(1), pages 212-227.
    176. Xu, Yongdeng & Guan, Bo & Lu, Wenna & Heravi, Saeed, 2024. "Macroeconomic shocks and volatility spillovers between stock, bond, gold and crude oil markets," Energy Economics, Elsevier, vol. 136(C).
    177. David Büttner & Bernd Hayo, 2009. "News and Correlations of CEEC-3 Financial Markets," MAGKS Papers on Economics 200944, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    178. 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).
    179. Anas Eisa Abdelkreem Mohammed & Henry Mwambi & Bernard Omolo, 2024. "Time-Varying Correlations between JSE.JO Stock Market and Its Partners Using Symmetric and Asymmetric Dynamic Conditional Correlation Models," Stats, MDPI, vol. 7(3), pages 1-16, July.
    180. Arthur Charpentier, 2015. "Prévision avec des copules en finance," Working Papers hal-01151233, HAL.
    181. An, Henry & Qiu, Feng & Rude, James, 2021. "Volatility spillovers between food and fuel markets: Do administrative regulations affect the transmission?," Economic Modelling, Elsevier, vol. 102(C).
    182. Piotr Fiszeder, 2011. "Minimum Variance Portfolio Selection for Large Number of Stocks – Application of Time-Varying Covariance Matrices," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 87-98.
    183. Nicol'o Musmeci & Tomaso Aste & Tiziana Di Matteo, 2016. "What does past correlation structure tell us about the future? An answer from network filtering," Papers 1605.08908, arXiv.org.
    184. Jeroen Rombouts & Lars Stentoft, 2010. "Multivariate Option Pricing With Time Varying Volatility and Correlations," CIRANO Working Papers 2010s-23, CIRANO.
    185. Phillip A. Cartwright & Natalija Riabko, 2016. "Further evidence on the explanatory power of spot food and energy commodities market prices for futures prices," Review of Quantitative Finance and Accounting, Springer, vol. 47(3), pages 579-605, October.
    186. Ceyhun Elgin & Adem Y. Elveren, 2025. "An Evaluation and Comparative Analysis of Fiscal and Macrofinancial Policies during the COVID-19 Pandemic: The Case of Bulgaria in the Balkan Context," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 89-112.
    187. Hashem Pesaran & Paolo Zaffaroni & Banca d'Italia), 2004. "Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management," Money Macro and Finance (MMF) Research Group Conference 2004 101, Money Macro and Finance Research Group.
    188. Chen, Xiaohong & Fan, Yanqin & Patton, Andrew J., 2004. "Simple tests for models of dependence between multiple financial time series, with applications to U.S. equity returns and exchange rates," LSE Research Online Documents on Economics 24681, London School of Economics and Political Science, LSE Library.
    189. Aloui, Chaker & Hammoudeh, Shawkat & Hamida, Hela ben, 2015. "Global factors driving structural changes in the co-movement between sharia stocks and sukuk in the Gulf Cooperation Council countries," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 311-329.
    190. Tunahan Yilmaz, 2021. "Optimal Dynamic Hedging in Selected Markets," International Econometric Review (IER), Econometric Research Association, vol. 13(4), pages 89-117, December.
    191. Marçal, Emerson Fernandes & Pereira, Pedro L. Valls, 2008. "Testing the Hypothesis of Contagion Using Multivariate Volatility Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 28(2), November.
    192. John T. Cuddington & Arturo L. Va'squez Cordano, 2013. "Linkages between spot and futures prices: Tests of the Fama-French-Samuelson hypotheses," Working Papers 2013-09, Colorado School of Mines, Division of Economics and Business.
    193. Massimiliano Caporin & Juliusz Pres' & Hipolit Torro, 2010. "Model Based Monte Carlo Pricing of Energy and Temperature Quanto Options," "Marco Fanno" Working Papers 0123, Dipartimento di Scienze Economiche "Marco Fanno".
    194. Halil Ibrahim Bulut, 2005. "Mudaraba-Venture Capital Closed-end Mutual Funds and Mudaraba-Venture Capital Open-end Mutual Funds," Istanbul Stock Exchange Review, Research and Business Development Department, Borsa Istanbul, vol. 8(30), pages 31-58.
    195. Gardebroek, Cornelis & Hernandez, Manuel A., 2013. "Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets," Energy Economics, Elsevier, vol. 40(C), pages 119-129.
    196. Václav Klepáč & David Hampel, 2015. "Assessing Efficiency of D-Vine Copula ARMA-GARCH Method in Value at Risk Forecasting: Evidence from PSE Listed Companies," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(4), pages 1287-1295.
    197. Chen, Runquan, 2009. "Regime switching in volatilities and correlation between stock and bond markets," LSE Research Online Documents on Economics 29306, London School of Economics and Political Science, LSE Library.
    198. Hafner, C. & Linton, O. & Tang, H., 2018. "Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1878, Faculty of Economics, University of Cambridge.
    199. Aboura, Sofiane & Chevallier, Julien, 2018. "Tail risk and the return-volatility relation," Research in International Business and Finance, Elsevier, vol. 46(C), pages 16-29.
    200. Charfeddine, Lanouar & Benlagha, Noureddine, 2016. "A time-varying copula approach for modelling dependency: New evidence from commodity and stock markets," Journal of Multinational Financial Management, Elsevier, vol. 37, pages 168-189.
    201. Souček, Michael & Todorova, Neda, 2013. "Realized volatility transmission between crude oil and equity futures markets: A multivariate HAR approach," Energy Economics, Elsevier, vol. 40(C), pages 586-597.
    202. Francq, Christian & Zakoian, Jean-Michel, 2019. "Virtual Historical Simulation for estimating the conditional VaR of large portfolios," MPRA Paper 95965, University Library of Munich, Germany.
    203. Karanasos, Menelaos & Yfanti, Stavroula & Karoglou, Michail, 2016. "Multivariate FIAPARCH modelling of financial markets with dynamic correlations in times of crisis," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 332-349.
    204. Julyerme M. Tonin & Carlos M. R. Vieira & Rui M. de Sousa Fragoso & João G. Martines Filho, 2020. "Conditional correlation and volatility between spot and futures markets for soybean and corn," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 707-724, October.
    205. Chau, Frankie & Deesomsak, Rataporn & Wang, Jun, 2014. "Political uncertainty and stock market volatility in the Middle East and North African (MENA) countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 1-19.
    206. Karol Szafranek, 2015. "Financialisation of the commodity markets. Conclusions from the VARX DCC GARCH," EcoMod2015 8554, EcoMod.
    207. Giovanni Barone-Adesi & Francesco Audrino, 2006. "Average conditional correlation and tree structures for multivariate GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 579-600.
    208. Banerjee, Ameet Kumar & Sensoy, Ahmet & Goodell, John W., 2024. "Connectivity and spillover during crises: Highlighting the prominent and growing role of green energy," Energy Economics, Elsevier, vol. 129(C).
    209. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Vo, Xuan Vinh, 2022. "What drives cross-market correlations during the United States Q.E.?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    210. Siran Fang & Yunjie Wei & Shouyang Wang, 2024. "30 years of exchange rate analysis and forecasting: A bibliometric review," Journal of Economic Surveys, Wiley Blackwell, vol. 38(3), pages 973-1007, July.
    211. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
    212. Gao, Jiti & Peng, Bin & Wu, Wei Biao & Yan, Yayi, 2024. "Time-varying multivariate causal processes," Journal of Econometrics, Elsevier, vol. 240(1).
    213. Halbleib Roxana & Voev Valeri, 2011. "Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 134-152, February.
    214. 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.
    215. Massimiliano Caporin & Michael McAleer, 2011. "Thresholds, news impact surfaces and dynamic asymmetric multivariate GARCH," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 65(2), pages 125-163, May.
    216. Sarwar, Suleman & Khalfaoui, Rabeh & Waheed, Rida & Dastgerdi, Hamidreza Ghorbani, 2019. "Volatility spillovers and hedging: Evidence from Asian oil-importing countries," Resources Policy, Elsevier, vol. 61(C), pages 479-488.
    217. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2009. "Modelling Conditional Correlations for Risk Diversification in Crude Oil Markets," CARF F-Series CARF-F-162, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    218. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About the Dynamic Conditional Correlation Representation," KIER Working Papers 870, Kyoto University, Institute of Economic Research.
    219. Gupta, Rangan & Kollias, Christos & Papadamou, Stephanos & Wohar, Mark E., 2018. "News implied volatility and the stock-bond nexus: Evidence from historical data for the USA and the UK markets," Journal of Multinational Financial Management, Elsevier, vol. 47, pages 76-90.
    220. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    221. Rasmus Søndergaard Pedersen, 2014. "Targeting estimation of CCC-Garch models with infinite fourth moments," Discussion Papers 14-04, University of Copenhagen. Department of Economics.
    222. Yanan Li & David E. Giles, 2015. "Modelling Volatility Spillover Effects Between Developed Stock Markets and Asian Emerging Stock Markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 155-177, March.
    223. Selim Amrouni & Aymeric Moulin & Tucker Balch, 2022. "CTMSTOU driven markets: simulated environment for regime-awareness in trading policies," Papers 2202.00941, arXiv.org, revised Feb 2022.
    224. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    225. Manabu Asai & Michael McAleer, 2013. "A Fractionally Integrated Wishart Stochastic Volatility Model," Documentos de Trabajo del ICAE 2013-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    226. CARPANTIER, Jean-François & SAMKHARADZE, Besik, 2012. "The asymmetric commodity inventory effect on the optimal hedge ratio," LIDAM Discussion Papers CORE 2012020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    227. Mazzarisi, Piero & Lillo, Fabrizio & Marmi, Stefano, 2019. "When panic makes you blind: A chaotic route to systemic risk," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 176-199.
    228. Valadkhani, Abbas & O'Brien, Martin & Karunanayake, Indika, 2009. "Modelling Australian Stock Market Volatility: A Multivariate GARCH Approach," Economics Working Papers wp09-11, School of Economics, University of Wollongong, NSW, Australia.
    229. Adams, Zeno & Glück, Thorsten, 2015. "Financialization in commodity markets: A passing trend or the new normal?," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 93-111.
    230. Elie Bouri & Mahamitra Das & Rangan Gupta & David Roubaud, 2018. "Spillovers between Bitcoin and other Assets during Bear and Bull Markets," Working Papers 201812, University of Pretoria, Department of Economics.
    231. King, Daniel & Botha, Ferdi, 2015. "Modelling stock return volatility dynamics in selected African markets," Economic Modelling, Elsevier, vol. 45(C), pages 50-73.
    232. Wan-Hsiu Cheng, 2008. "Overestimation in the Traditional GARCH Model During Jump Periods," Economics Bulletin, AccessEcon, vol. 3(68), pages 1-20.
    233. Caldeira, João F & Moura, Guilherme Valle & Santos, André Alves Portela, 2013. "Seleção de carteiras utilizando o modelo Fama-French-Carhart," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
    234. Philipp Adämmer & Martin T. Bohl & Ernst-Oliver Ledebur, 2015. "Price Transmissions During Financialization and Turmoil: New Evidence from North American and European Agricultural Futures," CQE Working Papers 3815, Center for Quantitative Economics (CQE), University of Muenster.
    235. Andreou, Elena & Matsi, Maria & Savvides, Andreas, 2013. "Stock and foreign exchange market linkages in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 248-268.
    236. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    237. João Caldeira & Guilherme Moura & André A.P. Santos, 2012. "Portfolio optimization using a parsimonious multivariate GARCH model: application to the Brazilian stock market," Economics Bulletin, AccessEcon, vol. 32(3), pages 1848-1857.
    238. Audrone Virbickaite & M. Concepci'on Aus'in & Pedro Galeano, 2013. "A Bayesian Non-Parametric Approach to Asymmetric Dynamic Conditional Correlation Model With Application to Portfolio Selection," Papers 1301.5129, arXiv.org, revised Jan 2014.
    239. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    240. Villalba Padilla, Fátima Irina & Flores-Ortega, Miguel, 2014. "Análisis de la volatilidad del índice principal del mercado bursátil mexicano, del índice de riesgo país y de la mezcla mexicana de exportación mediante un modelo GARCH trivariado asimétrico || Volati," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 17(1), pages 3-22, June.
    241. MacDonald, Ronald & Sogiakas, Vasilios & Tsopanakis, Andreas, 2018. "Volatility co-movements and spillover effects within the Eurozone economies: A multivariate GARCH approach using the financial stress index," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 17-36.
    242. Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Multivariate GARCH models," CREATES Research Papers 2008-06, Department of Economics and Business Economics, Aarhus University.
    243. Asai, Manabu & Caporin, Massimiliano & McAleer, Michael, 2015. "Forecasting Value-at-Risk using block structure multivariate stochastic volatility models," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 40-50.
    244. Vargas, Gregorio A., 2006. "An Asymmetric Block Dynamic Conditional Correlation Multivariate GARCH Model," MPRA Paper 189, University Library of Munich, Germany, revised Aug 2006.
    245. Beneki, Christina & Koulis, Alexandros & Kyriazis, Nikolaos A. & Papadamou, Stephanos, 2019. "Investigating volatility transmission and hedging properties between Bitcoin and Ethereum," Research in International Business and Finance, Elsevier, vol. 48(C), pages 219-227.
    246. Sébastien Laurent & Jeroen Rombouts & Francesco Violente, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," CIRANO Working Papers 2009s-45, CIRANO.
    247. Mohammad Alomari & Abdel Razzaq Al rababa’a & Ghaith El-Nader & Ahmad Alkhataybeh, 2021. "Who’s behind the wheel? The role of social and media news in driving the stock–bond correlation," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 959-1007, October.
    248. Chia-Lin Chang & Lydia González-Serrano & Juan-Ángel Jiménez-Martín, 2011. "Currency Hedging Strategies Using Dynamic Multivariate GARCH," Documentos de Trabajo del ICAE 2011-33, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    249. Olessia Caillé & Daria Onori, 2018. "Conditional Risk-Based Portfolio," Working Papers hal-01973115, HAL.
    250. Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with ‘Volatility Surprise’," Working Papers hal-04141310, HAL.
    251. Ahmad, Wasim & Sehgal, Sanjay & Bhanumurthy, N.R., 2013. "Eurozone crisis and BRIICKS stock markets: Contagion or market interdependence?," Economic Modelling, Elsevier, vol. 33(C), pages 209-225.
    252. 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.
    253. Manabu Asai & Michael McAleer, 2016. "Asymptotic Theory for Extended Asymmetric Multivariate GARCH Processes," Documentos de Trabajo del ICAE 2016-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    254. Andrés García-Medina & Ester Aguayo-Moreno, 2024. "LSTM–GARCH Hybrid Model for the Prediction of Volatility in Cryptocurrency Portfolios," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1511-1542, April.
    255. Víctor Peña & Kaoru Irie, 2022. "On the Relationship between Uhlig Extended and beta‐Bartlett Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 147-153, January.
    256. Chen Tong & Peter Reinhard Hansen & Ilya Archakov, 2024. "Cluster GARCH," Papers 2406.06860, arXiv.org.
    257. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2012. "Financial Risk Measurement for Financial Risk Management," NBER Working Papers 18084, National Bureau of Economic Research, Inc.
    258. Neil Shephard & Kevin Sheppard & Robert F. Engle, 2008. "Fitting vast dimensional time-varying covariance models," Economics Series Working Papers 403, University of Oxford, Department of Economics.
    259. Pierre O. De souza & Tiago P. Filomena & João F. Caldeira & Denis Borenstein & Marcelo B. Righi, 2017. "Risk parity in the brazilian market," Economics Bulletin, AccessEcon, vol. 37(3), pages 1555-1566.
    260. Hendrych, R. & Cipra, T., 2016. "On conditional covariance modelling: An approach using state space models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 304-317.
    261. Sercan Demiralay & Veysel Ulusoy, 2017. "How Has the Behavior of Cross-Market Correlations Altered During Financial and Debt Crises?," Manchester School, University of Manchester, vol. 85(6), pages 765-794, December.
    262. Dimitrios Vortelinos & Konstantinos Gkillas (Gillas) & Costas Syriopoulos & Argyro Svingou, 2017. "Asymmetric and nonlinear inter-relations of US stock indices," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 14(1), pages 78-129, December.
    263. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    264. David E. Allen & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2014. "Volatility Spillovers from Australia's Major Trading Partners across the GFC," Tinbergen Institute Discussion Papers 14-106/III, Tinbergen Institute.
    265. Christopher Thiem, 2018. "Oil price uncertainty and the business cycle: Accounting for the influences of global supply and demand within a VAR GARCH-in-mean framework," Applied Economics, Taylor & Francis Journals, vol. 50(34-35), pages 3735-3751, July.
    266. McIver, Ron P. & Kang, Sang Hoon, 2020. "Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets," Research in International Business and Finance, Elsevier, vol. 54(C).
    267. Eduardo Ortas & José Moneva & Roger Burritt & Joanne Tingey-Holyoak, 2014. "Does Sustainability Investment Provide Adaptive Resilience to Ethical Investors? Evidence from Spain," Journal of Business Ethics, Springer, vol. 124(2), pages 297-309, October.
    268. Grané Chávez, Aurea & Martín-Barragán, Belén & Veiga, Helena, 2014. "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS ws140503, Universidad Carlos III de Madrid. Departamento de Estadística.
    269. Nikkinen, Jussi & Rothovius, Timo, 2019. "The EIA WPSR release, OVX and crude oil internet interest," Energy, Elsevier, vol. 166(C), pages 131-141.
    270. Dimiter Shalvardjiev, 2025. "Asset Hedging via Digital Asset Indices," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 63-88.
    271. Khurram Shehzad & Xiaoxing Liu & Aviral Tiwari & Muhammad Arif & Abdul Rauf, 2021. "Analysing time difference and volatility linkages between China and the United States during financial crises and stable period using VARX‐DCC‐MEGARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 814-833, January.
    272. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2019. "Regularized Estimation of High-Dimensional Vector AutoRegressions with Weakly Dependent Innovations," Papers 1912.09002, arXiv.org, revised Jun 2021.
    273. Raddant, Matthias & Kenett, Dror, 2016. "Interconnectedness in the global financial market," VfS Annual Conference 2016 (Augsburg): Demographic Change 145560, Verein für Socialpolitik / German Economic Association.
    274. Rodolfo Cermeño & Julio Mamani-Palacios, 2013. "Regímenes Monetarios y Volatilidad del Tipo de Cambio Real: El Caso Peruano, 1995-2012," Working Papers DTE 565, CIDE, División de Economía.
    275. BAUWENS, Luc & STORTI, Giuseppe, 2013. "Computationally efficient inference procedures for vast dimensional realized covariance models," LIDAM Reprints CORE 2469, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    276. Jos� A. Fioruci & Ricardo S. Ehlers & Marinho G. Andrade Filho, 2014. "Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 320-331, February.
    277. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    278. Chang, Kuang-Liang, 2012. "The time-varying and asymmetric dependence between crude oil spot and futures markets: Evidence from the Mixture copula-based ARJI–GARCH model," Economic Modelling, Elsevier, vol. 29(6), pages 2298-2309.
    279. Onour, Ibrahim, 2011. "Does credit for equity investments feedback on stock market volatility? Evidence from an emerging stock market," MPRA Paper 28001, University Library of Munich, Germany.
    280. Djamel Kirat & Ibrahim Ahamada, 2009. "The impact of the European Union emission trading scheme on electricity generation sectors," Documents de travail du Centre d'Economie de la Sorbonne 09025, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    281. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2017. "Predictability and diversification benefits of investing in commodity and currency futures," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 52-66.
    282. Manabu Asai & Massimiliano Caporin & Michael McAleer, 2009. "Block Structure Multivariate Stochastic Volatility Models," CIRJE F-Series CIRJE-F-699, CIRJE, Faculty of Economics, University of Tokyo.
    283. Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
    284. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.
    285. Carol Alexander & Emese Lazar & Silvia Stanescu, 2018. "Analytic Moments for GARCH Processes," Papers 1808.09666, arXiv.org, revised Sep 2018.
    286. Rakesh Gupta & Junhao Yang & Thadavillil Jithendranathan, 2017. "Diversification into Emerging Markets – An Australian and the US Perspective Using a Time-varying Approach," Australian Economic Papers, Wiley Blackwell, vol. 56(2), pages 134-162, June.
    287. 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.
    288. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    289. Makushkin, Mikhail & Lapshin, Victor, 2020. "Modelling tail dependencies between Russian and foreign stock markets: Application for market risk valuation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 30-52.
    290. Philippe Charlot & Vêlayoudom Marimoutou, 2011. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model (version révisée)," Working Papers hal-00605965, HAL.
    291. Apostolos Serletis & Maksim Isakin, "undated". "Stochastic Volatility Demand Systems," Working Papers 2014-74, Department of Economics, University of Calgary, revised 29 Sep 2014.
    292. Horvath Roman & Poldauf Petr, 2012. "International Stock Market Comovements: What Happened during the Financial Crisis?," Global Economy Journal, De Gruyter, vol. 12(1), pages 1-21, March.
    293. Alessio Brini & Giacomo Toscano, 2024. "SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks," Papers 2401.06249, arXiv.org, revised Jan 2025.
    294. Trino-Manuel Ñíguez, 2008. "Volatility and VaR forecasting in the Madrid Stock Exchange," Spanish Economic Review, Springer;Spanish Economic Association, vol. 10(3), pages 169-196, September.
    295. Cristiana Tudor & Aura Girlovan & Gabriel Robert Saiu & Daniel Dumitru Guse, 2025. "Asymmetric Shocks and Pension Fund Volatility: A GARCH Approach with Macroeconomic Predictors to an Unexplored Emerging Market," Mathematics, MDPI, vol. 13(7), pages 1-29, March.
    296. 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.
    297. Charlotte Christiansen, 2010. "Decomposing European bond and equity volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(2), pages 105-122.
    298. John Francis Diaz & Peh Ying Qian & Genevieve Liao Tan, 2018. "Variance Persistence in the Greater China Region: A Multivariate GARCH Approach," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 23(2), pages 49-68, July-Dec.
    299. Angi RÖSCH & Harald SCHMIDBAUER, 2008. "Volatility Spillovers between Crude Oil Prices and US Dollar to Euro Exchange Rates," EcoMod2008 23800119, EcoMod.
    300. Francisco Blasques & Andre Lucas & Erkki Silde, 2013. "Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models," Tinbergen Institute Discussion Papers 13-097/IV/DSF59, Tinbergen Institute.
    301. Fengler, Matthias & Polivka, Jeannine, 2021. "Proxy-identification of a structural MGARCH model for asset returns," Economics Working Paper Series 2103, University of St. Gallen, School of Economics and Political Science, revised Oct 2024.
    302. Heather M. Anderson & Farshid Vahid, 2013. "Common non-linearities in multiple series of stock market volatility," Monash Econometrics and Business Statistics Working Papers 1/13, Monash University, Department of Econometrics and Business Statistics.
    303. Shegorika Rajwani & Dilip Kumar, 2016. "Asymmetric Dynamic Conditional Correlation Approach to Financial Contagion: A Study of Asian Markets," Global Business Review, International Management Institute, vol. 17(6), pages 1339-1356, December.
    304. Wasim Ahmad & N.R. Bhanumurthy & Sanjay Sehgal, 2014. "The Eurozone crisis and its contagion effects on the European stock markets," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 31(3), pages 325-352, July.
    305. Marçal, Emerson F. & Valls Pereira, Pedro L., 2008. "Testando A Hipótese De Contágio A Partir De Modelos Multivariados De Volatilidade [Testing the contagion hypotheses using multivariate volatility models]," MPRA Paper 10356, University Library of Munich, Germany.
    306. M. Hashem Pesaran & Bahram Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series 2056, CESifo.
    307. Chkili, Walid, 2016. "Dynamic correlations and hedging effectiveness between gold and stock markets: Evidence for BRICS countries," Research in International Business and Finance, Elsevier, vol. 38(C), pages 22-34.
    308. Savva, Christos S., 2009. "International stock markets interactions and conditional correlations," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 645-661, October.
    309. Noureddine BENLAGHA & Slim MSEDDI, 2016. "The Macroeconomic And Financial Impacts Of European Crisis On Saudi Arabia," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 16(1).
    310. Edson Zambon Monte & Felipe Fantin Almeida, 2020. "Interrelationships Between The Stock Returns Of Brazilian Companies That Make Up The Sãƒo Paulo Stock Exchange Index," Revista de Economia Mackenzie (REM), Mackenzie Presbyterian University, Social and Applied Sciences Center, vol. 17(1), pages 115-145, January-J.
    311. Raddant, Matthias & Wagner, Friedrich, 2016. "Multivariate GARCH for a large number of stocks," Kiel Working Papers 2049, Kiel Institute for the World Economy (IfW Kiel).
    312. Caporin, M. & McAleer, M.J., 2010. "Ranking multivariate GARCH models by problem dimension," Econometric Institute Research Papers EI 2010-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    313. Malik, Farooq & Ewing, Bradley T., 2009. "Volatility transmission between oil prices and equity sector returns," International Review of Financial Analysis, Elsevier, vol. 18(3), pages 95-100, June.
    314. Storti, Giuseppe & Wang, Chao, 2022. "A multivariate semi-parametric portfolio risk optimization and forecasting framework," MPRA Paper 115266, University Library of Munich, Germany.
    315. Melanie-Kristin Beck & Bernd Hayo & Matthias Neuenkirch, 2013. "Central bank communication and correlation between financial markets: Canada and the United States," International Economics and Economic Policy, Springer, vol. 10(2), pages 277-296, June.
    316. Olivier Ledoit & Michael Wolf, 2019. "The power of (non-)linear shrinking: a review and guide to covariance matrix estimation," ECON - Working Papers 323, Department of Economics - University of Zurich, revised Feb 2020.
    317. Jeroen Rombouts & Lars Stentoft & Francesco Violente, 2012. "The Value of Multivariate Model Sophistication: An Application to pricing Dow Jones Industrial Average Options," CIRANO Working Papers 2012s-05, CIRANO.
    318. Yacouba Boubacar Maïnassara & Othman Kadmiri & Bruno Saussereau, 2022. "Portmanteau test for a class of multivariate asymmetric power GARCH model," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 964-1002, November.
    319. Ilia Tetin & Elizaveta Antonenko & Guych Nuryyev, 2023. "Asymmetric Effects of Exchange Rate Volatility on Taiwan-China Trade: A Non-Linear ARDL Analysis of 20 Industries," Bulletin of Applied Economics, Risk Market Journals, vol. 10(2), pages 173-189.
    320. Jose Fernandez & Bruce Morley, 2015. "Interdependence among Agricultural Commodity Markets, Macroeconomic Factors, Crude Oil and Commodity Index," Department of Economics Working Papers 42/15, University of Bath, Department of Economics.
    321. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    322. Soni, Rajat Kumar & Nandan, Tanuj & Sawarn, Ujjawal, 2024. "Investment modeling between energy futures and responsible investment," Research in International Business and Finance, Elsevier, vol. 70(PB).
    323. Andrea, SILVESTRINI, 2005. "Temporal aggregaton of univariate linear time series models," Discussion Papers (ECON - Département des Sciences Economiques) 2005044, Université catholique de Louvain, Département des Sciences Economiques.
    324. Nidhi Choudhary & Girish K. Nair & Harsh Purohit, 2015. "Volatility In Copper Prices In India," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-26, December.
    325. Chamizo, Álvaro & Novales, Alfonso, 2021. "Evaluation of market risk associated with hedging a credit derivative portfolio," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 411-430.
    326. Çekin, Semih Emre & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "Measuring co-dependencies of economic policy uncertainty in Latin American countries using vine copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 207-217.
    327. Ratti, Ronald A. & Hasan, M. Zahid, 2013. "Oil Price Shocks and Volatility in Australian Stock Returns ‎," MPRA Paper 49043, University Library of Munich, Germany.
    328. Matthias Pelster & Johannes Vilsmeier, 2018. "The determinants of CDS spreads: evidence from the model space," Review of Derivatives Research, Springer, vol. 21(1), pages 63-118, April.
    329. E. Otranto, 2008. "Identifying Financial Time Series with Similar Dynamic Conditional Correlation," Working Paper CRENoS 200817, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    330. Dennis Bergmann & Declan O’Connor & Andreas Thümmel, 2016. "An analysis of price and volatility transmission in butter, palm oil and crude oil markets," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 4(1), pages 1-23, December.
    331. Kei Nakagawa & Masanori Hirano & Kentaro Minami & Takanobu Mizuta, 2024. "A Multi-agent Market Model Can Explain the Impact of AI Traders in Financial Markets -- A New Microfoundations of GARCH model," Papers 2409.12516, arXiv.org.
    332. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    333. Atoi, Ngozi Victor & Nwambeke, Chinedu G., 2021. "Money and Foreign Exchange Markets Dynamics in Nigeria: A Multivariate GARCH Approach," MPRA Paper 109305, University Library of Munich, Germany.
    334. Canh, Nguyen Phuc & Wongchoti, Udomsak & Thanh, Su Dinh & Thong, Nguyen Trung, 2019. "Systematic risk in cryptocurrency market: Evidence from DCC-MGARCH model," Finance Research Letters, Elsevier, vol. 29(C), pages 90-100.
    335. 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.
    336. El Abed, Riadh & Zardoub, Amna, 2017. "Time varying and asymmetric effect between sovereign credit market and financial market: The asymmetric DCC model," Economics Discussion Papers 2017-97, Kiel Institute for the World Economy (IfW Kiel).
    337. Elena Andreou & Bas J.M. Werker, 2014. "Residual-based Rank Specification Tests for AR-GARCH type models," University of Cyprus Working Papers in Economics 02-2014, University of Cyprus Department of Economics.
    338. Kwan, Clarence C.Y., 2008. "Estimation error in the average correlation of security returns and shrinkage estimation of covariance and correlation matrices," Finance Research Letters, Elsevier, vol. 5(4), pages 236-244, December.
    339. Martina Danielova Zaharieva & Mark Trede & Bernd Wilfling, 2017. "Bayesian semiparametric multivariate stochastic volatility with an application to international stock-market co-movements," CQE Working Papers 6217, Center for Quantitative Economics (CQE), University of Muenster.
    340. 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.
    341. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    342. Rizvi, Syed Aun R. & Arshad, Shaista & Alam, Nafis, 2018. "A tripartite inquiry into volatility-efficiency-integration nexus - case of emerging markets," Emerging Markets Review, Elsevier, vol. 34(C), pages 143-161.
    343. Marco Barassi & Lajos Horváth & Yuqian Zhao, 2020. "Change‐Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 340-349, April.
    344. José Rangel & Robert Engle, 2012. "The Factor–Spline–GARCH Model for High and Low Frequency Correlations," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 109-124.
    345. Yu‐Sheng Lai, 2022. "Use of high‐frequency data to evaluate the performance of dynamic hedging strategies," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 104-124, January.
    346. Harald SCHMIDBAUER & Eren KALAYCIO?LU, 2008. "Crude Oil and Oil-Related Turkish Company Stocks: A Volatility Analysis," EcoMod2008 23800127, EcoMod.
    347. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
    348. Fresoli, Diego E. & Ruiz, Esther, 2016. "The uncertainty of conditional returns, volatilities and correlations in DCC models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 170-185.
    349. Matthias R. Fengler & Jeannine Polivka, 2024. "Structural Volatility Impulse Response Analysis," Swiss Finance Institute Research Paper Series 24-63, Swiss Finance Institute.
    350. Rita Pimentel & Morten Risstad & Sjur Westgaard, 2022. "Predicting interest rate distributions using PCA & quantile regression," Digital Finance, Springer, vol. 4(4), pages 291-311, December.
    351. 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.
    352. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.
    353. Ahmad, Wasim, 2017. "On the dynamic dependence and investment performance of crude oil and clean energy stocks," Research in International Business and Finance, Elsevier, vol. 42(C), pages 376-389.
    354. Silvennoinen, Annastiina & Teräsvirta, Timo, 2005. "Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations," SSE/EFI Working Paper Series in Economics and Finance 577, Stockholm School of Economics, revised 01 Oct 2005.
    355. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    356. Yu-Pin Hu & Ruey S. Tsay, 2014. "Principal Volatility Component Analysis," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 153-164, April.
    357. Adams, Zeno & Glück, Thorsten, 2013. "Financialization in Commodity Markets: Disentangling the Crisis from the Style Effect," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79949, Verein für Socialpolitik / German Economic Association.
    358. 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.
    359. Palandri, Alessandro, 2009. "Sequential conditional correlations: Inference and evaluation," Journal of Econometrics, Elsevier, vol. 153(2), pages 122-132, December.
    360. Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar & Wolfgang Schmid & Anil K. Bera, 2023. "Spatial and Spatiotemporal Volatility Models: A Review," Papers 2308.13061, arXiv.org.
    361. Kusen, Alex & Rudolf, Markus, 2019. "Feedback trading: Strategies during day and night with global interconnectedness," Research in International Business and Finance, Elsevier, vol. 48(C), pages 438-463.
    362. Kevin Grier & Haichun Ye, 2009. "Twin Sons Of Different Mothers: The Long And The Short Of The Twin Deficits Debate," Economic Inquiry, Western Economic Association International, vol. 47(4), pages 625-638, October.
    363. Zouheir Mighri & Majid Ibrahim Alsaggaf, 2019. "Volatility Spillovers among the Cryptocurrency Time Series," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 81-90.
    364. Abosedra, Salah & Arayssi, Mahmoud & Ben Sita, Bernard & Mutshinda, Crispin, 2020. "Exploring GDP growth volatility spillovers across countries," Economic Modelling, Elsevier, vol. 89(C), pages 577-589.
    365. NEIFAR, MALIKA & HarzAllah, AMIRA, 2025. "Integration, Contagion and Turmoils; Evidence from Emerging markets," MPRA Paper 123775, University Library of Munich, Germany, revised 25 Feb 2025.
    366. Mardi Dungey & Gerald Dwyer & Thomas Flavin, 2013. "Systematic and Liquidity Risk in Subprime-Mortgage Backed Securities," Open Economies Review, Springer, vol. 24(1), pages 5-32, February.
    367. Sadorsky, Perry, 2012. "Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies," Energy Economics, Elsevier, vol. 34(1), pages 248-255.
    368. Marco Avarucci & Eric Beutner & Paolo Zaffaroni, 2012. "On moment conditions for quasi-maximum likelihood estimation of multivariate ARCH models," DSS Empirical Economics and Econometrics Working Papers Series 2012/1, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
    369. Bekkerman, Anton & Pelletier, Denis, 2009. "Basis Volatilities of Corn and Soybean in Spatially Separated Markets: The Effect of Ethanol Demand," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49281, Agricultural and Applied Economics Association.
    370. Onur Ozgur & Alberto Bisin, 2011. "Dynamic linear economies with social interactions," Levine's Working Paper Archive 786969000000000036, David K. Levine.
    371. Michael McAleer, 2009. "The Ten Commandments for Optimizing Value-at-Risk and Daily Capital Charges," Documentos de Trabajo del ICAE 2009-10, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    372. Luiz de Mello & Diego Moccero, 2006. "Consolidating Macroeconomic Adjustment in Brazil," OECD Economics Department Working Papers 531, OECD Publishing.
    373. Stavros Degiannakis & Apostolos Kiohos, 2014. "Multivariate modelling of 10-day-ahead VaR and dynamic correlation for worldwide real estate and stock indices," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 41(2), pages 216-232, March.
    374. Mashlakov, Aleksei & Kuronen, Toni & Lensu, Lasse & Kaarna, Arto & Honkapuro, Samuli, 2021. "Assessing the performance of deep learning models for multivariate probabilistic energy forecasting," Applied Energy, Elsevier, vol. 285(C).
    375. Jean-Marie Dufour & Lynda Khalaf & Marie-Claude Beaulieu, 2010. "Multivariate residual-based finite-sample tests for serial dependence and ARCH effects with applications to asset pricing models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 263-285.
    376. Lumengo Bonga-Bonga & Tebogo Maake, 2021. "The Relationship between Carry Trade and Asset Markets in South Africa," JRFM, MDPI, vol. 14(7), pages 1-13, July.
    377. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    378. Hassan Mohammadi & Yuting Tan, 2015. "Return and Volatility Spillovers across Equity Markets in Mainland China, Hong Kong and the United States," Econometrics, MDPI, vol. 3(2), pages 1-18, April.
    379. Riccardo De Blasis & Filippo Petroni, 2021. "Price Leadership and Volatility Linkages between Oil and Renewable Energy Firms during the COVID-19 Pandemic," Energies, MDPI, vol. 14(9), pages 1-16, May.
    380. Shiyi Chen & Wolfgang K. Härdle & Kiho Jeong, 2010. "Forecasting volatility with support vector machine-based GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 406-433.
    381. Sun, Xiaolei & Li, Jianping & Tang, Ling & Wu, Dengsheng, 2012. "Identifying the risk-return tradeoff and exploring the dynamic risk exposure of country portfolio of the FSU's oil economies," Economic Modelling, Elsevier, vol. 29(6), pages 2494-2503.
    382. Wei Kuang, 2024. "High-frequency enhanced VaR: A robust univariate realized volatility model for diverse portfolios and market conditions," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-35, May.
    383. Chikumbi, Lydia & Muchapondwa, Edwin & Thiam, Djiby, 2020. "Volatility Linkages between Energy and Wine Prices in South Africa," EfD Discussion Paper 20-7, Environment for Development, University of Gothenburg.
    384. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.
    385. Ausloos, Marcel & Jovanovic, Franck & Schinckus, Christophe, 2016. "On the “usual” misunderstandings between econophysics and finance: Some clarifications on modelling approaches and efficient market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 7-14.
    386. Basher, Syed Abul & Sadorsky, Perry, 2016. "Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH," Energy Economics, Elsevier, vol. 54(C), pages 235-247.
    387. Das, Suman & Roy, Saikat Sinha, 2023. "Following the leaders? A study of co-movement and volatility spillover in BRICS currencies," Economic Systems, Elsevier, vol. 47(2).
    388. Sarwar, Suleman & Shahbaz, Muhammad & Anwar, Awais & Tiwari, Aviral Kumar, 2019. "The importance of oil assets for portfolio optimization: The analysis of firm level stocks," Energy Economics, Elsevier, vol. 78(C), pages 217-234.
    389. Hafner, C. & Reznikova, O., 2010. "On the estimation of dynamic conditional correlation models," LIDAM Discussion Papers ISBA 2010006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    390. García-Ferrer, Antonio & González-Prieto, Ester & Peña, Daniel, 2008. "A multivariate generalized independent factor GARCH model with an application to financial stock returns," DES - Working Papers. Statistics and Econometrics. WS ws087528, Universidad Carlos III de Madrid. Departamento de Estadística.
    391. Marcos Escobar-Anel & Maximilian Gollart & Rudi Zagst, 2021. "Closed-form portfolio optimization under GARCH models," Papers 2109.00433, arXiv.org.
    392. Arif Orçun Söylemez, 2013. "Stock Exchange Volatility Transmissions between Turkey and the Major Financial Centers," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 1(2), pages 27-32.
    393. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2025. "The Role of Uncertainty in Forecasting Realized Covariance of US State-Level Stock Returns: A Reverse-MIDAS Approach," Working Papers 202501, University of Pretoria, Department of Economics.
    394. Gabriele Fiorentini & Giorgio Calzolari & Enrique Sentana, 2007. "Indirect estimation of large conditionally heteroskedastic factor models, with an application to the Dow 30 stocks," Working Paper series 40_07, Rimini Centre for Economic Analysis.
    395. LAJILI, Oualid, 2013. "Transmission de la volatilité entre le marché du pétrole et les marchés financiers des pays producteurs [Volatility transmission among the oil market and the financial markets of oil-producing coun," MPRA Paper 86624, University Library of Munich, Germany.
    396. Dreger, Christian & Kholodilin, Konstantin A. & Ulbricht, Dirk & Fidrmuc, Jarko, 2016. "Between the hammer and the anvil: The impact of economic sanctions and oil prices on Russia’s ruble," Journal of Comparative Economics, Elsevier, vol. 44(2), pages 295-308.
    397. Howard Caulfield & James P. Gleeson, 2024. "Systematic comparison of deep generative models applied to multivariate financial time series," Papers 2412.06417, arXiv.org.
    398. Quentin Giai Gianetto & Hamdi Raïssi, 2015. "Testing Instantaneous Causality in Presence of Nonconstant Unconditional Covariance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 46-53, January.
    399. Jyri Kinnunen & Minna Martikainen, 2017. "Dynamic Autocorrelation and International Portfolio Allocation," Multinational Finance Journal, Multinational Finance Journal, vol. 21(1), pages 21-48, March.
    400. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    401. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH models," Economics Series Working Papers 594, University of Oxford, Department of Economics.
    402. Karoll Gómez Portilla & Santiago Gallón Gómez, 2007. "Distribución condicional de los retornos de la tasa de cambio colombiana: un ejercicio empírico a partir de modelos GARCH multivariados," Revista de Economía del Rosario, Universidad del Rosario, December.
    403. de Pinho, Frank M. & Franco, Glaura C. & Silva, Ralph S., 2016. "Modeling volatility using state space models with heavy tailed distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 108-127.
    404. Grier, Kevin B. & Smallwood, Aaron D., 2013. "Exchange rate shocks and trade: A multivariate GARCH-M approach," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 282-305.
    405. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2016. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-1019, CIRJE, Faculty of Economics, University of Tokyo.
    406. Sangwhan Kim & Anil K. Bera, 2023. "Scalar Measures of Volatility and Dependence for the Multivariate Models with Applications to Asian Financial Markets," JRFM, MDPI, vol. 16(4), pages 1-16, March.
    407. Giuseppe Storti & Chao Wang, 2022. "A semi-parametric dynamic conditional correlation framework for risk forecasting," Papers 2207.04595, arXiv.org, revised Dec 2024.
    408. Luca Vincenzo Ballestra & Riccardo De Blasis & Graziella Pacelli, 2025. "Multivariate GARCH models with spherical parameterizations: an oil price application," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-20, December.
    409. 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.
    410. 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.
    411. Panos K. Pouliasis & Nikos C. Papapostolou, 2018. "Volatility and correlation timing: The role of commodities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1407-1439, November.
    412. 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.
    413. Morar Triandafil, Cristina & Brezeanu, Petre & Huidumac, Catalin & Morar Triandafil, Adrian, 2011. "The Drivers of the CEE Exchange Rate Volatility - Empirical Perspective in the context of the Recent Financial Crisis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 212-229, March.
    414. Rodolfo Cermeño & María Eugenia Sanin, 2015. "Are Flexible Exchange Rate Regimes more Volatile? Panel GARCH Evidence for the G7 and Latin America," Review of Development Economics, Wiley Blackwell, vol. 19(2), pages 297-308, May.
    415. Alexander, Carol & Lazar, Emese & Stanescu, Silvia, 2021. "Analytic moments for GJR-GARCH (1, 1) processes," International Journal of Forecasting, Elsevier, vol. 37(1), pages 105-124.
    416. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2021. "VCRIX — A volatility index for crypto-currencies," International Review of Financial Analysis, Elsevier, vol. 78(C).
    417. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.
    418. St'ephane Chr'etien & Juan-Pablo Ortega, 2011. "Multivariate GARCH estimation via a Bregman-proximal trust-region method," Papers 1101.5475, arXiv.org.
    419. Mori Kogid & Jaratin Lily & Rozilee Asid & James M. Alin & Dullah Mulok, 2022. "Volatility spillover and dynamic co-movement of foreign direct investment between Malaysia and China and developed countries," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(1), pages 131-148, February.
    420. M. Hashem Pesaran & Christoph Schleicher & Paolo Zaffaroni, 2008. "Model Averaging in Risk Management with an Application to Futures Markets," CESifo Working Paper Series 2231, CESifo.
    421. Dias, Alexandra & Embrechts, Paul, 2010. "Modeling exchange rate dependence dynamics at different time horizons," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1687-1705, December.
    422. Jooyoung Jeon & James W. Taylor, 2012. "Using Conditional Kernel Density Estimation for Wind Power Density Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 66-79, March.
    423. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    424. Esparcia, Carlos & Diaz, Antonio & Alonso, Daniel, 2023. "How important is green awareness in energy investment decisions? An environmentally-based rebalancing portfolio study," Energy Economics, Elsevier, vol. 128(C).
    425. Moses K. Tule & Umar B. Ndako & Samuel F. Onipede, 2017. "Oil price shocks and volatility spillovers in the Nigerian sovereign bond market," Review of Financial Economics, John Wiley & Sons, vol. 35(1), pages 57-65, November.
    426. Kamel Malik Bensafta & Gervasio Semedo, 2014. "Transmission de la volatilité et Central-Banking," Working Papers halshs-01012058, HAL.
    427. Adam E Clements & Ayesha Scott & Annastiina Silvennoinen, 2012. "Forecasting multivariate volatility in larger dimensions: some practical issues," NCER Working Paper Series 80, National Centre for Econometric Research.
    428. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    429. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2014. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-938, CIRJE, Faculty of Economics, University of Tokyo.
    430. Hernandez, Manuel & Lemma, Solomon & Rashid, Shahidur, 2015. "The Ethiopian Commodity Exchange and the coffee market: Are local prices more integrated to global markets?," 2015 Conference, August 9-14, 2015, Milan, Italy 211732, International Association of Agricultural Economists.
    431. Helmut Herwartz & Alberto Saucedo, 2020. "Food–oil volatility spillovers and the impact of distinct biofuel policies on price uncertainties on feedstock markets," Agricultural Economics, International Association of Agricultural Economists, vol. 51(3), pages 387-402, May.
    432. Pop, Raluca Elena, 2012. "Herd behavior towards the market index: evidence from Romanian stock exchange," MPRA Paper 51595, University Library of Munich, Germany.
    433. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
    434. 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.
    435. Kaijian He & Kin Keung Lai & Guocheng Xiang, 2012. "Portfolio Value at Risk Estimate for Crude Oil Markets: A Multivariate Wavelet Denoising Approach," Energies, MDPI, vol. 5(4), pages 1-26, April.
    436. Shah, Said Zamin & Baharumshah, Ahmad Zubaidi & Hook, Law Siong & Habibullah, Muzafar Shah, 2017. "Nominal uncertainty, real uncertainty and macroeconomic performance in a time-varying asymmetric framework: Implications for monetary policy," Research in International Business and Finance, Elsevier, vol. 42(C), pages 75-93.
    437. Cho, Haeran & Korkas, Karolos K., 2022. "High-dimensional GARCH process segmentation with an application to Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 23(C), pages 187-203.
    438. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    439. Duchesne, Pierre, 2006. "Testing for multivariate autoregressive conditional heteroskedasticity using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2142-2163, December.
    440. Li, Xiafei & Miffre, Joëlle & Brooks, Chris & O'Sullivan, Niall, 2008. "Momentum profits and time-varying unsystematic risk," Journal of Banking & Finance, Elsevier, vol. 32(4), pages 541-558, April.
    441. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & María de la Cruz Del Río-Rama & José Álvarez-García, 2022. "Using Markov-Switching Models in US Stocks Optimal Portfolio Selection in a Black–Litterman Context (Part 1)," Mathematics, MDPI, vol. 10(8), pages 1-28, April.
    442. Chen, Rongda & Xu, Jianjun, 2019. "Forecasting volatility and correlation between oil and gold prices using a novel multivariate GAS model," Energy Economics, Elsevier, vol. 78(C), pages 379-391.
    443. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Series Working Papers 533, University of Oxford, Department of Economics.
    444. 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.
    445. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2012. "The conditional autoregressive Wishart model for multivariate stock market volatility," Journal of Econometrics, Elsevier, vol. 167(1), pages 211-223.
    446. Ceballos, Francisco & Hernandez, Manuel A. & Minot, Nicholas & Robles, Miguel, 2015. "Grain price and volatility transmission from international to domestic markets in developing countries," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206057, Agricultural and Applied Economics Association.
    447. Annastiina Silvennoinen & Timo Teräsvirta, 2012. "Modelling conditional correlations of asset returns: A smooth transition approach," CREATES Research Papers 2012-09, Department of Economics and Business Economics, Aarhus University.
    448. Pan, Qunxing & Mei, Xiaowen & Gao, Tianqing, 2022. "Modeling dynamic conditional correlations with leverage effects and volatility spillover effects: Evidence from the Chinese and US stock markets affected by the recent trade friction," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    449. Janiga-Ćmiel Anna, 2016. "An Analysis of Conditional Dependencies of Covariance Matrices for Economic Processes in Selected EU Countries," Folia Oeconomica Stetinensia, Sciendo, vol. 16(2), pages 119-134, December.
    450. Bekiros, Stelios D., 2014. "Contagion, decoupling and the spillover effects of the US financial crisis: Evidence from the BRIC markets," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 58-69.
    451. Sucarrat, Genaro & Escribano, Álvaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.
    452. Francq, Christian & Zakoian, Jean-Michel, 2010. "QML estimation of a class of multivariate GARCH models without moment conditions on the observed process," MPRA Paper 20779, University Library of Munich, Germany.
    453. Massimo PERI & Daniela VANDONE & Lucia BALDI, 2014. "Water, Food, Energy: Searching for the Economic Nexus," Departmental Working Papers 2014-03, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    454. Enow, Samuel Tabot, 2023. "Exploring Volatility clustering financial markets and its implication," Journal of Economic and Social Development, Clinical Journals Press, vol. 10(02), pages 01-05, September.
    455. Erdogan, Oral & Tata, Kenan & Karahasan, B. Can & Sengoz, M. Hakan, 2013. "Dynamics of the co-movement between stock and maritime markets," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 282-290.
    456. Ahlrichs, Jakob & Rockstuhl, Sebastian & Tränkler, Timm & Wenninger, Simon, 2020. "The impact of political instruments on building energy retrofits: A risk-integrated thermal Energy Hub approach," Energy Policy, Elsevier, vol. 147(C).
    457. Manuel Carlos Nogueira & Mara Madaleno, 2022. "Are Sustainability Indices Infected by the Volatility of Stock Indices? Analysis before and after the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(22), pages 1-13, November.
    458. Chen, Qihao & Huang, Zhuo & Liang, Fang, 2023. "Measuring systemic risk with high-frequency data: A realized GARCH approach," Finance Research Letters, Elsevier, vol. 54(C).
    459. Stan Tendijck & Philip Jonathan & David Randell & Jonathan Tawn, 2024. "Temporal evolution of the extreme excursions of multivariate k$$ k $$th order Markov processes with application to oceanographic data," Environmetrics, John Wiley & Sons, Ltd., vol. 35(3), May.
    460. Peters, Koen & Fleuren, H.A. & Cruijssen, Frans, 2024. "The Role of Analytics in Achieving the Sustainable Development Goal of Zero Hunger," Other publications TiSEM a228bc07-76f6-4405-b563-8, Tilburg University, School of Economics and Management.
    461. Jorge Alberto Achcar & Edilberto Cepeda-Cuervo & Milton Barossi-Filho, 2012. "Multivariate volatility models: an application to IBOVESPA and Dow Jones Industrial," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, June.
    462. Wang, Yilin & Zhang, Zeming & Li, Xiafei & Chen, Xiaodan & Wei, Yu, 2020. "Dynamic return connectedness across global commodity futures markets: Evidence from time and frequency domains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    463. Nakatani, Tomoaki & Teräsvirta, Timo, 2007. "Testing for Volatility Interactions in the Constant Conditional Correlation GARCH Model," SSE/EFI Working Paper Series in Economics and Finance 649, Stockholm School of Economics, revised 04 May 2008.
    464. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    465. David M. Drukker, 2009. "New multivariate time-series estimators in Stata," DC09 Stata Conference 12, Stata Users Group.
    466. Mollick, André Varella & Assefa, Tibebe Abebe, 2013. "U.S. stock returns and oil prices: The tale from daily data and the 2008–2009 financial crisis," Energy Economics, Elsevier, vol. 36(C), pages 1-18.
    467. Dimitrios Thomakos & Johannes Klepsch & Dimitris N. Politis, 2020. "Model Free Inference on Multivariate Time Series with Conditional Correlations," Stats, MDPI, vol. 3(4), pages 1-26, November.
    468. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    469. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    470. Baba, Naohiko & Inada, Masakazu, 2009. "Price discovery of subordinated credit spreads for Japanese mega-banks: Evidence from bond and credit default swap markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 616-632, October.
    471. Linjie Wang & Jean‐Paul Chavas & Jian Li, 2024. "Dynamic linkages in agricultural and energy markets: A quantile impulse response approach," Agricultural Economics, International Association of Agricultural Economists, vol. 55(4), pages 639-676, July.
    472. Meng, Xiaochun & Taylor, James W., 2022. "Comparing probabilistic forecasts of the daily minimum and maximum temperature," International Journal of Forecasting, Elsevier, vol. 38(1), pages 267-281.
    473. 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.
    474. Stanislav Anatolyev & Stanislav Khrapov, 2015. "Right on Target, or Is it? The Role of Distributional Shape in Variance Targeting," Econometrics, MDPI, vol. 3(3), pages 1-23, August.
    475. Lakshina, Valeriya, 2014. "Is it possible to break the «curse of dimensionality»? Spatial specifications of multivariate volatility models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 36(4), pages 61-78.
    476. Kosater, Peter, 2006. "Cross-city hedging with weather derivatives using bivariate DCC GARCH models," Discussion Papers in Econometrics and Statistics 2/06, University of Cologne, Institute of Econometrics and Statistics.
    477. Fantazzini, Dean, 2008. "An Econometric Analysis of Financial Data in Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 10(2), pages 91-137.
    478. Carlo Drago & Andrea Scozzari, 2022. "Evaluating conditional covariance estimates via a new targeting approach and a networks-based analysis," Papers 2202.02197, arXiv.org.
    479. Liu, Ruipeng & Lux, Thomas, 2010. "Flexible and robust modelling of volatility comovements: a comparison of two multifractal models," Kiel Working Papers 1594, Kiel Institute for the World Economy (IfW Kiel).
    480. Abu S. Amin & Lucjan T. Orlowski, 2014. "Returns, Volatilities, and Correlations Across Mature, Regional, and Frontier Markets: Evidence from South Asia," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(3), pages 5-27, May.
    481. Listorti, Giulia & Esposti, Roberto, 2012. "Horizontal Price Transmission in Agricultural Markets: Fundamental Concepts and Open Empirical Issues," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(01), pages 1-28, April.
    482. A. Can Inci & H.C. Li & Joseph McCarthy, 2011. "Measuring flight to quality: a local correlation analysis," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 10(1), pages 69-87, February.
    483. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034, Decembrie.
    484. Trino-Manuel Ñíguez & Javier Perote, 2016. "Multivariate moments expansion density: application of the dynamic equicorrelation model," Working Papers 1602, Banco de España.
    485. Bauwens, Luc & Dzuverovic, Emilija & Hafner, Christian, 2024. "Asymmetric Models for Realized Covariances," LIDAM Discussion Papers ISBA 2024022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    486. Kushal Banik Chowdhury & Srikanta Kundu & Nityananda Sarkar, 2018. "Regime‐dependent effects of uncertainty on inflation and output growth: evidence from the United Kingdom and the United States," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(4), pages 390-413, September.
    487. Gagari Chakrabarti, 2011. "Financial crisis and the changing nature of volatility contagion in the Asia-Pacific region," Journal of Asset Management, Palgrave Macmillan, vol. 12(3), pages 172-184, August.
    488. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    489. Nico Katzke, 2013. "South African Sector Return Correlations: using DCC and ADCC Multivariate GARCH techniques to uncover the underlying dynamics," Working Papers 17/2013, Stellenbosch University, Department of Economics.
    490. Cheng Yu & Zhoufan Zhu & Ke Zhu, 2025. "Tensor dynamic conditional correlation model: A new way to pursuit "Holy Grail of investing"," Papers 2502.13461, arXiv.org.
    491. Mahdi Ghaemi Asl & Giorgio Canarella & Stephen M. Miller, 2020. "Dynamic Asymmetric Optimal Portfolio Allocation between Energy Stocks and Energy Commodities: Evidence from Clean Energy and Oil and Gas Companies," Working papers 2020-07, University of Connecticut, Department of Economics.
    492. Benjamin Poignard & Manabu Asai, 2023. "High‐dimensional sparse multivariate stochastic volatility models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 4-22, January.
    493. Khalfaoui, R & Boutahar, M, 2012. "Portfolio risk evaluation: An approach based on dynamic conditional correlations models and wavelet multiresolution analysis," MPRA Paper 41624, University Library of Munich, Germany.
    494. Blanka Let, 2010. "Dynamics of Multivariate Return Series of U.S. Automotive Stock Companies in Conditions of Crisis," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 43-50.
    495. Kizys, Renatas & Pierdzioch, Christian, 2010. "The business cycle and the equity risk premium in real time," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 711-722, October.
    496. Alhaj-Yaseen, Yaseen S. & Lam, Eddery & Barkoulas, John T., 2014. "Price discovery for cross-listed firms with foreign IPOs," International Review of Financial Analysis, Elsevier, vol. 31(C), pages 80-87.
    497. Kwangmin Jung & Donggyu Kim & Seunghyeon Yu, 2021. "Next Generation Models for Portfolio Risk Management: An Approach Using Financial Big Data," Papers 2102.12783, arXiv.org, revised Feb 2022.
    498. Chandra, S. Ajay, 2009. "Testing the equality of error distributions from k independent GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1245-1260, July.
    499. Lucchetti, Riccardo & Palomba, Giulio, 2009. "Nonlinear adjustment in US bond yields: An empirical model with conditional heteroskedasticity," Economic Modelling, Elsevier, vol. 26(3), pages 659-667, May.
    500. Krishnakumar, Jaya & Kabili, Andi & Roko, Ilir, 2012. "Estimation of SEM with GARCH errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3153-3181.
    501. Matteo Barigozzi & Marc Hallin, 2015. "Generalized Dynamic Factor Models and Volatilities: Estimation and Forecasting," Working Papers ECARES ECARES 2015-22, ULB -- Universite Libre de Bruxelles.
    502. Rothonis, Stephanie & Tran, Duy & Wu, Eliza, 2016. "Does national culture affect the intensity of volatility linkages in international equity markets?," Research in International Business and Finance, Elsevier, vol. 36(C), pages 85-95.
    503. Pelster, Matthias & Vilsmeier, Johannes, 2016. "The determinants of CDS spreads: Evidence from the model space," Discussion Papers 43/2016, Deutsche Bundesbank.
    504. Romain Allez & Jean-Philippe Bouchaud, 2012. "Eigenvector dynamics: general theory and some applications," Papers 1203.6228, arXiv.org, revised Jul 2012.
    505. Claudio Morana, 2017. "Semiparametric Estimation of Multivariate GARCH Models," Working Paper series 17-02, Rimini Centre for Economic Analysis.
    506. Jaydip Sen & Sidra Mehtab & Abhishek Dutta, 2021. "Volatility Modeling of Stocks from Selected Sectors of the Indian Economy Using GARCH," Papers 2105.13898, arXiv.org.
    507. Pei Pei, 2010. "Backtesting Portfolio Value-at-Risk with Estimated Portfolio Weights," CAEPR Working Papers 2010-010, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    508. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    509. Caporin Massimiliano & Paruolo Paolo, 2005. "Spatial effects in multivariate ARCH," Economics and Quantitative Methods qf0501, Department of Economics, University of Insubria.
    510. Vica Tendenan & Richard Gerlach & Chao Wang, 2020. "Tail risk forecasting using Bayesian realized EGARCH models," Papers 2008.05147, arXiv.org, revised Aug 2020.
    511. Henri Audigé, 2013. "A new approach of contagion based on smooth transition conditional correlation GARCH models: An empirical application to the Greek crisis," Working Papers hal-04141224, HAL.
    512. Kirt Butler & Katsushi Okada, 2009. "The relative contribution of conditional mean and volatility in bivariate returns to international stock market indices," Applied Financial Economics, Taylor & Francis Journals, vol. 19(1), pages 1-15.
    513. Jun Yu & Renate Meyer, 2004. "Multivariate Stochastic Volatility Models: Bayesian Estimation and Model Comparison," Working Papers 23-2004, Singapore Management University, School of Economics.
    514. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    515. Lanne, Markku & Saikkonen, Pentti, 2005. "A Multivariate Generalized Orthogonal Factor GARCH Model," MPRA Paper 23714, University Library of Munich, Germany.
    516. John Cotter & Enrique Salvador, 2014. "The non-linear trade-off between return and risk: a regime-switching multi-factor framework," Working Papers 201414, Geary Institute, University College Dublin.
    517. Malgorzata Doman & Ryszard Doman, 2013. "The Dynamics and Strength of Linkages between the Stock Markets in the Czech Republic, Hungary and Poland after their EU Accession," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 13, pages 5-32.
    518. Bazán-Palomino, Walter, 2022. "Interdependence, contagion and speculative bubbles in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 49(C).
    519. Naseri, Marjan & Masih, Mansur, 2014. "Integration and Comovement of Developed and Emerging Islamic Stock Markets: A Case Study of Malaysia," MPRA Paper 58799, University Library of Munich, Germany.
    520. Philipp Adämmer & Martin T. Bohl & Ernst-Oliver Ledebur, 2017. "Dynamics Between North American And European Agricultural Futures Prices During Turmoil And Financialization," Bulletin of Economic Research, Wiley Blackwell, vol. 69(1), pages 57-76, January.
    521. Riadh El Abed & Sahar Boukadida & Warda Jaidane, 2019. "Financial Stress Transmission from Sovereign Credit Market to Financial Market: A Multivariate FIGARCH-DCC Approach," Global Business Review, International Management Institute, vol. 20(5), pages 1122-1140, October.
    522. Claudiu Boţoc, 2017. "Univariate and Bivariate Volatility in Central European Stock Markets," Prague Economic Papers, Prague University of Economics and Business, vol. 2017(2), pages 127-141.
    523. Massimiliano Caporin, 2007. "Variance (Non) Causality in Multivariate GARCH," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 1-24.
    524. Amel Melki & Ahmed Ghorbel, 2023. "Which Commodity Sectors Effectively Hedge Emerging Eastern European Stock Markets? Evidence from MGARCH Models," Commodities, MDPI, vol. 2(3), pages 1-19, August.
    525. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    526. 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.
    527. Markwat, T.D. & Kole, H.J.W.G. & van Dijk, D.J.C., 2009. "Time Variation in Asset Return Dependence: Strength or Structure?," ERIM Report Series Research in Management ERS-2009-052-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.
    528. Vanderlei Kleinschmidt & Roberto Meurer, 2008. "Interdependence in conditional variances between Latin American stock markets," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807211543080, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    529. Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
    530. Antypas, Antonios & Koundouri, Phoebe & Kourogenis, Nikolaos, 2011. "Volatility Trends and Optimal Portfolios: the Case of Agricultural Commodities," MPRA Paper 122420, University Library of Munich, Germany.
    531. Zexuan Yin & Paolo Barucca, 2022. "Variational Heteroscedastic Volatility Model," Papers 2204.05806, arXiv.org.
    532. Iuliana ZLATCU & Matei KUBINSCHI & Dinu BARNEA, 2015. "Fuel Price Volatility and Asymmetric Transmission of Crude Oil Price Changes to Fuel Prices," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(605), W), pages 33-44, Winter.
    533. Syed Kumail Abbas Rizvi & Bushra Naqvi & Nawazish Mirza, 2022. "Is green investment different from grey? Return and volatility spillovers between green and grey energy ETFs," Annals of Operations Research, Springer, vol. 313(1), pages 495-524, June.
    534. Škrinjarić Tihana & Šego Boško, 2016. "Dynamic Portfolio Selection on Croatian Financial Markets: MGARCH Approach," Business Systems Research, Sciendo, vol. 7(2), pages 78-90, September.
    535. Hafner, C.M. & Rombouts, J.V.K., 2004. "Estimation of temporally aggregated multivariate GARCH models," Econometric Institute Research Papers EI 2004-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    536. Piljak, Vanja & Swinkels, Laurens, 2017. "Frontier and emerging government bond markets," Emerging Markets Review, Elsevier, vol. 30(C), pages 232-255.
    537. Pami Dua & Divya Tuteja, 2016. "Contagion in International Stock and Currency Markets During Recent Crisis Episodes," Working papers 258, Centre for Development Economics, Delhi School of Economics.
    538. Alan Woodland & Kishti Sen, 2010. "The volatility of Australian traded goods' prices," Applied Economics, Taylor & Francis Journals, vol. 42(30), pages 3849-3869.
    539. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
    540. Jin, Xin & Maheu, John M., 2016. "Modeling covariance breakdowns in multivariate GARCH," Journal of Econometrics, Elsevier, vol. 194(1), pages 1-23.
    541. 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.
    542. K. Diamantopoulos & I. Vrontos, 2010. "A Student-t Full Factor Multivariate GARCH Model," Computational Economics, Springer;Society for Computational Economics, vol. 35(1), pages 63-83, January.
    543. Jean-David Fermanian, 2017. "Recent Developments in Copula Models," Econometrics, MDPI, vol. 5(3), pages 1-3, July.
    544. Valeriane Jokhadze & Wolfgang M. Schmidt, 2020. "Measuring Model Risk In Financial Risk Management And Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 1-37, April.
    545. Bahram Pesaran & M. Hashem Pesaran, 2010. "Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market Crash," CESifo Working Paper Series 3023, CESifo.
    546. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    547. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    548. Paul Catani & Timo Teräsvirta & Meiqun Yin, 2017. "A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 599-621, October.
    549. Enrique Sentana, 2018. "Volatility, Diversification and Contagion," Working Papers wp2018_1803, CEMFI.
    550. Gürtler, Marc & Rauh, Ronald, 2013. "Empirical studies in a multivariate non-stationary, nonparametric regression model for financial returns," Working Papers IF43V1, Technische Universität Braunschweig, Institute of Finance.
    551. Carroll, Rachael & Kearney, Colm, 2015. "Testing the mixture of distributions hypothesis on target stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 1-14.
    552. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    553. Harris, Richard D.F. & Mazibas, Murat, 2010. "Dynamic hedge fund portfolio construction," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 351-357, December.
    554. Ding, Liang & Vo, Minh, 2012. "Exchange rates and oil prices: A multivariate stochastic volatility analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 15-37.
    555. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    556. Matthias R. Fengler & Helmut Herwartz & Christian Werner, 2012. "A Dynamic Copula Approach to Recovering the Index Implied Volatility Skew," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 457-493, June.
    557. De Gooijer, Jan G. & Sivarajasingham, Selliah, 2008. "Parametric and nonparametric Granger causality testing: Linkages between international stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2547-2560.
    558. M. Raddant & F. Wagner, 2022. "Multivariate GARCH with dynamic beta," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1324-1343, October.
    559. Dick van Dijk & Haris Munandar & Christian Hafner, 2011. "The euro introduction and noneuro currencies," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 95-116.
    560. Josip Arneric & Elza Jurun & Snježana Pivac, 2008. "Multivariate Risk-Return Decision Making Within Dynamic Estimation," Economic Analysis Working Papers (2002-2010). Atlantic Review of Economics (2011-2016), Colexio de Economistas de A Coruña, Spain and Fundación Una Galicia Moderna, vol. 7, pages 1-11, October.
    561. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.
    562. Dendramis, Yiannis & Kapetanios, George & Tzavalis, Elias, 2014. "Level shifts in stock returns driven by large shocks," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 41-51.
    563. Nguyen, Hoang & Virbickaite, Audrone, 2022. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Working Papers 2022:5, Örebro University, School of Business.
    564. Irfan Akbar Kazi & Suzanne Salloy, 2013. "Contagion effect due to Lehman Brothers’ bankruptcy and the global financial crisis - From the perspective of the Credit Default Swaps’ G14 dealers," Working Papers hal-04141216, HAL.
    565. Liu, Ruipeng & Lux, Thomas, 2017. "Generalized Method of Moment estimation of multivariate multifractal models," Economic Modelling, Elsevier, vol. 67(C), pages 136-148.
    566. E.M. Afsal & Mohammad Imdadul Haque, 2016. "Market Interactions in Gold and Stock Markets: Evidences from Saudi Arabia," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1025-1034.
    567. Kenichiro Shiraya & Kanji Suzuki & Tomohisa Yamakami, 2024. "New approaches of the DCC-GARCH residual: Application to foreign exchange rates," Papers 2411.08246, arXiv.org.
    568. Anindya Chakrabarty & Anupam De & Gautam Bandyopadhyay, 2015. "A Wavelet-based MRA-EDCC-GARCH Methodology for the Detection of News and Volatility Spillover across Sectoral Indices—Evidence from the Indian Financial Market," Global Business Review, International Management Institute, vol. 16(1), pages 35-49, February.
    569. Kyriaki Begiazi & Dimitrios Asteriou & Keith Pilbeam, 2016. "A multivariate analysis of United States and global real estate investment trusts," International Economics and Economic Policy, Springer, vol. 13(3), pages 467-482, July.
    570. Caporin, Massimiliano, 2013. "Equity and CDS sector indices: Dynamic models and risk hedging," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 261-275.
    571. Menelaos Karanasos & Ning Zeng, 2013. "Conditional heteroskedasticity in macroeconomics data: UK inflation, output growth and their uncertainties," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 12, pages 266-288, Edward Elgar Publishing.
    572. Luc, BAUWENS & C.M., HAFNER & J.V.K., ROMBOUTS, 2006. "Multivariate mixed normal conditional heteroskedasticity," Discussion Papers (ECON - Département des Sciences Economiques) 2006007, Université catholique de Louvain, Département des Sciences Economiques.
    573. BAUWENS, Luc & BEN OMRANE, Walid & RENGIFO, Erick, 2006. "Intra-daily FX optimal portfolio allocation," LIDAM Discussion Papers CORE 2006010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    574. Peri, M. & Vandone, D. & Baldi, L., 2015. "Volatility Spillover between Water, Food and Energy," 2015 Conference, August 9-14, 2015, Milan, Italy 212627, International Association of Agricultural Economists.
    575. Poloni, Federico & Sbrana, Giacomo, 2014. "Feasible generalized least squares estimation of multivariate GARCH(1, 1) models," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 151-159.
    576. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.
    577. Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers 21-21, Federal Reserve Bank of Philadelphia.
    578. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    579. Hira Aftab & A. B. M. Rabiul Alam Beg, 2021. "Does Time Varying Risk Premia Exist in the International Bond Market? An Empirical Evidence from Australian and French Bond Market," IJFS, MDPI, vol. 9(1), pages 1-13, January.
    580. Ronald A. Ratti & M. Zahid Hasan, 2013. "Oil Price Shocks and Volatility in Australian Stock Returns," The Economic Record, The Economic Society of Australia, vol. 89, pages 67-83, June.
    581. Weng, Haijie & Trück, Stefan, 2011. "Style analysis and Value-at-Risk of Asia-focused hedge funds," Pacific-Basin Finance Journal, Elsevier, vol. 19(5), pages 491-510, November.
    582. Xiarchos, Irene M. & Fletcher, Jerald J., 2009. "Price and volatility transmission between primary and scrap metal markets," Resources, Conservation & Recycling, Elsevier, vol. 53(12), pages 664-673.
    583. García-Ferrer, Antonio & González-Prieto, Ester & Peña, Daniel, 2012. "A conditionally heteroskedastic independent factor model with an application to financial stock returns," International Journal of Forecasting, Elsevier, vol. 28(1), pages 70-93.
    584. Luis Fernando Melo Velandia & Oscar Reinaldo Becerra Camargo, 2006. "Una aproximación a la dinámica de las tasas de interés de corto plazo en Colombia a través de modelos GARCH multivariados," Borradores de Economia 366, Banco de la Republica de Colombia.
    585. Grout, Paul A. & Zalewska, Anna, 2016. "Stock market risk in the financial crisis," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 326-345.
    586. Li, Hong, 2012. "The impact of China's stock market reforms on its international stock market linkages," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(4), pages 358-368.
    587. Restrepo E., María Isabel, 2012. "Estimating Portfolio Value at Risk with GARCH and MGARCH models," Perfil de Coyuntura Económica, Universidad de Antioquia, CIE, issue 19, pages 77-92, July.
    588. Helmut Lütkepohl & Thore Schlaak, 2018. "Choosing Between Different Time‐Varying Volatility Models for Structural Vector Autoregressive Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(4), pages 715-735, August.
    589. Burda Martin, 2015. "Constrained Hamiltonian Monte Carlo in BEKK GARCH with Targeting," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 95-113, January.
    590. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
    591. Kris Boudt & Dries Cornilly & Tim Verdonck, 2019. "Nearest Comoment Estimation With Unobserved Factors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/970, Ghent University, Faculty of Economics and Business Administration.
    592. Michel Beine & Pierre-Yves Preumont & Ariane Szafarz, 2006. "Sector diversification during crises: a European perspective," DULBEA Working Papers 06-07.RS, ULB -- Universite Libre de Bruxelles.
    593. Kalu O. Emenike, 2021. "Interdependence among West African stock markets: A dimension of regional financial integration," African Development Review, African Development Bank, vol. 33(2), pages 288-299, June.
    594. Riadh El Abed, 2017. "On the Co-movements among East Asian Foreign Exchange Markets: A Multivariate FIAPARCH-DCC approach," Economics Bulletin, AccessEcon, vol. 37(3), pages 2247-2259.
    595. Massimiliano Caporin & Michael McAleer, 2008. "Scalar BEKK and indirect DCC," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 537-549.
    596. Escobari, Diego & Jafarinejad, Mohammad, 2018. "Investors’ Uncertainty and Stock Market Risk," MPRA Paper 86975, University Library of Munich, Germany.
    597. 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.
    598. Brechmann Eike Christain & Czado Claudia, 2013. "Risk management with high-dimensional vine copulas: An analysis of the Euro Stoxx 50," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 307-342, December.
    599. Li, Guangchen & Shen, Z.Y. & Song, Malin & Wei, Weixian, 2024. "Exploring the interconnectedness of China's new energy and stock markets: A study on volatility spillovers and dynamic correlations," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 471-484.
    600. Zhang, Yongli & Rolling, Craig & Yang, Yuhong, 2021. "Estimating and forecasting dynamic correlation matrices: A nonlinear common factor approach," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    601. Fengler, Matthias & Polivka, Jeanine, 2022. "Identifying Structural Shocks to Volatility through a Proxy-MGARCH Model," VfS Annual Conference 2022 (Basel): Big Data in Economics 264010, Verein für Socialpolitik / German Economic Association.
    602. Boubacar Maïnassara, Y. & Kadmiri, O. & Saussereau, B., 2022. "Estimation of multivariate asymmetric power GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    603. Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
    604. Apostolakis, George N. & Floros, Christos & Giannellis, Nikolaos, 2022. "On bank return and volatility spillovers: Identifying transmitters and receivers during crisis periods," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 156-176.
    605. Park, Sung Y. & Ryu, Doojin & Song, Jeongseok, 2017. "The dynamic conditional relationship between stock market returns and implied volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 638-648.
    606. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    607. M. Shabani & M. Magris & George Tzagkarakis & J. Kanniainen & A. Iosifidis, 2023. "Predicting the state of synchronization of financial time series using cross recurrence plots," Post-Print hal-04415269, HAL.
    608. Rainer Jobst & Daniel Rösch & Harald Scheule & Martin Schmelzle, 2015. "A Simple Econometric Approach for Modeling Stress Event Intensities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 300-320, April.
    609. Barigozzi, Matteo & Hallin, Marc, 2020. "Generalized dynamic factor models and volatilities: Consistency, rates, and prediction intervals," Journal of Econometrics, Elsevier, vol. 216(1), pages 4-34.
    610. Guillermo Yañez & Carlos Maquieira, 2009. "Rendimiento de Ofertas Públicas Iniciales de Acciones en Chile: Evidencia Empírica entre 1994 y 2007," Serie de Documentos de Trabajo 02, Superintendencia de Valores y Seguros.
    611. de Goeij, Peter & Marquering, Wessel, 2009. "Stock and bond market interactions with level and asymmetry dynamics: An out-of-sample application," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 318-329, March.
    612. Varga-Haszonits, I. & Kondor, I., 2007. "Noise sensitivity of portfolio selection in constant conditional correlation GARCH models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 307-318.
    613. Lorenzo-Valdes, Arturo & Ruiz-Porras, Antonio, 2011. "Modelación de los rendimientos bursátiles mexicanos mediante los modelos TGARCH y EGARCH: Un estudio econométrico para 30 acciones y el Índice de Precios y Cotizaciones [Modeling Mexican stock retu," MPRA Paper 36872, University Library of Munich, Germany.
    614. Park, Keehwan & Fang, Zhongzheng & Ho Ha, Young, 2019. "Stock and bond returns correlation in Korea: Local versus global risk during crisis periods," Journal of Asian Economics, Elsevier, vol. 65(C).
    615. HAFNER, Christian & PREMINGER, Arie, 2006. "Asymptotic theory for a factor GARCH model," LIDAM Discussion Papers CORE 2006071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    616. Heng-Hung KUO & Li-Hsing HO & Wen-Hung LIN, 2015. "Do hog breeds matter? Investigating the price volatility in the Taiwan's auction market," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(7), pages 314-325.
    617. Gregoriou, Andros & Hunter, John & Wu, Feng, 2009. "An empirical investigation of the relationship between the real economy and stock returns for the United States," Journal of Policy Modeling, Elsevier, vol. 31(1), pages 133-143.
    618. Yip, Iris W.H. & So, Mike K.P., 2009. "Simplified specifications of a multivariate generalized autoregressive conditional heteroscedasticity model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(2), pages 327-340.
    619. Frank Venmans, 2015. "Capital market response to emission allowance prices: a multivariate GARCH approach," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 17(4), pages 577-620, October.
    620. L. Bauwens & J. V. K. Rombouts, 2007. "Bayesian Clustering of Many Garch Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 365-386.
    621. Dua, Pami & Tuteja, Divya, 2016. "Financial crises and dynamic linkages across international stock and currency markets," Economic Modelling, Elsevier, vol. 59(C), pages 249-261.
    622. Paolo Guarda & Abdelaziz Rouabah, 2015. "Is the financial sector Luxembourg?s engine of growth?," BCL working papers 97, Central Bank of Luxembourg.
    623. Jin Guo & Tetsuji Tanaka, 2020. "The Effectiveness of Self-Sufficiency Policy: International Price Transmissions in Beef Markets," Sustainability, MDPI, vol. 12(15), pages 1-23, July.
    624. Indika Karunanayake & Abbas Valadkhani & Martin O'Brien, 2010. "Financial Crises And International Stock Market Volatility Transmission," Australian Economic Papers, Wiley Blackwell, vol. 49(3), pages 209-221, September.
    625. Md Shahedur R. Chowdhury & Damian S. Damianov & Diego Escobari, 2024. "Price Exuberance and Contagion across Housing Markets: Evidence from US Metropolitan Areas," The Journal of Real Estate Finance and Economics, Springer, vol. 69(1), pages 132-163, July.
    626. Zouheir Mighri, 2018. "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 427-473, June.
    627. Bai, Jushan & Chen, Zhihong, 2008. "Testing multivariate distributions in GARCH models," Journal of Econometrics, Elsevier, vol. 143(1), pages 19-36, March.
    628. Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2014. "Worldwide Evidences in the Relationships between Agriculture, Energy and Water Sectors," 2014 International European Forum, February 17-21, 2014, Innsbruck-Igls, Austria 199346, International European Forum on System Dynamics and Innovation in Food Networks.
    629. Szafranek, Karol, 2021. "Evidence on time-varying inflation synchronization," Economic Modelling, Elsevier, vol. 94(C), pages 1-13.
    630. Andrew J. Patton, 2006. "Estimation of multivariate models for time series of possibly different lengths," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 147-173.
    631. Ashfaq, Saleha & Tang, Yong & Maqbool, Rashid, 2019. "Volatility spillover impact of world oil prices on leading Asian energy exporting and importing economies’ stock returns," Energy, Elsevier, vol. 188(C).
    632. 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.
    633. Cao, Min & Conlon, Thomas, 2023. "Composite jet fuel cross-hedging," Journal of Commodity Markets, Elsevier, vol. 30(C).
    634. Marsili, Matteo & Raffaelli, Giacomo & Ponsot, Benedicte, 2009. "Dynamic instability in generic model of multi-assets markets," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1170-1181, May.
    635. Christian Hafner & Philip Hans Franses, 2009. "A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 612-631.
    636. Sergio Mayordomo & Juan Ignacio Pe�a, 2014. "An empirical analysis of dynamic dependences in the European corporate credit markets: bonds versus credit derivatives," Applied Financial Economics, Taylor & Francis Journals, vol. 24(9), pages 605-619, May.
    637. Pham, Linh, 2019. "Do all clean energy stocks respond homogeneously to oil price?," Energy Economics, Elsevier, vol. 81(C), pages 355-379.
    638. 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.
    639. Roy, Rudra Prosad & Sinha Roy, Saikat, 2017. "Financial contagion and volatility spillover: An exploration into Indian commodity derivative market," Economic Modelling, Elsevier, vol. 67(C), pages 368-380.
    640. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    641. García Ruiz, Reyna Susana & López Herrera, Francisco & Cruz Aké, Salvador, 2018. "Determinantes del crédito y la morosidad en México / Determinants of credit and defaulting in Mexico," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 8(1), pages 85-104, enero-jun.
    642. Corbet, Shaen & Gurdgiev, Constantin & Meegan, Andrew, 2018. "Long-term stock market volatility and the influence of terrorist attacks in Europe," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 118-131.
    643. Feriel Gharbi, 2019. "Time-varying volatility spillovers among bitcoin and commodity currencies," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(4), pages 1-2.
    644. Barigozzi, Matteo & Hallin, Marc, 2017. "A network analysis of the volatility of high-dimensionalfinancial series," LSE Research Online Documents on Economics 67456, London School of Economics and Political Science, LSE Library.
    645. Ågren, Martin, 2006. "Does Oil Price Uncertainty Transmit to Stock Markets?," Working Paper Series 2006:23, Uppsala University, Department of Economics.
    646. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Yoon, Seong-Min, 2014. "Dynamic spillovers among major energy and cereal commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 225-243.
    647. Tihana ŠKRINJARIĆ & Lidija DEDI & Boško ŠEGO, 2021. "Return and Volatility Spillover between Stock Prices and Exchange Rates in Croatia: A Spillover Methodology Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 93-108, December.
    648. 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).
    649. Mr. Marcus Pramor & Ms. Natalia T. Tamirisa, 2006. "Common Volatility Trends in the Central and Eastern European Currencies and the Euro," IMF Working Papers 2006/206, International Monetary Fund.
    650. Manabu Asai & Chia-Lin Chang & Michael McAleer & Laurent Pauwels, 2021. "Asymptotic and Finite Sample Properties for Multivariate Rotated GARCH Models," Econometrics, MDPI, vol. 9(2), pages 1-21, May.
    651. Massimiliano Caporin & Riccardo (Jack) Lucchetti & Giulio Palomba, 2020. "Analytical Gradients of Dynamic Conditional Correlation Models," JRFM, MDPI, vol. 13(3), pages 1-21, March.
    652. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility using state space models," Papers 0802.0223, arXiv.org.
    653. Hafner, Christian M., 2008. "Temporal aggregation of multivariate GARCH processes," Journal of Econometrics, Elsevier, vol. 142(1), pages 467-483, January.
    654. Foos, Daniel & Lütkebohmert, Eva & Markovych, Mariia & Pliszka, Kamil, 2017. "Euro area banks' interest rate risk exposure to level, slope and curvature swings in the yield curve," Discussion Papers 24/2017, Deutsche Bundesbank.
    655. Michael Mcaleer & Bernardo da Veiga, 2008. "Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 1-19.
    656. Bharat Kumar Meher & Puja Kumari & Ramona Birau & Cristi Spulbar & Abhishek Anand & Ion Florescu, 2024. "Forecasting Volatility Spillovers Using Advanced GARCH Models: Empirical Evidence for Developed Stock Markets from Austria and USA," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 1, pages 16-29.
    657. Julien Idier., 2006. "Stock exchanges industry consolidation and shock transmission," Working papers 159, Banque de France.
    658. Anne Péguin-Feissolle & Bilel Sanhaji, 2015. "Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)," Working Papers halshs-01133751, HAL.
    659. Yang Zhou & Chi Xie & Gang-Jin Wang & Jue Gong & You Zhu, 2025. "Forecasting cryptocurrency volatility: a novel framework based on the evolving multiscale graph neural network," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-52, December.
    660. Babii, Andrii & Chen, Xi & Ghysels, Eric, 2019. "Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty," Journal of Econometrics, Elsevier, vol. 212(1), pages 47-77.
    661. Denis Pelletier, 2004. "Regime Switching for Dynamic Correlations," Econometric Society 2004 North American Summer Meetings 230, Econometric Society.
    662. Almeida, Carlos & Czado, Claudia, 2012. "Efficient Bayesian inference for stochastic time-varying copula models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1511-1527.
    663. 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.
    664. Gregory Rice & Tony Wirjanto & Yuqian Zhao, 2020. "Tests for conditional heteroscedasticity of functional data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(6), pages 733-758, November.
    665. Leonidas Tsiaras, 2010. "Dynamic Models of Exchange Rate Dependence Using Option Prices and Historical Returns," CREATES Research Papers 2010-35, Department of Economics and Business Economics, Aarhus University.
    666. Anthony N. Rezitis & Panagiotis Andrikopoulos & Theodoros Daglis, 2024. "Assessing the asymmetric volatility linkages of energy and agricultural commodity futures during low and high volatility regimes," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(3), pages 451-483, March.
    667. Anton Bekkerman, 2011. "Time‐varying hedge ratios in linked agricultural markets," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 71(2), pages 179-200, August.
    668. Chakraborty, Sandip & Kakani, Ram Kumar & Sampath, Aravind, 2022. "Portfolio risk and stress across the business cycle," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    669. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    670. Dey Shubhasis & Sampath Aravind, 2017. "Dynamic Linkages between Gold and Equity Prices: Evidence from Indian Financial Services and Information Technology Companies," Working papers 251, Indian Institute of Management Kozhikode.
    671. Herwartz, Helmut & Roestel, Jan, 2018. "A structural approach to identify financial transmission in distinguished scenarios of crises," Economics Working Papers 2018-08, Christian-Albrechts-University of Kiel, Department of Economics.
    672. Cini, Federico & Ferrari, Annalisa, 2025. "Towards the estimation of ESG ratings: A machine learning approach using balance sheet ratios," Research in International Business and Finance, Elsevier, vol. 73(PB).
    673. Karunanayake, Indika & Valadkhani, Abbas & O’Brien, Martin, 2012. "GDP Growth and the Interdependency of Volatility Spillovers," MPRA Paper 50398, University Library of Munich, Germany.
    674. Jeffrey Racine, 2015. "Mixed data kernel copulas," Empirical Economics, Springer, vol. 48(1), pages 37-59, February.
    675. Pedro Raffy Vartanian, 2020. "Volatility transmission between commodities and Ibovespa in the period 2000–2016: Is there a possibility of diversification?," International Economics and Economic Policy, Springer, vol. 17(2), pages 483-501, May.
    676. Dibooglu, Sel & Cevik, Emrah I. & Gillman, Max, 2022. "Gold, silver, and the US dollar as harbingers of financial calm and distress," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 200-210.
    677. Carnero M. Angeles & Eratalay M. Hakan, 2014. "Estimating VAR-MGARCH models in multiple steps," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 339-365, May.
    678. Gloria Gonzalez-Rivera & Yun Luo, 2020. "A Truncated Mixture Transition Model for Interval-valued Time Series," Working Papers 202005, University of California at Riverside, Department of Economics.
    679. Andreou, Elena & Werker, Bas J.M., 2015. "Residual-based rank specification tests for AR–GARCH type models," Journal of Econometrics, Elsevier, vol. 185(2), pages 305-331.
    680. Monica Billio & Massimiliano Caporin, 2006. "A generalized Dynamic Conditional Correlation Model for Portfolio Risk Evaluation," Working Papers 2006_53, Department of Economics, University of Venice "Ca' Foscari".
    681. Kshitij Sharma & Yogesh K. Dwivedi & Bhimaraya Metri, 2024. "Incorporating causality in energy consumption forecasting using deep neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 537-572, August.
    682. Olson, Eric & J. Vivian, Andrew & Wohar, Mark E., 2014. "The relationship between energy and equity markets: Evidence from volatility impulse response functions," Energy Economics, Elsevier, vol. 43(C), pages 297-305.
    683. Johansson, Anders C., 2008. "Interdependencies among Asian bond markets," Journal of Asian Economics, Elsevier, vol. 19(2), pages 101-116, April.
    684. Francisco Rubio & Xavier Mestre & Daniel P. Palomar, 2011. "Performance analysis and optimal selection of large mean-variance portfolios under estimation risk," Papers 1110.3460, arXiv.org.
    685. Marcelo Scherer Perlin & Mauro Mastella & Daniel Francisco Vancin & Henrique Pinto Ramos, 2021. "A GARCH Tutorial with R," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 25(1), pages 200088-2000.
    686. Alessandra Amendola & Marinella Boccia & Vincenzo Candila & Giampiero M. Gallo, 2020. "Energy and non–energy Commodities: Spillover Effects on African Stock Markets," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-7.
    687. Pan, Zhiyuan & Wang, Yudong & Yang, Li, 2014. "Hedging crude oil using refined product: A regime switching asymmetric DCC approach," Energy Economics, Elsevier, vol. 46(C), pages 472-484.
    688. Rivera-Alonso, David & Iglesias, Emma M., 2024. "Is the Chinese crude oil spot price a good hedging tool for other crude oil prices, and in special for the main Russian oil benchmarks and during international sanctions?," Resources Policy, Elsevier, vol. 90(C).
    689. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    690. Umar, Muhammad & Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2021. "Dance with the devil? The nexus of fourth industrial revolution, technological financial products and volatility spillovers in global financial system," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    691. Mustafa Hakan Eratalay & Ariana Paola Cortés Ángel, 2022. "The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms," JRFM, MDPI, vol. 15(4), pages 1-41, March.
    692. Gamini Premaratne & Prabhath Jayasinghe, 2005. "Exchange rate exposure of stock returns at firm level," International Finance 0503004, University Library of Munich, Germany.
    693. Gloria Gonzalez-Rivera & Emre Yoldas, 2010. "Multivariate Autocontours for Specification Testing in Multivariate GARCH Models," Working Papers 201436, University of California at Riverside, Department of Economics.
    694. André A. P. Santos & Francisco J. Nogales & Esther Ruiz, 2013. "Comparing Univariate and Multivariate Models to Forecast Portfolio Value-at-Risk," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 400-441, March.
    695. Hafner, C.M. & Herwartz, H., 2003. "Analytical quasi maximum likelihood inference in multivariate volatility models," Econometric Institute Research Papers EI 2003-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    696. Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.
    697. Stefano Grassi & Francesco Violante, 2021. "Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas," CREATES Research Papers 2021-05, Department of Economics and Business Economics, Aarhus University.
    698. Christian Francq & Lajos Horváth & Jean-Michel Zakoïan, 2016. "Variance Targeting Estimation of Multivariate GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 353-382.
    699. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    700. Francisco Ortiz Arango & Alma Nelly Montiel Guzmán, 2017. "Transmission of future prices of corn of the Chicago Board of Trade to the Mexican spot market," Contaduría y Administración, Accounting and Management, vol. 62(3), pages 941-957, Julio-Sep.
    701. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2008. "Dynamic Stock Market Interactions between the Canadian, Mexican, and the United States Markets: The NAFTA Experience," Working papers 2008-49, University of Connecticut, Department of Economics.
    702. Abdoulkarim Ilmi Amir & Yacouba Boubacar Maïnassara, 2020. "Multivariate portmanteau tests for weak multiplicative seasonal VARMA models," Statistical Papers, Springer, vol. 61(6), pages 2529-2560, December.
    703. Anders Rahbek & Heino Bohn Nielsen, 2012. "Unit Root Vector Autoregression with volatility Induced Stationarity," CREATES Research Papers 2012-29, Department of Economics and Business Economics, Aarhus University.
    704. Claudio, Morana, 2018. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Working Papers 382, University of Milano-Bicocca, Department of Economics, revised 04 Jun 2018.
    705. Beatrice Franzolini & Alexandros Beskos & Maria De Iorio & Warrick Poklewski Koziell & Karolina Grzeszkiewicz, 2022. "Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market," Papers 2208.00952, arXiv.org, revised May 2023.
    706. 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.
    707. 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.
    708. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    709. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.
    710. Wei Zhou, 2017. "Dynamic and Asymmetric Contagion Reactions of Financial Markets During the Last Subprime Crisis," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 207-230, August.
    711. Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2012. "A Closed-Form Solution of the Multi-Period Portfolio Choice Problem for a Quadratic Utility Function," Papers 1207.1003, arXiv.org, revised Nov 2014.
    712. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    713. Lucchetti, Riccardo & Palomba, Giulio, 2008. "Nonlinear Adjustment in US Bond Yields: an Empirical Analysis with Conditional Heteroskedasticity," MPRA Paper 11571, University Library of Munich, Germany.
    714. Anders Johansson, 2009. "Stochastic volatility and time-varying country risk in emerging markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(3), pages 337-363.
    715. Rittler, Daniel, 2012. "Price discovery and volatility spillovers in the European Union emissions trading scheme: A high-frequency analysis," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 774-785.
    716. Rodrigo A. Morales Fernández Rafaelly & Roberto J. Santillán-Salgado, 2021. "Oil price effect on sectoral stock returns: A conditional covariance and correlation approach for Mexico," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(1), pages 1-15, Enero - M.
    717. Jean-François Carpantier & Arnaud Dufays, 2012. "Commodities volatility and the theory of storage," Working Papers hal-01821149, HAL.
    718. K. Triantafyllopoulos, 2012. "Multi‐variate stochastic volatility modelling using Wishart autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(1), pages 48-60, January.
    719. Hecq, A.W. & Laurent, S.F.J.A. & Palm, F.C., 2011. "On the univariate representation of multivariate volatility models with common factors," Research Memorandum 011, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    720. Kamel Malik Bensafta & Gervasio Semedo, 2014. "Market Volatility Transmission and Central Banking: What Happened during the Subprime Crisis?," International Economic Journal, Taylor & Francis Journals, vol. 28(4), pages 559-588, December.
    721. Matteo Bonato, 2012. "Modeling fat tails in stock returns: a multivariate stable-GARCH approach," Computational Statistics, Springer, vol. 27(3), pages 499-521, September.
    722. Donghang Luo & Ke Zhu & Huan Gong & Dong Li, 2020. "Testing error distribution by kernelized Stein discrepancy in multivariate time series models," Papers 2008.00747, arXiv.org.
    723. Hediger, Simon & Näf, Jeffrey, 2024. "Combining the MGHyp distribution with nonlinear shrinkage in modeling financial asset returns," Journal of Empirical Finance, Elsevier, vol. 77(C).
    724. Apostolos Ampountolas, 2023. "The Effect of COVID-19 on Cryptocurrencies and the Stock Market Volatility -- A Two-Stage DCC-EGARCH Model Analysis," Papers 2307.09137, arXiv.org.
    725. 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.
    726. Robert Garthoff & Iryna Okhrin & Wolfgang Schmid, 2014. "Statistical surveillance of the mean vector and the covariance matrix of nonlinear time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(3), pages 225-255, July.
    727. Weronika Ormaniec & Marcin Pitera & Sajad Safarveisi & Thorsten Schmidt, 2022. "Estimating value at risk: LSTM vs. GARCH," Papers 2207.10539, arXiv.org.
    728. Herwartz, Helmut & Roestel, Jan, 2022. "Asset prices, financial amplification and monetary policy: Structural evidence from an identified multivariate GARCH model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    729. Tran Hoang Hai, 2020. "Estimation of volatility causality in structural autoregressions with heteroskedasticity using independent component analysis," Statistical Papers, Springer, vol. 61(1), pages 1-16, February.
    730. Emenike Kalu O., 2017. "The Interrelationship between Crude Oil Price Volatility and Money Market Rate Volatility in a Developing, Oil-Producing Economy," Eastern European Business and Economics Journal, Eastern European Business and Economics Studies Centre, vol. 3(1), pages 28-47.
    731. Chakraborty, Sandip & Kakani, Ram Kumar, 2016. "Institutional investment, equity volume and volatility spillover: Causalities and asymmetries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 1-20.
    732. Stephanos Papadamou & Vangelis Arvanitis, 2015. "The effect of the market-based monetary policy transparency index on inflation and output variability," International Review of Applied Economics, Taylor & Francis Journals, vol. 29(1), pages 105-124, January.
    733. Laura Capera Romero & Anne Opschoor, 2024. "Realized Variances vs. Correlations: Unlocking the Gains in Multivariate Volatility Forecasting," Tinbergen Institute Discussion Papers 24-059/III, Tinbergen Institute.
    734. Oikonomikou, Leoni Eleni, 2018. "Modeling financial market volatility in transition markets: a multivariate case," Research in International Business and Finance, Elsevier, vol. 45(C), pages 307-322.
    735. Pierre L. Siklos, 2008. "Determinants of Emerging Market Spreads: Domestic, Global Factors, and Volatility," Working Papers 182008, Hong Kong Institute for Monetary Research.
    736. Kühl, Michael, 2009. "Excess comovements between the Euro/US dollar and British pound/US dollar exchange rates," University of Göttingen Working Papers in Economics 89, University of Goettingen, Department of Economics.
    737. Andrew Papanicolaou & Hao Fu & Prashanth Krishnamurthy & Farshad Khorrami, 2023. "A Deep Neural Network Algorithm for Linear-Quadratic Portfolio Optimization with MGARCH and Small Transaction Costs," Papers 2301.10869, arXiv.org, revised Feb 2023.
    738. Bokai Cao & Xueyuan Lin & Yiyan Qi & Chengjin Xu & Cehao Yang & Jian Guo, 2025. "Financial Wind Tunnel: A Retrieval-Augmented Market Simulator," Papers 2503.17909, arXiv.org.
    739. Salokhiddin Avazkhodjaev & Farkhod Mukhamedov & Jaloliddin Usmonov, 2022. "Do Energy and Gold Markets Interact with Islamic Stocks? Evidence from the Asia-Pacific Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 197-208, May.
    740. M. Hakan Eratalay, 2016. "Estimation of Multivariate Stochastic Volatility Models: A Comparative Monte Carlo Study," International Econometric Review (IER), Econometric Research Association, vol. 8(2), pages 19-52, September.
    741. Yuta Kurose & Yasuhiro Omori, 2018. "Multiple-lock Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1075, CIRJE, Faculty of Economics, University of Tokyo.
    742. Apostolos Serletis & Libo Xu, "undated". "Volatility and a Century of Energy Markets Dynamics," Working Papers 2016-29, Department of Economics, University of Calgary, revised 28 Jan 2016.
    743. Burhan F. Yavas & Lidija Dedi & Tihana Škrinjarić, 2022. "Did equity returns and volatilities change after the 2016 Trump election victory?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1291-1308, January.
    744. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    745. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2008. "Multivariate Gram-Charlier Densities," MPRA Paper 29073, University Library of Munich, Germany.
    746. Cheng Yu & Dong Li & Feiyu Jiang & Ke Zhu, 2023. "Matrix GARCH Model: Inference and Application," Papers 2306.05169, arXiv.org.
    747. Piet Sercu & Martina Vandebroek & Tom Vinaimont, 2008. "Thin‐Trading Effects in Beta: Bias v. Estimation Error," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(9‐10), pages 1196-1219, November.
    748. Farhat Iqbal, 2013. "Robust estimation of the simplified multivariate GARCH model," Empirical Economics, Springer, vol. 44(3), pages 1353-1372, June.
    749. Vincenzo Candila & Salvatore Farace, 2018. "On the Volatility Spillover between Agricultural Commodities and Latin American Stock Markets," Risks, MDPI, vol. 6(4), pages 1-16, October.
    750. Salles, Andre Assis de & Maria Eduarda, Silva & Paulo, Teles, 2022. "Empirical Evidence of Associations and Similarities between the National Equity Markets Indexes and Crude Oil Prices in the International Market," MPRA Paper 113589, University Library of Munich, Germany.
    751. Zaichao Du & Pei Pei, 2020. "Backtesting portfolio value‐at‐risk with estimated portfolio weights," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 605-619, September.
    752. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.
    753. Piotr Bórawski & Aneta Bełdycka-Bórawska & Lisa Holden, 2023. "Changes in the Polish Coal Sector Economic Situation with the Background of the European Union Energy Security and Eco-Efficiency Policy," Energies, MDPI, vol. 16(2), pages 1-17, January.
    754. Christos Kollias & Stephanos Papadamou & Vangelis Arvanitis, 2013. "Does Terrorism Affect the Stock‐Bond Covariance? Evidence from European Countries," Southern Economic Journal, John Wiley & Sons, vol. 79(4), pages 832-848, April.
    755. Aielli, Gian Piero & Caporin, Massimiliano, 2013. "Fast clustering of GARCH processes via Gaussian mixture models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 205-222.
    756. Onour, Ibrahim, 2012. "Volatility Spillover Across GCC Stock Markets," MPRA Paper 57086, University Library of Munich, Germany.
    757. Eraslan, Sercan & Ali, Faek Menla, 2017. "Financial crises and the dynamic linkages between stock and bond returns," Discussion Papers 17/2017, Deutsche Bundesbank.
    758. Li, Weiming & Gao, Jing & Li, Kunpeng & Yao, Qiwei, 2016. "Modelling multivariate volatilities via latent common factors," LSE Research Online Documents on Economics 68121, London School of Economics and Political Science, LSE Library.
    759. Ruey S. Tsay, 2007. "Multivariate volatility models," Papers math/0702815, arXiv.org.
    760. Stanislav Anatolyev, 2013. "Objects of nonstructural time series modeling (in Russian)," Quantile, Quantile, issue 11, pages 1-12, December.
    761. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    762. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2013. "On the Benefits of Equicorrelation for Portfolio Allocation," NCER Working Paper Series 99, National Centre for Econometric Research.
    763. Hafner, Christian M. & Herwartz, Helmut, 2006. "Volatility impulse responses for multivariate GARCH models: An exchange rate illustration," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 719-740, August.
    764. Zhang, Hanyu & Dufour, Alfonso, 2024. "Managing portfolio risk during crisis times: A dynamic conditional correlation perspective," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 241-251.
    765. Franck Martin & Jiangxingyun Zhang, 2014. "Correlation and volatility on bond markets during the EMU crisis: does the OMT change the process ?," Economics Bulletin, AccessEcon, vol. 34(2), pages 1327-1349.
    766. Van Cauwenberge Annelies & Vancauteren Mark & Braekers Roel & Vandemaele Sigrid, 2022. "The degree of international trade and exchange rate exposure—Firm‐level evidence from two small open economies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3832-3850, October.
    767. Ryszard Doman, 2010. "Modeling the Dependence Structure of the WIG20 Portfolio Using a Pair-copula Construction," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 31-42.
    768. Bensafta, Kamel Malik & Semedo, Gervasio, 2009. "De la transmission de la volatilité à la contagion entre marchés boursiers : l’éclairage d’un modèle VAR non linéaire avec bris structurels en variance," L'Actualité Economique, Société Canadienne de Science Economique, vol. 85(1), pages 13-76, mars.
    769. 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.
    770. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2014. "Energy portfolio risk management using time-varying extreme value copula methods," Economic Modelling, Elsevier, vol. 38(C), pages 470-485.
    771. Vaughn Gambeta & Roy Kwon, 2020. "Risk Return Trade-Off in Relaxed Risk Parity Portfolio Optimization," JRFM, MDPI, vol. 13(10), pages 1-28, October.
    772. Hlouskova, Jaroslava & Schmidheiny, Kurt & Wagner, Martin, 2009. "Multistep predictions for multivariate GARCH models: Closed form solution and the value for portfolio management," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 330-336, March.
    773. Fernández, Begoña & Muriel, Nelson, 2009. "Regular variation and related results for the multivariate GARCH(p,q) model with constant conditional correlations," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1538-1550, August.
    774. Majdoub, Jihed & Mansour, Walid, 2014. "Islamic equity market integration and volatility spillover between emerging and US stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 452-470.
    775. Mohammad Naim Azimi, 2016. "Assessing the Exchange Rate Volatility as an External Shock to Chinese Economy," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(5), pages 277-285, May.
    776. Zouheir Mighri & Faysal Mansouri, 2014. "Modeling international stock market contagion using multivariate fractionally integrated APARCH approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-25, December.
    777. Sadorsky, Perry, 2014. "Modeling volatility and conditional correlations between socially responsible investments, gold and oil," Economic Modelling, Elsevier, vol. 38(C), pages 609-618.
    778. Brian Basvi, 2024. "Application of Copula Methods in Financial Risk Management: Case of the Zimbabwe Stock Exchange and the Victoria Falls Stock Exchange," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(5), pages 674-695, May.
    779. Kinnunen, Jyri, 2017. "Dynamic cross-autocorrelation in stock returns," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 162-173.
    780. Becker, R. & Clements, A.E. & Doolan, M.B. & Hurn, A.S., 2015. "Selecting volatility forecasting models for portfolio allocation purposes," International Journal of Forecasting, Elsevier, vol. 31(3), pages 849-861.
    781. Escobar-Anel, Marcos & Rastegari, Javad & Stentoft, Lars, 2020. "Affine multivariate GARCH models," Journal of Banking & Finance, Elsevier, vol. 118(C).
    782. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    783. Tsuji, Chikashi, 2018. "Return transmission and asymmetric volatility spillovers between oil futures and oil equities: New DCC-MEGARCH analyses," Economic Modelling, Elsevier, vol. 74(C), pages 167-185.
    784. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    785. Kevin Sheppard & Wen Xu, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    786. Seyfettin Erdoğan & Hilal Bozkurt, 2009. "The Determinants of Current Account Deficit in Turkey: An Analysis with MGARCH Models," Journal of Finance Letters (Maliye ve Finans Yazıları), Maliye ve Finans Yazıları Yayıncılık Ltd. Şti., vol. 24(84), pages 135-172, July.
    787. Oberndorfer, Ulrich, 2009. "EU Emission Allowances and the stock market: Evidence from the electricity industry," Ecological Economics, Elsevier, vol. 68(4), pages 1116-1126, February.
    788. Asai, Manabu & McAleer, Michael, 2008. "A Portfolio Index GARCH model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 449-461.
    789. Sophie Chemarin & Andreas Heinen & Eric Strobl, 2008. "Electricity, carbon and weather in France: where do we stand ?," Working Papers hal-00340171, HAL.
    790. Manner, Hans & Stark, Florian & Wied, Dominik, 2019. "Testing for structural breaks in factor copula models," Journal of Econometrics, Elsevier, vol. 208(2), pages 324-345.
    791. Massimo Peri & Daniela Vandone & Lucia Baldi, 2017. "Volatility Spillover between Water, Energy and Food," Sustainability, MDPI, vol. 9(6), pages 1-16, June.
    792. Mostafa Shabani & Martin Magris & George Tzagkarakis & Juho Kanniainen & Alexandros Iosifidis, 2022. "Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots," Papers 2210.14605, arXiv.org, revised Nov 2022.
    793. Maria Grydaki & Stilianos Fountas, 2010. "What Explains Nominal Exchange Rate Volatility? Evidence from the Latin American Countries," Discussion Paper Series 2010_10, Department of Economics, University of Macedonia, revised Jul 2010.
    794. Junran Wu & Ke Xu & Xueyuan Chen & Shangzhe Li & Jichang Zhao, 2021. "Price graphs: Utilizing the structural information of financial time series for stock prediction," Papers 2106.02522, arXiv.org, revised Nov 2021.
    795. Óscar Reinaldo Becerra & Luis Fernando Melo Velandia., 2009. "Transmisión de Tasas de Interés bajo el Esquema de Metas de Inflación: Evidencia para Colombia," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 46(133), pages 107-134.
    796. Hafner, Christian M. & Preminger, Arie, 2009. "On asymptotic theory for multivariate GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2044-2054, October.
    797. Saghaian, Sayed H. & Nemati, Mehdi & Walters, Cory G. & Chen, Bo, 2017. "Asymmetric Price Volatility Interaction between U.S. Food and Energy Markets," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258240, Agricultural and Applied Economics Association.
    798. Gkillas, Konstantinos & Tsagkanos, Athanasios & Svingou, Argyro & Siriopoulos, Costas, 2020. "Uncertainty in Euro area and the bond spreads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    799. Chunming Yuan, 2008. "The Exchange Rate and Macroeconomic Determinants: Time-Varying Transitional Dynamics," UMBC Economics Department Working Papers 09-114, UMBC Department of Economics, revised 01 Nov 2009.
    800. Wagner Oliveira Monteiro & Rodrigo De Losso da Silveira Bueno, 2011. "Dynamic Hedging inMarkov Regimes Switching," Anais do XXXVII Encontro Nacional de Economia [Proceedings of the 37th Brazilian Economics Meeting] 136, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    801. Chi Su & Richard A. Schoney & James F. Nolan, 2023. "Buy, sell or rent the farm: succession planning and the future of farming on the Great Plains," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 627-669, July.
    802. Kin-Yip Ho & Albert K Tsui, 2008. "Volatility Dynamics In Foreign Exchange Rates: Further Evidence From The Malaysian Ringgit And Singapore Dollar," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-27.
    803. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    804. Kumiega, Andrew & Neururer, Thaddeus & Van Vliet, Ben, 2011. "Independent component analysis for realized volatility: Analysis of the stock market crash of 2008," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 292-302, June.
    805. Stephanos Papadamou & Thomas Markopoulos, 2014. "Investigating Intraday Interdependence Between Gold, Silver and Three Major Currencies: the Euro, British Pound and Japanese Yen," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 20(4), pages 399-410, November.
    806. Gatfaoui, Hayette, 2013. "Translating financial integration into correlation risk: A weekly reporting's viewpoint for the volatility behavior of stock markets," Economic Modelling, Elsevier, vol. 30(C), pages 776-791.
    807. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Nicola, 2015. "Exchange rate uncertainty and international portfolio flows: A multivariate GARCH-in-mean approach," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 70-92.
    808. Maria Grydaki & Stilianos Fountas, 2010. "What Explains Output Volatility? Evidence from the G3," Discussion Paper Series 2010_09, Department of Economics, University of Macedonia, revised Jul 2010.
    809. He, Zhongfang, 2018. "A Class of Generalized Dynamic Correlation Models," MPRA Paper 84820, University Library of Munich, Germany.
    810. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.
    811. Werker, Bas J M & Andreou, Elena, 2013. "Residual-based Rank Specification Tests for AR-GARCH type models," CEPR Discussion Papers 9583, C.E.P.R. Discussion Papers.
    812. Chen, Yufeng & Xu, Jing & Hu, May, 2022. "Asymmetric volatility spillovers and dynamic correlations between crude oil price, exchange rate and gold price in BRICS," Resources Policy, Elsevier, vol. 78(C).
    813. Martin Burda & Louis Belisle, 2019. "Copula Multivariate GARCH Model with Constrained Hamiltonian Monte Carlo," Working Papers tecipa-638, University of Toronto, Department of Economics.
    814. Christian Francq & Jean-Michel Zakoïan, 2016. "Estimating multivariate volatility models equation by equation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 613-635, June.
    815. Shu-Heng Chen & Sai-Ping Li, 2011. "Econophysics: Bridges over a Turbulent Current," Papers 1107.5373, arXiv.org.
    816. Burda Martin & Bélisle Louis, 2019. "Copula multivariate GARCH model with constrained Hamiltonian Monte Carlo," Dependence Modeling, De Gruyter, vol. 7(1), pages 133-149, January.
    817. Bianchi, Michele Leonardo & De Luca, Giovanni & Rivieccio, Giorgia, 2023. "Non-Gaussian models for CoVaR estimation," International Journal of Forecasting, Elsevier, vol. 39(1), pages 391-404.
    818. Morelli, Giacomo, 2023. "Stochastic ordering of systemic risk in commodity markets," Energy Economics, Elsevier, vol. 117(C).
    819. 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.
    820. Cronin, David & Kennedy, Bernard, 2007. "Does Uncertainty Impact Money Growth? A Multivariate GARCH Analysis," Research Technical Papers 6/RT/07, Central Bank of Ireland.
    821. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    822. Delcoure, Natalya (Natasha) & Singh, Harmeet, 2016. "BRIC or CBRI: It just doesn’t sound as sexy, does it?," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 230-239.
    823. Jin Guo & Tetsuji Tanaka, 2020. "Dynamic Transmissions and Volatility Spillovers between Global Price and U.S. Producer Price in Agricultural Markets," JRFM, MDPI, vol. 13(4), pages 1-20, April.
    824. Pavković Ana & Anđelinović Mihovil & Pavković Ivan, 2019. "Achieving Portfolio Diversification through Cryptocurrencies in European Markets," Business Systems Research, Sciendo, vol. 10(2), pages 85-107, September.
    825. 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.
    826. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    827. Yi Zheng & Heng Chen, 2011. "Who is More Important – a Leading Power or a Close Neighbor?," Chapters, in: Lilai Xu (ed.), China’s Economy in the Post-WTO Environment, chapter 1, Edward Elgar Publishing.
    828. Eli Bouri & Andre Eid & Imad Kachacha, 2014. "The Dynamic Behaviour and Determinants of Linkages among Middle Eastern and North African Stock Exchanges," Economic Issues Journal Articles, Economic Issues, vol. 19(1), pages 1-22, March.
    829. Li, Dan & Drovandi, Christopher & Clements, Adam, 2024. "Outlier-robust methods for forecasting realized covariance matrices," International Journal of Forecasting, Elsevier, vol. 40(1), pages 392-408.
    830. Power, Gabriel J. & Vedenov, Dmitry V., 2008. "The Shape of the Optimal Hedge Ratio: Modeling Joint Spot-Futures Prices using an Empirical Copula-GARCH Model," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37609, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    831. Piotr Fiszeder & Witold Orzeszko, 2012. "Nonparametric Verification of GARCH-Class Models for Selected Polish Exchange Rates and Stock Indices," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(5), pages 430-449, November.
    832. Rubaiyat Ahsan Bhuiyan & Afzol Husain & Changyong Zhang, 2023. "Diversification evidence of bitcoin and gold from wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-36, December.
    833. Kris Boudt & Hong Anh Luu, 2022. "Estimation and decomposition of food price inflation risk," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 295-319, June.
    834. John Francis T. Diaz, 2018. "Volatility Dynamics in the ASEAN– China Free Trade Agreement," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(3), pages 287-306, December.
    835. Luc Bauwens & Jeroen Rombouts, 2004. "Bayesian Clustering Of Similar Multivariate Garch Models," Econometric Society 2004 North American Winter Meetings 370, Econometric Society.
    836. Zhou, Jian, 2014. "Modeling conditional covariance for mixed-asset portfolios," Economic Modelling, Elsevier, vol. 40(C), pages 242-249.
    837. Inés Jiménez & Andrés Mora-Valencia & Trino-Manuel Ñíguez & Javier Perote, 2020. "Portfolio Risk Assessment under Dynamic (Equi)Correlation and Semi-Nonparametric Estimation: An Application to Cryptocurrencies," Mathematics, MDPI, vol. 8(12), pages 1-24, November.
    838. Bhaumik, S. & Karanasos, M. & Kartsaklas, A., 2016. "The informative role of trading volume in an expanding spot and futures market," Journal of Multinational Financial Management, Elsevier, vol. 35(C), pages 24-40.
    839. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2017. "Asymmetry in spillover effects: Evidence for international stock index futures markets," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 94-111.
    840. Avinash & T. Mallikarjunappa, 2024. "Do Spot, Futures, and Options Markets Exhibit Price and Volatility Interdependence? Evidence from India," Jindal Journal of Business Research, , vol. 13(1), pages 100-117, June.
    841. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    842. 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.
    843. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan, 2022. "Dynamic volatility connectedness between thermal coal futures and major cryptocurrencies: Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    844. Felipe de Oliveira & Sinézio Fernandes Maia & Diego Pita de Jesus, 2017. "Which information matters to Market risk spreading in Brazil? Volatility transmission modeling using MGARH-BEKK, DCC, t-COPULAS," EcoMod2017 10378, EcoMod.
    845. Peters, Koen & Fleuren, H.A. & Cruijssen, Frans, 2024. "The Role of Analytics in Achieving the Sustainable Development Goal of Zero Hunger," Discussion Paper 2024-009, Tilburg University, Center for Economic Research.
    846. Ercan Özen & Özdemir Letife & Simon Grima & Frank Bezzina, 2014. "Investigating Causality Effects in Return Volatility among Five Major Futures Markets in European Countries with a Mediterranean Connection," Journal of Financial Management, Markets and Institutions, Società editrice il Mulino, issue 2, pages 207-220, December.
    847. Ahmad, Wasim & Sadorsky, Perry & Sharma, Amit, 2018. "Optimal hedge ratios for clean energy equities," Economic Modelling, Elsevier, vol. 72(C), pages 278-295.
    848. Carlo Drago & Andrea Scozzari, 2023. "A Network-Based Analysis for Evaluating Conditional Covariance Estimates," Mathematics, MDPI, vol. 11(2), pages 1-19, January.
    849. José Fernández, 2015. "Interdependence among Agricultural Commodity Markets, Macroeconomic Factors, Crude Oil and Commodity Index," Bristol Economics Discussion Papers 15/666, School of Economics, University of Bristol, UK.
    850. Oral Erdogan & Harald Schmidbauer, 2006. "Investors’ Selection Between Two Financial Markets: A Conditional Correlation Approach," Istanbul Stock Exchange Review, Research and Business Development Department, Borsa Istanbul, vol. 8(30), pages 1-18.
    851. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    852. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2014. "Instabilities in the relationships and hedging strategies between crude oil and US stock markets: Do long memory and asymmetry matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 354-366.
    853. Imtiaz Mohammad Sifat & Azhar Mohamad & Kevin Reinaldo Amin, 2021. "Intertemporal price discovery between stock index futures and spot markets: New evidence from high‐frequency data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 898-913, January.
    854. Kundu, Srikanta & Sarkar, Nityananda, 2016. "Return and volatility interdependences in up and down markets across developed and emerging countries," Research in International Business and Finance, Elsevier, vol. 36(C), pages 297-311.
    855. Debalke, Negash Mulatu, 2023. "Examining volatility and spillover effects between markets for sovereign bonds of African countries and the world’s long term interest rate," MPRA Paper 117491, University Library of Munich, Germany.
    856. Jarjour, Riad & Chan, Kung-Sik, 2020. "Dynamic conditional angular correlation," Journal of Econometrics, Elsevier, vol. 216(1), pages 137-150.
    857. Alex Huang, 2011. "Volatility Modeling by Asymmetrical Quadratic Effect with Diminishing Marginal Impact," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 301-330, March.
    858. de Goeij, P. C. & Marquering, W., 2009. "Stock and bond market interactions with level and asymmetry dynamics : An out-of-sample application," Other publications TiSEM fa1d33b9-7e68-4e15-b211-e, Tilburg University, School of Economics and Management.
    859. Gilles Zumbach, 2013. "The statistical properties of the innovations in multivariate ARCH processes in high dimensions," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 29-44, January.
    860. Acar, Elif F. & Czado, Claudia & Lysy, Martin, 2019. "Flexible dynamic vine copula models for multivariate time series data," Econometrics and Statistics, Elsevier, vol. 12(C), pages 181-197.
    861. Duong Le, 2017. "Relationship between Crude Oil Prices and the U.S. Dollar Exchange Rates: Constant or Time-varying?," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(5), pages 1-6.
    862. 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.
    863. Kamel Malik BENSAFTA & Gervasio SEMEDO, 2013. "Transmission de la volatilité et central banking : quelles réactions durant la crise des subprimes ?," LEO Working Papers / DR LEO 1694, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    864. Benavides Guillermo & Capistrán Carlos, 2009. "A Note on the Volatilities of the Interest Rate and the Exchange Rate Under Different Monetary Policy Instruments: Mexico 1998-2008," Working Papers 2009-10, Banco de México.
    865. Dangxing Chen, 2019. "Does the leverage effect affect the return distribution?," Papers 1909.08662, arXiv.org, revised Sep 2019.
    866. Pape, Katharina & Wied, Dominik & Galeano, Pedro, 2016. "Monitoring multivariate variance changes," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 54-68.
    867. Bodnar, Olha & Bodnar, Taras & Gupta, Arjun K., 2010. "Estimation and inference for dependence in multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 869-881, April.
    868. Adams, Zeno & Glueck, Thorsten, 2014. "Financialization in Commodity Markets: A Passing Trend or the New Normal?," Working Papers on Finance 1413, University of St. Gallen, School of Finance, revised Aug 2015.
    869. Mohini GUPTA & Purwa SRIVASTAVA & Amritkant MISHRA & Malayaranjan SAHOO, 2021. "Time-varying volatility spillover of foreign exchange rate in three Asian markets: Based on DCC-GARCH approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(629), W), pages 105-120, Winter.
    870. 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.
    871. Tehrani , Reza & Veisizadeh , Vahid, 2021. "Dynamic Cross Hedging Effectiveness between Gold and Stock Market Based on Downside Risk Measures: Evidence from Iran Emerging Capital Market," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(1), pages 43-70, March.
    872. Hafner, C.M. & Franses, Ph.H.B.F., 2003. "A generalized dynamic conditional correlation model for many asset returns," Econometric Institute Research Papers EI 2003-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    873. 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.
    874. Leonardo Chaves Borges Cardoso & Maurício Vaz Lobo Bittencourt, 2016. "Price Volatility Transmission From Oil To Energy And Non-Energy Agricultural Commodities," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 181, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    875. Al Mamun, Md & Uddin, Gazi Salah & Suleman, Muhammad Tahir & Kang, Sang Hoon, 2020. "Geopolitical risk, uncertainty and Bitcoin investment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    876. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
    877. Narayana Maharana & Ashok Kumar Panigrahi & Suman Kalyan Chaudhury, 2024. "Volatility Persistence and Spillover Effects of Indian Market in the Global Economy: A Pre- and Post-Pandemic Analysis Using VAR-BEKK-GARCH Model," JRFM, MDPI, vol. 17(7), pages 1-20, July.
    878. Zohaib Aziz & Javed Iqbal, 2017. "Testing the Dynamic Linkages of the Pakistani Stock Market with Regional and Global Markets," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 22(2), pages 89-116, July-Dec.
    879. Francq, Christian & Zakoian, Jean-Michel, 2015. "Joint inference on market and estimation risks in dynamic portfolios," MPRA Paper 68100, University Library of Munich, Germany.
    880. Bauwens, Luc & Ben Omrane, Walid & Rengifo, Erick, 2010. "Intradaily dynamic portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2400-2418, November.
    881. 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).
    882. Eddie Chi-man Hui & Xian Zheng, 2012. "The dynamic correlation and volatility of real estate price and rental: an application of MSV model," Applied Economics, Taylor & Francis Journals, vol. 44(23), pages 2985-2995, August.
    883. Zouheir Mighri & Faysal Mansouri, 2013. "Dynamic Conditional Correlation Analysis of Stock Market Contagion: Evidence from the 2007-2010 Financial Crises," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 637-661.
    884. 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.
    885. Trancoso, Tiago, 2014. "Emerging markets in the global economic network: Real(ly) decoupling?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 499-510.
    886. Nikolaus Hautsch & Ostap Okhrin & Alexander Ristig, 2023. "Maximum-Likelihood Estimation Using the Zig-Zag Algorithm," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1346-1375.
    887. G. C. Livingston & Darfiana Nur, 2023. "Bayesian inference of multivariate-GARCH-BEKK models," Statistical Papers, Springer, vol. 64(5), pages 1749-1774, October.
    888. Hafner, Christian M. & Herwartz, Helmut, 2023. "Asymmetric volatility impulse response functions," Economics Letters, Elsevier, vol. 222(C).
    889. TRENCA Ioan & PETRIA Nicolae & DEZSI Eva, 2014. "Linkages Between The Stock Markets Of Eastern Europe," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 66(1), pages 91-104.
    890. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    891. Chrétien, Stéphane & Ortega, Juan-Pablo, 2014. "Multivariate GARCH estimation via a Bregman-proximal trust-region method," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 210-236.
    892. Dey, Shubhasis & Sampath, Aravind, 2018. "Dynamic linkages between gold and equity prices: Evidence from Indian financial services and information technology companies," Finance Research Letters, Elsevier, vol. 25(C), pages 41-46.
    893. Lee, Hsiang-Tai, 2010. "Regime switching correlation hedging," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2728-2741, November.
    894. Enow, Samuel Tabot, 2023. "Exploring Volatility clustering financial markets and its implication," Journal of Economic and Social Development, Clinical Journals Press, vol. 10(02), pages 01-05, September.
    895. Lim, Siew Hoon & Turner, Peter A., 2016. "Airline Fuel Hedging: Do Hedge Horizon and Contract Maturity Matter?," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 55(01), April.
    896. Ausin, M. Concepcion & Lopes, Hedibert F., 2010. "Time-varying joint distribution through copulas," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2383-2399, November.
    897. Anshul Verma & Riccardo Junior Buonocore & Tiziana di Matteo, 2017. "A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering," Papers 1712.02138, arXiv.org, revised May 2018.
    898. Dey, Shubhasis & Sampath, Aravind, 2020. "Returns, volatility and spillover – A paradigm shift in India?," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    899. Manner, Hans & Reznikova, Olga, 2010. "Forecasting international stock market correlations: does anything beat a CCC?," Discussion Papers in Econometrics and Statistics 7/10, University of Cologne, Institute of Econometrics and Statistics.
    900. Nicolas Koch, 2014. "Dynamic linkages among carbon, energy and financial markets: a smooth transition approach," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 715-729, March.
    901. Tsang, Andrew & Yiu, Matthew S. & Nguyen, Huy Toan, 2021. "Spillover across sovereign bond markets between the US and ASEAN4 economies," Journal of Asian Economics, Elsevier, vol. 76(C).
    902. R. Ferreira, Alexandre & A. P. Santos, Andre, 2016. "On the choice of covariance specifications for portfolio selection problems," MPRA Paper 73259, University Library of Munich, Germany.
    903. Turtle, H.J. & Wang, Kainan, 2016. "The benefits of improved covariance estimation," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 233-246.
    904. Llorens-Terrazas, Jordi & Brownlees, Christian, 2023. "Projected Dynamic Conditional Correlations," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1761-1776.
    905. Nelson Yunvirusaba & Jane Aduda & Ananda Kube, 2019. "Volatility Spillover Effects among Securities Exchanges in East Africa," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(10), pages 32-41, October.
    906. Zhang, Heng-Guo & Su, Chi-Wei & Song, Yan & Qiu, Shuqi & Xiao, Ran & Su, Fei, 2017. "Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model," Economic Modelling, Elsevier, vol. 67(C), pages 355-367.
    907. Yavas, Burhan F. & Dedi, Lidija, 2016. "An investigation of return and volatility linkages among equity markets: A study of selected European and emerging countries," Research in International Business and Finance, Elsevier, vol. 37(C), pages 583-596.
    908. Hasanov, Akram Shavkatovich & Do, Hung Xuan & Shaiban, Mohammed Sharaf, 2016. "Fossil fuel price uncertainty and feedstock edible oil prices: Evidence from MGARCH-M and VIRF analysis," Energy Economics, Elsevier, vol. 57(C), pages 16-27.
    909. Bade, Alexander & Frahm, Gabriel & Jaekel, Uwe, 2008. "A general approach to Bayesian portfolio optimization," Discussion Papers in Econometrics and Statistics 1/08, University of Cologne, Institute of Econometrics and Statistics.
    910. Mensi, Walid & Nekhili, Ramzi & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Oil and precious metals: Volatility transmission, hedging, and safe haven analysis from the Asian crisis to the COVID-19 crisis," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 73-96.
    911. Shay Kee Tan & Kok Haur Ng & Jennifer So-Kuen Chan, 2022. "Predicting Returns, Volatilities and Correlations of Stock Indices Using Multivariate Conditional Autoregressive Range and Return Models," Mathematics, MDPI, vol. 11(1), pages 1-24, December.
    912. Roberto Casarin & Domenico Sartore & Marco Tronzano, 2018. "A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 101-114, January.

  41. Michel Beine & Sébastien Laurent & Christelle Lecourt, 2002. "Accounting for conditional leptokurtosis and closing days effects in FIGARCH models of daily exchange rates," ULB Institutional Repository 2013/10443, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Antonio Rubia Serrano & Trino-Manuel Ñíguez, 2003. "Forecasting The Conditional Covariance Matrix Of A Portfolio Under Long-Run Temporal Dependence," Working Papers. Serie AD 2003-34, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    2. Algieri, Bernardina, 2014. "The influence of biofuels, economic and financial factors on daily returns of commodity futures prices," Energy Policy, Elsevier, vol. 69(C), pages 227-247.
    3. Michel Beine & Agnès Bénassy-Quéré & Christelle Lecourt, 1999. "The Impact of Foreign Exchange Interventions: New Evidence from FIGARCH Estimations," Working Papers 1999-14, CEPII research center.
    4. Thierry Ane, 2006. "Short and long term components of volatility in Hong Kong stock returns," Applied Financial Economics, Taylor & Francis Journals, vol. 16(6), pages 439-460.
    5. Aneta Wlodarczyk & Iwona Otola, 2016. "Analysis of the Relationship between Market Volatility and Firms Volatility on the Polish Capital Market," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 87-116.
    6. Agnieszka Jach & Piotr Kokoszka, 2010. "Empirical wavelet analysis of tail and memory properties of LARCH and FIGARCH models," Computational Statistics, Springer, vol. 25(1), pages 163-182, March.
    7. Su, Jung-Bin & Lee, Ming-Chih & Chiu, Chien-Liang, 2014. "Why does skewness and the fat-tail effect influence value-at-risk estimates? Evidence from alternative capital markets," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 59-85.
    8. Michel Beine & Sébastien Laurent, 2000. "Structural change and long memory in volatility: new evidence from daily exchange rates," ULB Institutional Repository 2013/10473, ULB -- Universite Libre de Bruxelles.
    9. Su, Jung-Bin & Hung, Jui-Cheng, 2011. "Empirical analysis of jump dynamics, heavy-tails and skewness on value-at-risk estimation," Economic Modelling, Elsevier, vol. 28(3), pages 1117-1130, May.
    10. Imran Riaz Malik & Attaullah Shah, 2016. "Resumption of Single Stock Futures (SSFs) with Stringent Regulations and their Impact on the Risk Characteristics of the Underlying Stocks," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 8(2), pages 1-22, October.
    11. Han, Young Wook, 2007. "High frequency perspective on jump process, long memory property and temporal aggregation: Case of $-AUD exchange rates," Japan and the World Economy, Elsevier, vol. 19(2), pages 248-262, March.
    12. Selmi, Refk & Bouoiyour, Jamal & Miftah, Amal & Wohar, Mark E., 2021. "Managing exposure to volatile oil prices: Evidence from U.S. sectoral and industry-level data," Resources Policy, Elsevier, vol. 73(C).
    13. Djahoué Mangblé Gérald, 2018. "Estimating and Forecasting West Africa Stock Market Volatility Using Asymmetric GARCH Models," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(6), pages 1-4.
    14. Kang, Sang Hoon & Yoon, Seong-Min, 2007. "Long memory properties in return and volatility: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 591-600.
    15. Beine, Michel & Laurent, Sebastien, 2003. "Central bank interventions and jumps in double long memory models of daily exchange rates," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 641-660, December.
    16. Wu, Ping-Tsung & Shieh, Shwu-Jane, 2007. "Value-at-Risk analysis for long-term interest rate futures: Fat-tail and long memory in return innovations," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 248-259, March.
    17. Trino-Manuel Ñíguez, 2003. "Volatility And Var Forecasting For The Ibex-35 Stock-Return Index Using Figarch-Type Processes And Different Evaluation Criteria," Working Papers. Serie AD 2003-33, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    18. Michel Beine & Agnes Bénassy-Quéré & Christelle Lecourt, 2002. "Central Bank intervention and foreign exchange rates: new evidence from FIGARCH estimations," ULB Institutional Repository 2013/10445, ULB -- Universite Libre de Bruxelles.
    19. 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.
    20. John Francis Diaz & Jo-Hui Chen, 2017. "Testing for Long-memory and Chaos in the Returns of Currency Exchange-traded Notes (ETNs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-2.
    21. Sebastian Letmathe & Yuanhua Feng & André Uhde, . "Semiparametric GARCH models with long memory applied to value-at-risk and expected shortfall," Journal of Risk, Journal of Risk.
    22. Karanasos, Menelaos & Kim, Jinki, 2006. "A re-examination of the asymmetric power ARCH model," Journal of Empirical Finance, Elsevier, vol. 13(1), pages 113-128, January.
    23. Thompson, James R. & Wilson, James R., 2016. "Multifractal detrended fluctuation analysis: Practical applications to financial time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 126(C), pages 63-88.
    24. Dima Alberg & Haim Shalit & Rami Yosef, 2008. "Estimating stock market volatility using asymmetric GARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 18(15), pages 1201-1208.
    25. Argel S. Masa & John Francis T. Diaz, 2017. "Long-memory Modelling and Forecasting of the Returns and Volatility of Exchange-traded Notes (ETNs)," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 11(1), pages 23-53, February.
    26. Saint Kuttu, 2018. "Asymmetric mean reversion and volatility in African real exchange rates," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(3), pages 575-590, July.
    27. Malinda & Maya & Jo-Hui & Chen, 2022. "Testing for the Long Memory and Multiple Structural Breaks in Consumer ETFs," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-6.
    28. Sang Hoon Kang & Seong-Min Yoon, 2009. "Value-at-Risk Analysis for Asian Emerging Markets: Asymmetry and Fat Tails in Returns Innovation," Korean Economic Review, Korean Economic Association, vol. 25, pages 387-411.
    29. Ken Johnston & David Carter & John Hatem, 2005. "Exchange rates, and fundamental variables: a semi-parametric analysis of binary choice," Applied Economics, Taylor & Francis Journals, vol. 37(16), pages 1915-1924.
    30. Alqahtani, Abdullah & Selmi, Refk & Hongbing, Ouyang, 2021. "The financial impacts of jump processes in the crude oil price: Evidence from G20 countries in the pre- and post-COVID-19," Resources Policy, Elsevier, vol. 72(C).
    31. Palmitesta Paola & Provasi Corrado, 2004. "GARCH-type Models with Generalized Secant Hyperbolic Innovations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-19, May.

  42. BAUWENS, Luc & LAURENT, Sébastien, 2002. "A new class of multivariate skew densities, with application to GARCH models," LIDAM Discussion Papers CORE 2002020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. GIOT, Pierre & LAURENT, Sébastien, 2003. "Value-at-Risk for long and short trading positions," LIDAM Reprints CORE 1707, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Luc, BAUWENS & G., STORTI, 2007. "A Component GARCH Model with Time Varying Weights," Discussion Papers (ECON - Département des Sciences Economiques) 2007012, Université catholique de Louvain, Département des Sciences Economiques.
    3. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CARF F-Series CARF-F-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    4. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
    5. Dongming Zhu & John W. Galbraith, 2009. "Forecasting Expected Shortfall with a Generalized Asymmetric Student-t Distribution," CIRANO Working Papers 2009s-24, CIRANO.
    6. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
    7. Eric Jondeau & Michael Rockinger, 2006. "Optimal Portfolio Allocation under Higher Moments," European Financial Management, European Financial Management Association, vol. 12(1), pages 29-55, January.
    8. Bal??zs ??gert & Ev??en Kocenda, 2007. "Time-Varying Comovements in Developed and Emerging European Stock Markets: Evidence from Intraday Data," William Davidson Institute Working Papers Series wp861, William Davidson Institute at the University of Michigan.
    9. Boswijk, H.P. & Weide, R. van der, 2006. "Wake me up before you GO-GARCH," CeNDEF Working Papers 06-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    10. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    11. Dongming Zhu & John W. Galbraith, 2009. "A Generalized Asymmetric Student-t Distribution with Application to Financial Econometrics," CIRANO Working Papers 2009s-13, CIRANO.
    12. Eric Jondeau & Michael Rockinger, 2002. "Conditional Dependency of Financial Series: The Copula-GARCH Model," FAME Research Paper Series rp69, International Center for Financial Asset Management and Engineering.
    13. Choi, Pilsun & Nam, Kiseok, 2008. "Asymmetric and leptokurtic distribution for heteroscedastic asset returns: The SU-normal distribution," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 41-63, January.
    14. Kai-Li Wang & Mei-Ling Chen, 2007. "The dynamics in the spot, futures, and call options with basis asymmetries: an intraday analysis in a generalized multivariate GARCH-M MSKST framework," Review of Quantitative Finance and Accounting, Springer, vol. 29(4), pages 371-394, November.
    15. GARCIA, René & RENAULT, Eric & VEREDAS, David, 2006. "Estimation of stable distributions by indirect inference," LIDAM Discussion Papers CORE 2006112, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Fantazzini, Dean, 2008. "An Econometric Analysis of Financial Data in Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 10(2), pages 91-137.
    17. Sentana, Enrique & Mencía, Javier, 2005. "Estimation and Testing of Dynamic Models with Generalized Hyperbolic Innovations," CEPR Discussion Papers 5177, C.E.P.R. Discussion Papers.
    18. Jose T.A.S. Ferreira & Mark F.J. Steel, 2004. "Bayesian Multivariate Regression Analysis with a New Class of Skewed Distributions," Econometrics 0403001, University Library of Munich, Germany.
    19. Eric Jondeau & Michael Rockinger, 2005. "Conditional Asset Allocation under Non-Normality: How Costly is the Mean-Variance Criterion?," FAME Research Paper Series rp132, International Center for Financial Asset Management and Engineering.
    20. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    21. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    22. BAUWENS, Luc & BEN OMRANE, Walid & RENGIFO, Erick, 2006. "Intra-daily FX optimal portfolio allocation," LIDAM Discussion Papers CORE 2006010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    23. 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.
    24. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    25. LOMBARDI, Marco & VEREDAS, David, 2007. "Indirect estimation of elliptical stable distributions," LIDAM Discussion Papers CORE 2007018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    26. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2008. "Dynamic Stock Market Interactions between the Canadian, Mexican, and the United States Markets: The NAFTA Experience," Working papers 2008-49, University of Connecticut, Department of Economics.
    27. 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.
    28. Philippe Lambert & Sébastien Laurent, 2008. "Testing Conditional Dynamics in Asymmetry. A Residual-Based Approach," Working Papers ECARES 2008_009, ULB -- Universite Libre de Bruxelles.
    29. Harvey, A. & Chakravarty, T., 2008. "Beta-t-(E)GARCH," Cambridge Working Papers in Economics 0840, Faculty of Economics, University of Cambridge.
    30. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    31. Michal Kaut & Stein Wallace, 2011. "Shape-based scenario generation using copulas," Computational Management Science, Springer, vol. 8(1), pages 181-199, April.
    32. Lai, Jing-yi, 2012. "Shock-dependent conditional skewness in international aggregate stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 72-83.
    33. Zhu, Dongming & Galbraith, John W., 2011. "Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 765-778, September.

  43. GIOT, Pierre & LAURENT, Sébastien, 2001. "Value-at-risk for long and short trading positions," LIDAM Discussion Papers CORE 2001022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    2. Nieto, María Rosa & Ruiz Ortega, Esther, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," DES - Working Papers. Statistics and Econometrics. WS ws087326, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
    4. Atukorala, Ranjani & Sriananthakumar, Sivagowry, 2015. "A comparison of the accuracy of asymptotic approximations in the dynamic regression model using Kullback-Leibler information," Economic Modelling, Elsevier, vol. 45(C), pages 169-174.
    5. Sylvain Benoît & Christophe Hurlin & Christophe Pérignon, 2014. "Implied Risk Exposures," Working Papers halshs-00836280, HAL.
    6. Degiannakis, Stavros & Floros, Christos & Dent, Pamela, 2013. "Forecasting Value-at-Risk and Expected Shortfall using Fractionally Integrated Models of Conditional Volatility: International Evidence," MPRA Paper 80433, University Library of Munich, Germany.
    7. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    8. Marno Verbeek & Jeroen VK Rombouts, 2005. "Evaluating Portfolio Value-at-Risk using Semi-Parametric GARCH Models," Computing in Economics and Finance 2005 40, Society for Computational Economics.
    9. Luc, BAUWENS & G., STORTI, 2007. "A Component GARCH Model with Time Varying Weights," Discussion Papers (ECON - Département des Sciences Economiques) 2007012, Université catholique de Louvain, Département des Sciences Economiques.
    10. Jiang, Yonghong & Nie, He & Monginsidi, Joe Yohanes, 2017. "Co-movement of ASEAN stock markets: New evidence from wavelet and VMD-based copula tests," Economic Modelling, Elsevier, vol. 64(C), pages 384-398.
    11. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, June.
    12. 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.
    13. Kulp-Tåg, Sofie, 2007. "An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions," Working Papers 526, Hanken School of Economics.
    14. F. Blasques & Christian Francq & Sébastien Laurent, 2023. "Quasi score-driven models," Post-Print hal-04069143, HAL.
    15. Anupam Dutta, 2025. "Assessing the Risk of Bitcoin Futures Market: New Evidence," Annals of Data Science, Springer, vol. 12(2), pages 481-497, April.
    16. Degiannakis, Stavros & Potamia, Artemis, 2017. "Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 176-190.
    17. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2015. "A comparison of Expected Shortfall estimation models," Journal of Economics and Business, Elsevier, vol. 78(C), pages 14-47.
    18. Grané, A. & Veiga, H., 2008. "Accurate minimum capital risk requirements: A comparison of several approaches," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2482-2492, November.
    19. Bei, Shuhua & Yang, Aijun & Pei, Haotian & Si, Xiaoli, 2023. "Price Risk Analysis using GARCH Family Models: Evidence from Shanghai Crude Oil Futures Market," Economic Modelling, Elsevier, vol. 125(C).
    20. Onour, Ibrahim, 2009. "Extreme Risk and Fat-tails Distribution Model:Empirical Analysis," MPRA Paper 17736, University Library of Munich, Germany, revised 20 Sep 2009.
    21. Angelidis, Timotheos & Degiannakis, Stavros, 2008. "Volatility forecasting: Intra-day versus inter-day models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 449-465, December.
    22. Tat’yana Serebryakova Yur’evna & Татьяна Серебрякова Юрьевна, 2018. "Научно-методический аспект учета рисков организации // Scientific and Methodological Aspectsof Risk Accounting in an Organization," Учет. Анализ. Аудит // Accounting. Analysis. Auditing, ФГОБУВО "Финансовый университет при Правительстве Российской Федерации" // Financial University under The Government of Russian Federation, vol. 5(1), pages 44-55.
    23. Jeroen Rombouts & E.W. Rengifo, 2004. "Dynamic Optimal Portfolio Selection in a VaR Framework," Cahiers de recherche 04-05, HEC Montréal, Institut d'économie appliquée.
    24. Emilio Cardona & Andrés Mora-Valencia & Daniel Velásquez-Gaviria, 2019. "Testing expected shortfall: an application to emerging market stock indices," Risk Management, Palgrave Macmillan, vol. 21(3), pages 153-182, September.
    25. Lima, Luiz Renato & Néri, Breno Pinheiro, 2007. "Comparing Value-at-Risk Methodologies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 27(1), May.
    26. Anastassios A. Drakos & Georgios P. Kouretas & Leonidas P. Zarangas, 2010. "Forecasting financial volatility of the Athens stock exchange daily returns: an application of the asymmetric normal mixture GARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 331-350.
    27. Degiannakis, Stavros & Dent, Pamela & Floros, Christos, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," MPRA Paper 80431, University Library of Munich, Germany.
    28. Maghyereh Aktham Issa & Awartani Basel, 2012. "Modeling and Forecasting Value-at-Risk in the UAE Stock Markets: The Role of Long Memory, Fat Tails and Asymmetries in Return Innovations," Review of Middle East Economics and Finance, De Gruyter, vol. 8(1), pages 1-22, August.
    29. David Ardia & S'ebastien Laurent & Rosnel Sessinou, 2024. "High-Dimensional Mean-Variance Spanning Tests," Papers 2403.17127, arXiv.org.
    30. John Cotter & Jim Hanly, 2011. "Hedging Effectiveness under Conditions of Asymmetry," Working Papers 200843, Geary Institute, University College Dublin.
    31. YiHao Lai, 2008. "Does Asymmetric Dependence Structure Matter? A Value-at-Risk View," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(3), pages 249-268, December.
    32. Weshah Razzak, 2009. "On the GCC Currency Union," EERI Research Paper Series EERI_RP_2009_29, Economics and Econometrics Research Institute (EERI), Brussels.
    33. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    34. Armanious, Amir, 2024. "Too-systemic-to-fail: Empirical comparison of systemic risk measures in the Eurozone financial system," Journal of Financial Stability, Elsevier, vol. 73(C).
    35. Niguez, Trino-Manuel & Perote, Javier, 2004. "Forecasting the density of asset returns," LSE Research Online Documents on Economics 6845, London School of Economics and Political Science, LSE Library.
    36. Stavroyiannis, S. & Makris, I. & Nikolaidis, V. & Zarangas, L., 2012. "Econometric modeling and value-at-risk using the Pearson type-IV distribution," International Review of Financial Analysis, Elsevier, vol. 22(C), pages 10-17.
    37. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
    38. Degiannakis, Stavros, 2004. "Forecasting Realized Intra-day Volatility and Value at Risk: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 80488, University Library of Munich, Germany.
    39. Alexander, Carol & Sheedy, Elizabeth, 2008. "Developing a stress testing framework based on market risk models," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2220-2236, October.
    40. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    41. Haas, Markus, 2008. "The autocorrelation structure of the Markov-switching asymmetric power GARCH process," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1480-1489, September.
    42. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
    43. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    44. Gao, Chun-Ting & Zhou, Xiao-Hua, 2016. "Forecasting VaR and ES using dynamic conditional score models and skew Student distribution," Economic Modelling, Elsevier, vol. 53(C), pages 216-223.
    45. Grané Chávez, 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.
    46. Philippe Lambert & Sébastien Laurent & David Veredas, 2012. "Testing conditional asymmetry. A residual based approach," ULB Institutional Repository 2013/136195, ULB -- Universite Libre de Bruxelles.
    47. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    48. Patra, Saswat, 2021. "Revisiting value-at-risk and expected shortfall in oil markets under structural breaks: The role of fat-tailed distributions," Energy Economics, Elsevier, vol. 101(C).
    49. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Kang, Sang Hoon, 2016. "Global financial crisis and spillover effects among the U.S. and BRICS stock markets," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 257-276.
    50. Mr. Selim A Elekdag & Sheheryar Malik & Ms. Srobona Mitra, 2019. "Breaking the Bank? A Probabilistic Assessment of Euro Area Bank Profitability," IMF Working Papers 2019/254, International Monetary Fund.
    51. Bams, Dennis & Blanchard, Gildas & Lehnert, Thorsten, 2017. "Volatility measures and Value-at-Risk," International Journal of Forecasting, Elsevier, vol. 33(4), pages 848-863.
    52. Xiao-Ming Li & Qing Xu, 2007. "Evaluating density forecasts of the model with a conditional skewed-t distribution for China's stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 18(3), pages 213-227.
    53. Timotheos Angelidis & Stavros Degiannakis, 2005. "Modeling risk for long and short trading positions," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 6(3), pages 226-238, July.
    54. Hung, Jui-Cheng & Lee, Ming-Chih & Liu, Hung-Chun, 2008. "Estimation of value-at-risk for energy commodities via fat-tailed GARCH models," Energy Economics, Elsevier, vol. 30(3), pages 1173-1191, May.
    55. Laura Garcia-Jorcano & Alfonso Novales, 2019. "A dominance approach for comparing the performance of VaR forecasting models," Documentos de Trabajo del ICAE 2019-23, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    56. Su, Jung-Bin & Lee, Ming-Chih & Chiu, Chien-Liang, 2014. "Why does skewness and the fat-tail effect influence value-at-risk estimates? Evidence from alternative capital markets," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 59-85.
    57. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    58. Amira Akl Ahmed & Doaa Akl Ahmed, 2016. "Modelling Conditional Volatility and Downside Risk for Istanbul Stock Exchange," Working Papers 1028, Economic Research Forum, revised Jul 2016.
    59. Degiannakis, Stavros, 2018. "Multiple Days Ahead Realized Volatility Forecasting: Single, Combined and Average Forecasts," MPRA Paper 96272, University Library of Munich, Germany.
    60. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    61. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    62. Su, Jung-Bin & Hung, Jui-Cheng, 2011. "Empirical analysis of jump dynamics, heavy-tails and skewness on value-at-risk estimation," Economic Modelling, Elsevier, vol. 28(3), pages 1117-1130, May.
    63. Ergün, A. Tolga & Jun, Jongbyung, 2010. "Time-varying higher-order conditional moments and forecasting intraday VaR and Expected Shortfall," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 264-272, August.
    64. 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.
    65. Matteo Grigoletto & Francesco Lisi, 2011. "Practical implications of higher moments in risk management," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 487-506, November.
    66. Wei Kuang, 2024. "High-frequency enhanced VaR: A robust univariate realized volatility model for diverse portfolios and market conditions," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-35, May.
    67. Timotheos Angelidis & Alexandros Benos, 2006. "Liquidity adjusted value-at-risk based on the components of the bid-ask spread," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 835-851.
    68. Cheng, Wan-Hsiu & Hung, Jui-Cheng, 2011. "Skewness and leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 160-173, January.
    69. Tang, Ta-Lun & Shieh, Shwu-Jane, 2006. "Long memory in stock index futures markets: A value-at-risk approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 437-448.
    70. Kittiakarasakun, Jullavut & Tse, Yiuman, 2011. "Modeling the fat tails in Asian stock markets," International Review of Economics & Finance, Elsevier, vol. 20(3), pages 430-440, June.
    71. Ra l de Jes s-Guti rrez & Roberto J. Santill n-Salgado, 2019. "Conditional Extreme Values Theory and Tail-related Risk Measures: Evidence from Latin American Stock Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 127-141.
    72. Hammoudeh, Shawkat & Araújo Santos, Paulo & Al-Hassan, Abdullah, 2013. "Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 318-334.
    73. Su, Jung-Bin, 2014. "Empirical analysis of long memory, leverage, and distribution effects for stock market risk estimates," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 1-39.
    74. Stavros Degiannakis, 2004. "Volatility forecasting: evidence from a fractional integrated asymmetric power ARCH skewed-t model," Applied Financial Economics, Taylor & Francis Journals, vol. 14(18), pages 1333-1342.
    75. Laura Garcia‐Jorcano & Alfonso Novales, 2021. "Volatility specifications versus probability distributions in VaR forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 189-212, March.
    76. Youssef, Manel & Belkacem, Lotfi & Mokni, Khaled, 2015. "Value-at-Risk estimation of energy commodities: A long-memory GARCH–EVT approach," Energy Economics, Elsevier, vol. 51(C), pages 99-110.
    77. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    78. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    79. Zouheir Mighri & Raouf Jaziri, 2023. "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 41-97, March.
    80. Chen, Yan & Yu, Wenqiang, 2020. "Setting the margins of Hang Seng Index Futures on different positions using an APARCH-GPD Model based on extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    81. Zhijie Xiao & Roger Koenker, 2009. "Conditional Quantile Estimation for GARCH Models," Boston College Working Papers in Economics 725, Boston College Department of Economics.
    82. Bernardo León & Andrés Mora, 2011. "CDS: relación con índices accionarios y medida de riesgo," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 29(64), pages 178-211, July.
    83. Hammoudeh, Shawkat & Kang, Sang Hoon & Mensi, Walid & Nguyen, Duc Khuong, 2014. "Dynamic global linkages of the BRICS stock markets with the U.S. and Europe under external crisis shocks: Implications for portfolio risk forecasting," MPRA Paper 73400, University Library of Munich, Germany, revised Mar 2016.
    84. Deschamps, Philippe J., 2012. "Bayesian estimation of generalized hyperbolic skewed student GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3035-3054.
    85. Vasilios Sogiakas, 2017. "On the implementation of asymmetric VaR models for managing and forecasting market risk," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(6), pages 1-2.
    86. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2014. "VaR performance during the subprime and sovereign debt crises: An application to emerging markets," Emerging Markets Review, Elsevier, vol. 20(C), pages 23-41.
    87. Angelidis, Timotheos & Degiannakis, Stavros, 2007. "Backtesting VaR Models: A Τwo-Stage Procedure," MPRA Paper 80418, University Library of Munich, Germany.
    88. Djahoué Mangblé Gérald, 2018. "Estimating and Forecasting West Africa Stock Market Volatility Using Asymmetric GARCH Models," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(6), pages 1-4.
    89. Pei Pei, 2010. "Backtesting Portfolio Value-at-Risk with Estimated Portfolio Weights," CAEPR Working Papers 2010-010, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    90. Kin-Yip Ho & Ka Cheng Tsui, 2004. "Volatility Dynamics of the Tokyo Stock Exchange: A Sectoral Analysis based on the Multivariate GARCH Approach," Money Macro and Finance (MMF) Research Group Conference 2004 12, Money Macro and Finance Research Group.
    91. Panagiotis Tzouvanas & Renatas Kizys & Ioannis Chatziantoniou & Roza Sagitova, 2019. "Can Variations in Temperature Explain the Systemic Risk of European Firms?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(4), pages 1723-1759, December.
    92. Paul Bui Quang & Tony Klein & Nam H. Nguyen & Thomas Walther, 2018. "Value-at-Risk for South-East Asian Stock Markets: Stochastic Volatility vs. GARCH," JRFM, MDPI, vol. 11(2), pages 1-20, April.
    93. Giannis Vardas & Anastasios Xepapadeas, 2006. "Preserving Biodiversity: Ambiguity and Safety Rules," Working Papers 0607, University of Crete, Department of Economics.
    94. Jie Cheng, 2024. "Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3617-3643, December.
    95. Slim, Skander & Koubaa, Yosra & BenSaïda, Ahmed, 2017. "Value-at-Risk under Lévy GARCH models: Evidence from global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 30-53.
    96. Wu, Ping-Tsung & Shieh, Shwu-Jane, 2007. "Value-at-Risk analysis for long-term interest rate futures: Fat-tail and long memory in return innovations," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 248-259, March.
    97. Shawkat Hammoudeh & Sang Hoon Kang & Walid Mensi & Duc Khuong Nguyen, 2016. "Dynamic Global Linkages of the BRICS Stock Markets with the United States and Europe Under External Crisis Shocks: Implications for Portfolio Risk Forecasting," The World Economy, Wiley Blackwell, vol. 39(11), pages 1703-1727, November.
    98. Wong, Woon K., 2010. "Backtesting value-at-risk based on tail losses," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 526-538, June.
    99. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics.
    100. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    101. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    102. Catherine Bruneau & Alexis Flageollet & Zhun Peng, 2015. "Risk Factors, Copula Dependence and Risk Sensitivity of a Large Portfolio," Documents de recherche 15-03, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    103. Kurita, Takamitsu, 2014. "Dynamic characteristics of the daily yen–dollar exchange rate," Research in International Business and Finance, Elsevier, vol. 30(C), pages 72-82.
    104. Angelidis, Timotheos & Benos, Alexandros & Degiannakis, Stavros, 2007. "A Robust VaR Model under Different Time Periods and Weighting Schemes," MPRA Paper 80466, University Library of Munich, Germany.
    105. Shao, Xi-Dong & Lian, Yu-Jun & Yin, Lian-Qian, 2009. "Forecasting Value-at-Risk using high frequency data: The realized range model," Global Finance Journal, Elsevier, vol. 20(2), pages 128-136.
    106. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    107. Chaker Aloui & Hela BEN HAMIDA, 2015. "Estimation and Performance Assessment of Value-at-Risk and Expected Shortfall Based on Long-Memory GARCH-Class Models," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 30-54, January.
    108. Bali, Turan G. & Mo, Hengyong & Tang, Yi, 2008. "The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 269-282, February.
    109. Onder Buberkoku, 2018. "Examining the Value-at-risk Performance of Fractionally Integrated GARCH Models: Evidence from Energy Commodities," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 36-50.
    110. Nikkin L. Beronilla & Dennis S. Mapa, 2008. "Range-based models in estimating value-at-risk (VaR)," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 45(2), pages 87-99, December.
    111. Angelidis, Timotheos & Degiannakis, Stavros, 2008. "Volatility forecasting: intra-day vs. inter-day models," MPRA Paper 80434, University Library of Munich, Germany.
    112. Cheng-Few Lee & Jung-Bin Su, 2012. "Alternative statistical distributions for estimating value-at-risk: theory and evidence," Review of Quantitative Finance and Accounting, Springer, vol. 39(3), pages 309-331, October.
    113. Sebastian Letmathe & Yuanhua Feng & André Uhde, . "Semiparametric GARCH models with long memory applied to value-at-risk and expected shortfall," Journal of Risk, Journal of Risk.
    114. Timotheos Angelidis & Alexandros Benos, 2008. "Value-at-Risk for Greek Stocks," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 67-104, March-Jun.
    115. Karanasos, Menelaos & Kim, Jinki, 2006. "A re-examination of the asymmetric power ARCH model," Journal of Empirical Finance, Elsevier, vol. 13(1), pages 113-128, January.
    116. Pradhan, Ashis Kumar & Tiwari, Aviral Kumar, 2021. "Estimating the market risk of clean energy technologies companies using the expected shortfall approach," Renewable Energy, Elsevier, vol. 177(C), pages 95-100.
    117. van Mierlo, J.G.A., 2001. "Over de verhouding tussen overheid, marktwerking en privatisering. Een economische meta-analyse," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    118. 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.
    119. Ahmed BenSaïda & Sabri Boubaker & Duc Khuong Nguyen & Skander Slim, 2018. "Value‐at‐risk under market shifts through highly flexible models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(8), pages 790-804, December.
    120. León, Ángel & Ñíguez, Trino-Manuel, 2020. "Modeling asset returns under time-varying semi-nonparametric distributions," Journal of Banking & Finance, Elsevier, vol. 118(C).
    121. Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.
    122. 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.
    123. Francois-Éric Racicot & Raymond Théoret, 2006. "La Value-at-Risk: Modèles de la VaR, simulations en Visual Basic (Excel) et autres mesures récentes du risque de marché," RePAd Working Paper Series UQO-DSA-wp022006, Département des sciences administratives, UQO.
    124. Brooks, Robert, 2007. "Power arch modelling of the volatility of emerging equity markets," Emerging Markets Review, Elsevier, vol. 8(2), pages 124-133, May.
    125. Haas, Markus & Liu, Ji-Chun, 2015. "Theory for a Multivariate Markov--switching GARCH Model with an Application to Stock Markets," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112855, Verein für Socialpolitik / German Economic Association.
    126. Sajjad Rasoul & Coakley Jerry & Nankervis John C, 2008. "Markov-Switching GARCH Modelling of Value-at-Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-31, September.
    127. Bogdan Wlodarczyk, 2017. "Zmiennosc cen na globalnym rynku surowcow a ryzyko banku," Problemy Zarzadzania, University of Warsaw, Faculty of Management, vol. 15(66), pages 107-124.
    128. Pritsker, Matthew, 2006. "The hidden dangers of historical simulation," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 561-582, February.
    129. Dr. Ibrahim Onour, "undated". "The Global Financial Crisis and Equity Markets in Middle East Oil Exporting Countries," API-Working Paper Series 1009, Arab Planning Institute - Kuwait, Information Center.
    130. International Monetary Fund, 2018. "Euro Area Policies: Financial Sector Assessment Program-Technical Note-Systemic Risk Analysis," IMF Staff Country Reports 2018/231, International Monetary Fund.
    131. Michele Caivano & Andrew Harvey, 2014. "Time series models with an EGB2 conditional distribution," Temi di discussione (Economic working papers) 947, Bank of Italy, Economic Research and International Relations Area.
    132. Jean-François Carpantier & Arnaud Dufays, 2012. "Commodities volatility and the theory of storage," Working Papers hal-01821149, HAL.
    133. Matteo Bonato, 2012. "Modeling fat tails in stock returns: a multivariate stable-GARCH approach," Computational Statistics, Springer, vol. 27(3), pages 499-521, September.
    134. Mesut BALLIBEY & Serpil T RKYILMAZ, 2014. "Value-at-Risk Analysis in the Presence of Asymmetry and Long Memory: The Case of Turkish Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 4(4), pages 836-848.
    135. Anna Rutkowska-Ziarko & Kamila Sobieska, 2016. "Ryzyko kwantylowe wybranych otwartych akcyjnych funduszy inwestycyjnych," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 40, pages 491-502.
    136. Diamandis, Panayiotis F. & Drakos, Anastassios A. & Kouretas, Georgios P. & Zarangas, Leonidas, 2011. "Value-at-risk for long and short trading positions: Evidence from developed and emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 20(3), pages 165-176, June.
    137. Jung-Bin Su, 2014. "How to mitigate the impact of inappropriate distributional settings when the parametric value-at-risk approach is used," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 305-325, February.
    138. GIOT, Pierre & LAURENT, Sébastien, 2003. "Market risk in commodity markets: a VaR approach," LIDAM Discussion Papers CORE 2003028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    139. Philippe Lambert & Sébastien Laurent, 2008. "Testing Conditional Dynamics in Asymmetry. A Residual-Based Approach," Working Papers ECARES 2008_009, ULB -- Universite Libre de Bruxelles.
    140. Ryszard Doman, 2010. "Modeling the Dependence Structure of the WIG20 Portfolio Using a Pair-copula Construction," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 31-42.
    141. Assaf, Ata, 2015. "Value-at-Risk analysis in the MENA equity markets: Fat tails and conditional asymmetries in return distributions," Journal of Multinational Financial Management, Elsevier, vol. 29(C), pages 30-45.
    142. Fantazzini, Dean, 2009. "The effects of misspecified marginals and copulas on computing the value at risk: A Monte Carlo study," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2168-2188, April.
    143. H. Fink & S. Geissel & J. Herbinger & F. T. Seifried, 2019. "Portfolio Optimization with Optimal Expected Utility Risk Measures," Working Paper Series 2019-07, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    144. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
    145. Mahsa Gorji & Rasoul Sajjad, 2017. "Improving Value-at-Risk Estimation from the Normal EGARCH Model," Contemporary Economics, Vizja University, vol. 11(1), March.
    146. Sobreira, Nuno & Louro, Rui, 2020. "Evaluation of volatility models for forecasting Value-at-Risk and Expected Shortfall in the Portuguese stock market," Finance Research Letters, Elsevier, vol. 32(C).
    147. Wong, Woon K & Copeland, Laurence, 2008. "Risk Measurement and Management in a Crisis-Prone World," Cardiff Economics Working Papers E2008/14, Cardiff University, Cardiff Business School, Economics Section.
    148. Kuang-Liang Chang, 2011. "The optimal value-at-risk hedging strategy under bivariate regime switching ARCH framework," Applied Economics, Taylor & Francis Journals, vol. 43(21), pages 2627-2640.
    149. Higgs, Helen & Lien, Gudbrand & Worthington, Andrew C., 2015. "Australian evidence on the role of interregional flows, production capacity, and generation mix in wholesale electricity prices and price volatility," Economic Analysis and Policy, Elsevier, vol. 48(C), pages 172-181.
    150. Ravi Kashyap, 2019. "Imitation in the Imitation Game," Papers 1911.06893, arXiv.org.
    151. Grané Chávez, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    152. S. Geissel & H. Graf & J. Herbinger & F. T. Seifried, 2022. "Portfolio optimization with optimal expected utility risk measures," Annals of Operations Research, Springer, vol. 309(1), pages 59-77, February.
    153. Raggi, Davide & Bordignon, Silvano, 2006. "Comparing stochastic volatility models through Monte Carlo simulations," Computational Statistics & Data Analysis, Elsevier, vol. 50(7), pages 1678-1699, April.
    154. Panayiotis Diamandis & Georgios Kouretas & Leonidas Zarangas, 2006. "Value-at-Risk for long and short trading positions: The case of the Athens Stock Exchange," Working Papers 0601, University of Crete, Department of Economics.
    155. Jin Xisong & Lehnert Thorsten, 2018. "Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas," Dependence Modeling, De Gruyter, vol. 6(1), pages 19-46, February.
    156. Stavros Degiannakis & Alexandra Livada & Epaminondas Panas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," Applied Economics, Taylor & Francis Journals, vol. 40(23), pages 3051-3067.
    157. Shamila Jayasuriya & William Shambora & Rosemary Rossiter, 2009. "Asymmetric Volatility in Emerging and Mature Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(1), pages 25-43, April.
    158. Harvey, Andrew & Sucarrat, Genaro, 2014. "EGARCH models with fat tails, skewness and leverage," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 320-338.
    159. Sang Hoon Kang & Seong-Min Yoon, 2009. "Value-at-Risk Analysis for Asian Emerging Markets: Asymmetry and Fat Tails in Returns Innovation," Korean Economic Review, Korean Economic Association, vol. 25, pages 387-411.
    160. Biage, Milton & Nelcide, Pierre Joseph, 2020. "Effects of asset frequency components on value-at-risk in emerging and developed markets," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 40(1), August.
    161. Lejeune, Bernard, 2009. "A diagnostic m-test for distributional specification of parametric conditional heteroscedasticity models for financial data," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 507-523, June.
    162. Pitera, Marcin & Schmidt, Thorsten, 2018. "Unbiased estimation of risk," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 133-145.
    163. 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.
    164. de Araújo, André da Silva & Garcia, Maria Teresa Medeiros, 2013. "Risk contagion in the north-western and southern European stock markets," Journal of Economics and Business, Elsevier, vol. 69(C), pages 1-34.
    165. Catherine Bruneau & Alexis Flageollet & Zhun Peng, 2020. "Economic and financial risk factors, copula dependence and risk sensitivity of large multi-asset class portfolios," Annals of Operations Research, Springer, vol. 284(1), pages 165-197, January.
    166. Elekdag, Selim & Malik, Sheheryar & Mitra, Srobona, 2020. "Breaking the Bank? A Probabilistic Assessment of Euro Area Bank Profitability," Journal of Banking & Finance, Elsevier, vol. 120(C).
    167. Turan Bali & Panayiotis Theodossiou, 2007. "A conditional-SGT-VaR approach with alternative GARCH models," Annals of Operations Research, Springer, vol. 151(1), pages 241-267, April.
    168. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2014. "Semi-nonparametric VaR forecasts for hedge funds during the recent crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 330-343.
    169. Orla McCullagh & Mark Cummins & Sheila Killian, 2023. "Decoupling VaR and regulatory capital: an examination of practitioners’ experience of market risk regulation," Journal of Banking Regulation, Palgrave Macmillan, vol. 24(3), pages 321-336, September.
    170. Dariusz Gołȩbiewski & Tomasz Barszcz & Wioletta Skrodzka & Igor Wojnicki & Andrzej Bielecki, 2022. "A New Approach to Risk Management in the Power Industry Based on Systems Theory," Energies, MDPI, vol. 15(23), pages 1-19, November.
    171. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    172. Yen-Hsien Lee & Hao Fang & Wei-Fan SU, 2014. "Effectiveness of Portfolio Diversification and the Dynamic Relationship between Stock and Currency Markets in the Emerging Eastern European and Russian Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(4), pages 296-311, September.
    173. Marcin Pitera & Thorsten Schmidt, 2016. "Unbiased estimation of risk," Papers 1603.02615, arXiv.org, revised Aug 2017.
    174. Matthew Pritsker, 2001. "The hidden dangers of historical simulation," Finance and Economics Discussion Series 2001-27, Board of Governors of the Federal Reserve System (U.S.).

  44. van Mierlo, J.G.A., 2001. "Over de verhouding tussen overheid, marktwerking en privatisering. Een economische meta-analyse," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).

    Cited by:

    1. Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
    2. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    3. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    4. 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.
    5. Bauwens, Luc & Ben Omrane, Walid & Giot, Pierre, 2005. "News announcements, market activity and volatility in the euro/dollar foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1108-1125, November.
    6. Vasilios Sogiakas, 2017. "On the implementation of asymmetric VaR models for managing and forecasting market risk," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(6), pages 1-2.

  45. S»bastien Laurent and Jean-Philippe Peters, 2001. "G@RCH 2.0: An Ox Package for Estimating and Forecasting Various ARCH Models," Computing in Economics and Finance 2001 123, Society for Computational Economics.

    Cited by:

    1. GIOT, Pierre & LAURENT, Sébastien, 2003. "Value-at-Risk for long and short trading positions," LIDAM Reprints CORE 1707, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Guneratne Banda Wickremasinghe & Param Silvapulle, 2004. "Role of Exchange Rate Volatility in Exchange Rate Pass-Through to Import Prices: Some Evidence from Japan," International Finance 0406006, University Library of Munich, Germany.
    3. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    4. Anastassios A. Drakos & Georgios P. Kouretas & Leonidas P. Zarangas, 2010. "Forecasting financial volatility of the Athens stock exchange daily returns: an application of the asymmetric normal mixture GARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 331-350.
    5. Härdle, Wolfgang Karl & Mungo, Julius, 2008. "Value-at-risk and expected shortfall when there is long range dependence," SFB 649 Discussion Papers 2008-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    7. Carol Alexandra & Emese Lazar, 2004. "Normal Mixture GARCH (1,1): Application to Exchange Rate Modelling," ICMA Centre Discussion Papers in Finance icma-dp2004-05, Henley Business School, University of Reading.
    8. 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.
    9. LAURENT, Sébastien & URBAIN, Jean-Pierre, 2004. "Bridging the gap between Ox and Gauss using OxGauss," LIDAM Discussion Papers CORE 2004012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Eskandar A. Tooma, 2003. "Modeling and Forecasting Egyptian Stock Market Volatility Before and After Price Limits," Working Papers 0310, Economic Research Forum, revised Apr 2003.
    11. 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.
    12. C. R. McKenzie & Sumiko Takaoka, 2007. "EViews 5.1," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1145-1152.
    13. Agata Kliber & Barbara Bedowska-Sojka, 2013. "Economic Situation of the Country or Risk in the World Financial Market? The Dynamics of Polish Sovereign Credit Default Swap Spreads," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 13, pages 87-106.
    14. 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.
    15. Sascha Mergner & Jan Bulla, 2008. "Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 771-802.
    16. Georgios Chortareas & John Nankervis & Ying Jiang, 2007. "Forecasting Exchange Rate Volatility with High Frequency Data: Is the Euro Different?," Money Macro and Finance (MMF) Research Group Conference 2006 79, Money Macro and Finance Research Group.
    17. 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.
    18. Angelidis, Timotheos & Degiannakis, Stavros, 2007. "Backtesting VaR Models: A Τwo-Stage Procedure," MPRA Paper 80418, University Library of Munich, Germany.
    19. Menelaos Karananos & S.H Sekioua & N Zeng, 2005. "On the order of integration of monthly US ex-ante and ex-post real interest rates new evidence from over a century of data," Money Macro and Finance (MMF) Research Group Conference 2005 21, Money Macro and Finance Research Group.
    20. 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.
    21. Giannis Vardas & Anastasios Xepapadeas, 2006. "Preserving Biodiversity: Ambiguity and Safety Rules," Working Papers 0607, University of Crete, Department of Economics.
    22. Nico Katzke & Chris Garbers, 2015. "Do Long Memory and Asymmetries Matter When Assessing Downside Return Risk?," Working Papers 06/2015, Stellenbosch University, Department of Economics.
    23. Cifter, Atilla & Ozun, Alper, 2007. "The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey," MPRA Paper 2489, University Library of Munich, Germany.
    24. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    25. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics.
    26. Wang, Yuanfang & Roberts, Matthew C., 2005. "Realized Volatility in the Agricultural Futures Market," 2005 Annual meeting, July 24-27, Providence, RI 19211, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    27. Härdle, Wolfgang Karl & Mungo, Julius, 2007. "Long memory persistence in the factor of Implied volatility dynamics," SFB 649 Discussion Papers 2007-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    28. Maria Grydaki & Stilianos Fountas, 2010. "What Explains Nominal Exchange Rate Volatility? Evidence from the Latin American Countries," Discussion Paper Series 2010_10, Department of Economics, University of Macedonia, revised Jul 2010.
    29. Maria Grydaki & Stilianos Fountas, 2010. "What Explains Output Volatility? Evidence from the G3," Discussion Paper Series 2010_09, Department of Economics, University of Macedonia, revised Jul 2010.
    30. Panayiotis Diamandis & Georgios Kouretas & Leonidas Zarangas, 2006. "Value-at-Risk for long and short trading positions: The case of the Athens Stock Exchange," Working Papers 0601, University of Crete, Department of Economics.

  46. Michel Beine & Sebastien Laurent, 2000. "Structural Change and Long Memory in Volatility: New Evidence from Daily Exchange Rates," Econometric Society World Congress 2000 Contributed Papers 0312, Econometric Society.

    Cited by:

    1. Nasr, Adnen Ben & Lux, Thomas & Ajm, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the volatility of the dow jones islamic stock market index: Long memory vs. regime switching," Economics Working Papers 2014-07, Christian-Albrechts-University of Kiel, Department of Economics.
    2. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    3. Claudio Morana & Andrea Beltratti, 2006. "Structural breaks and common factors in the volatility of the Fama-French factor portfolios," Applied Financial Economics, Taylor & Francis Journals, vol. 16(14), pages 1059-1073.
    4. Mohamed Boutahar & Gilles Dufrénot & Anne Péguin-Feissolle, 2008. "A Simple Fractionally Integrated Model with a Time-varying Long Memory Parameter d t," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 225-241, April.
    5. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    6. Baillie, Richard T. & Morana, Claudio, 2009. "Modelling long memory and structural breaks in conditional variances: An adaptive FIGARCH approach," Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1577-1592, August.
    7. Morana, Claudio, 2009. "On the macroeconomic causes of exchange rate volatility," International Journal of Forecasting, Elsevier, vol. 25(2), pages 328-350.
    8. Rehim Kilic, 2011. "A conditional variance tale from an emerging economy's freely floating exchange rate," Applied Economics, Taylor & Francis Journals, vol. 43(19), pages 2465-2480.
    9. Aouad Hadjer, Soumia & Taouli, Mustapha Kamel & Benbouziane, Mohamed, 2012. "Modélisation du Comportement du Taux de Change du Dinar Algérien: Une Investigation Empirique par la Méthode ARFIMA [Modeling of the Algerian Dinar Exchange Rate: An empirical investigation using t," MPRA Paper 38605, University Library of Munich, Germany.
    10. Morana, Claudio & Beltratti, Andrea, 2004. "Structural change and long-range dependence in volatility of exchange rates: either, neither or both?," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 629-658, December.
    11. Belkhouja, Mustapha & Boutahary, Mohamed, 2011. "Modeling volatility with time-varying FIGARCH models," Economic Modelling, Elsevier, vol. 28(3), pages 1106-1116, May.
    12. Adnen Ben Nasr & Mohamed Boutahar & Abdelwahed Trabelsi, 2010. "Fractionally integrated time varying GARCH model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 399-430, August.
    13. Adnen Ben Nasr & Ahdi Noomen Ajmi & Rangan Gupta, 2014. "Modelling the volatility of the Dow Jones Islamic Market World Index using a fractionally integrated time-varying GARCH (FITVGARCH) model," Applied Financial Economics, Taylor & Francis Journals, vol. 24(14), pages 993-1004, July.
    14. Gabriel Rodríguez & Junior A. Ojeda Cunya & José Carlos Gonzáles Tanaka, 2019. "An empirical note about estimation and forecasting Latin American Forex returns volatility: the role of long memory and random level shifts components," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 18(2), pages 107-123, June.
    15. Jian Zhou, 2011. "Long memory in REIT volatility revisited: genuine or spurious, and self-similar?," Journal of Property Research, Taylor & Francis Journals, vol. 28(3), pages 213-232, January.
    16. Claudio Morana, 2007. "Estimating, Filtering and Forecasting Realized Betas," ICER Working Papers - Applied Mathematics Series 6-2007, ICER - International Centre for Economic Research.

  47. Michel Beine & Sébastien Laurent, 2000. "La persistance des chocs de volatilité sur le marché des changes s'est-elle modifiée depuis le début des années quatre-vingts ?," ULB Institutional Repository 2013/10453, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Michel Beine & Sébastien Laurent, 2000. "Structural change and long memory in volatility: new evidence from daily exchange rates," ULB Institutional Repository 2013/10473, ULB -- Universite Libre de Bruxelles.

  48. Aurélie Boubel & Sébastien Laurent & Christelle Lecourt, 2000. "L’impact des signaux de politique monétaire sur la volatilité intrajournalière du taux de change deutschemark – dollar," Documents de recherche 00-09, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.

    Cited by:

    1. Sylvie Lecarpentier Moyal & Georges Prat & Patricia Renou Maissant & Remzi Uctum, 2013. "Persistence of announcement effects on the intraday volatility of stock returns: evidence from individual data," Working Papers 2013-27, Department of Research, Ipag Business School.
    2. Sylvie Lecarpentier-Moyal & Georges Prat & Patricia Renou-Maissant & Remzi Uctum, 2013. "Persistence of announcement effects on the intraday volatility of stock returns: evidence from individual data," Working Papers hal-04141172, HAL.
    3. Darmoul Mokhtar & Nizar Harrathi, 2007. "Monetary information arrivals and intraday exchange rate volatility: a comparison of the GARCH and the EGARCH models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00174996, HAL.
    4. Darmoul Mokhtar, 2006. "The impact of monetary policy signals on the intradaily euro-dollar volatility," Post-Print halshs-00118789, HAL.
    5. Darmoul Mokhtar, 2006. "The impact of monetary policy signals on the intradaily Euro-dollar volatility," Cahiers de la Maison des Sciences Economiques bla06049, Université Panthéon-Sorbonne (Paris 1).

Articles

  1. Blasques, F. & Francq, Christian & Laurent, Sébastien, 2023. "Quasi score-driven models," Journal of Econometrics, Elsevier, vol. 234(1), pages 251-275.
    See citations under working paper version above.
  2. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2023. "We modeled long memory with just one lag!," Journal of Econometrics, Elsevier, vol. 236(1).
    See citations under working paper version above.
  3. Laurent, Sébastien & Shi, Shuping, 2022. "Unit Root Test With High-Frequency Data," Econometric Theory, Cambridge University Press, vol. 38(1), pages 113-171, February.
    See citations under working paper version above.
  4. Laurent, Sébastien & Shi, Shuping, 2020. "Volatility estimation and jump detection for drift–diffusion processes," Journal of Econometrics, Elsevier, vol. 217(2), pages 259-290.
    See citations under working paper version above.
  5. Darolles, Serge & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Journal of Econometrics, Elsevier, vol. 204(2), pages 223-247.
    See citations under working paper version above.
  6. Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
    See citations under working paper version above.
  7. Boudt, Kris & Laurent, Sébastien & Lunde, Asger & Quaedvlieg, Rogier & Sauri, Orimar, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Journal of Econometrics, Elsevier, vol. 196(2), pages 347-367.
    See citations under working paper version above.
  8. Christophe Hurlin & Sébastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2017. "Risk Measure Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 499-512, October.
    See citations under working paper version above.
  9. Hafner, Christian M. & Laurent, Sebastien & Violante, Francesco, 2017. "Weak Diffusion Limits Of Dynamic Conditional Correlation Models," Econometric Theory, Cambridge University Press, vol. 33(3), pages 691-716, June.
    See citations under working paper version above.
  10. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174.
    See citations under working paper version above.
  11. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    See citations under working paper version above.
  12. Hecq Alain & Laurent Sébastien & Palm Franz C., 2016. "On the Univariate Representation of BEKK Models with Common Factors," Journal of Time Series Econometrics, De Gruyter, vol. 8(2), pages 91-113, July.
    See citations under working paper version above.
  13. Erdemlioglu, Deniz & Laurent, Sébastien & Neely, Christopher J., 2015. "Which continuous-time model is most appropriate for exchange rates?," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 256-268.
    See citations under working paper version above.
  14. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.

    Cited by:

    1. Christophe Hurlin & Sébastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2017. "Risk Measure Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 499-512, October.
    2. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    3. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    4. Charles, Amélie & Darné, Olivier, 2019. "Volatility estimation for Bitcoin: Replication and robustness," International Economics, Elsevier, vol. 157(C), pages 23-32.
    5. Yilmaz, Mustafa K. & Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2015. "Cross-sectoral interactions in Islamic equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 1-20.
    6. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    7. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    8. Carlos Trucíos & James W. Taylor, 2023. "A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 989-1007, July.
    9. Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    10. 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.
    11. Hui Hong & Shitong Wu & Cheng Zhang, 2025. "Margin buying activity and stock market trading in China: Is there a connection?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 30(2), pages 1564-1582, April.
    12. 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.
    13. Sladana Babić & Christophe Ley & Lorenzo Ricci & David Veredas, 2023. "TailCoR: A new and simple metric for tail correlations that disentangles the linear and nonlinear dependencies that cause extreme co-movements," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-23, January.
    14. Grané Chávez, Aurea & Martín-Barragán, Belén & Veiga, Helena, 2014. "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS ws140503, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    16. Charles, Amélie & Darné, Olivier & Pop, Adrian, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Research in International Business and Finance, Elsevier, vol. 35(C), pages 33-56.
    17. Francisco Blasques & Andre Lucas & Erkki Silde, 2013. "Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models," Tinbergen Institute Discussion Papers 13-097/IV/DSF59, Tinbergen Institute.
    18. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    19. Fiszeder, Piotr & Małecka, Marta & Molnár, Peter, 2024. "Robust estimation of the range-based GARCH model: Forecasting volatility, value at risk and expected shortfall of cryptocurrencies," Economic Modelling, Elsevier, vol. 141(C).
    20. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    21. Ewa Ratuszny, 2013. "Robust Estimation in VaR Modelling - Univariate Approaches using Bounded Innovation Propagation and Regression Quantiles Methodology," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 5(1), pages 35-63, March.
    22. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2020. "On the pernicious effects of oil price uncertainty on US real economic activities," Empirical Economics, Springer, vol. 59(6), pages 2689-2715, December.
    23. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
    24. 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).
    25. Lorenzo Ricci & David Veredas, 2012. "TailCoR," Working Papers 1227, Banco de España.
      • Sla{dj}ana Babi'c & Christophe Ley & Lorenzo Ricci & David Veredas, 2020. "TailCoR," Papers 2011.14817, arXiv.org.
    26. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    27. 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.
    28. Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
    29. Spiliotis, Evangelos & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios, 2019. "Tales from tails: On the empirical distributions of forecasting errors and their implication to risk," International Journal of Forecasting, Elsevier, vol. 35(2), pages 687-698.
    30. Sylvain Barde, 2015. "A fast algorithm for finding the confidence set of large collections of models," Studies in Economics 1519, School of Economics, University of Kent.
    31. Amélie Charles & Olivier Darné, 0. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 0, pages 1-24.
    32. Christian Francq & Lajos Horváth & Jean-Michel Zakoïan, 2016. "Variance Targeting Estimation of Multivariate GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 353-382.
    33. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    34. Souhir, Ben Amor & Heni, Boubaker & Lotfi, Belkacem, 2019. "Price risk and hedging strategies in Nord Pool electricity market evidence with sector indexes," Energy Economics, Elsevier, vol. 80(C), pages 635-655.
    35. 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.
    36. Abdul Aziz, Nor Syahilla & Vrontos, Spyridon & M. Hasim, Haslifah, 2019. "Evaluation of multivariate GARCH models in an optimal asset allocation framework," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 568-596.
    37. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    38. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    39. Saker Sabkha & Christian de Peretti, 2022. "On the performances of Dynamic Conditional Correlation models in the Sovereign CDS market and the corresponding bond market," Post-Print hal-01710398, HAL.
    40. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    41. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    42. Arturo Leccadito & Alessandro Staino & Pietro Toscano, 2024. "A novel robust method for estimating the covariance matrix of financial returns with applications to risk management," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-28, December.
    43. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.

  15. Laurent, Sébastien & Rombouts, Jeroen V.K. & Violante, Francesco, 2013. "On loss functions and ranking forecasting performances of multivariate volatility models," Journal of Econometrics, Elsevier, vol. 173(1), pages 1-10.
    See citations under working paper version above.
  16. Lambert, Philippe & Laurent, Sébastien & Veredas, David, 2012. "Testing conditional asymmetry: A residual-based approach," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1229-1247.
    See citations under working paper version above.
  17. 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.

    Cited by:

    1. 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).
    2. Hans DEWACHTER & Deniz ERDEMLIOGLU & Jean-Yves GNABO & Christelle LECOURT, 2013. "The intra-day impact of communication on euro-dollar volatility and jumps," Working Papers of Department of Economics, Leuven ces13.04, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.

  18. Sébastien Laurent & Jeroen V. K. Rombouts & Francesco Violante, 2012. "On the forecasting accuracy of multivariate GARCH models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 934-955, September.
    See citations under working paper version above.
  19. 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.

    Cited by:

    1. 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.
    2. Christian Walter, 2020. "Sustainable Financial Risk Modelling Fitting the SDGs: Some Reflections," Sustainability, MDPI, vol. 12(18), pages 1-28, September.
    3. Imane El Ouadghiri & Remzi Uctum, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01386027, HAL.
    4. Machin, S. & Marie, O. & Vujic, S., 2012. "Youth crime and education expansion," Research Memorandum 036, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    5. 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.
    6. Iulia LUPU & Gheorghe HURDUZEU & Mariana NICOLAE, 2016. "Connections Between Sentiment Indices And Reduced Volatilities Of Sustainability Stock Market Indices," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(1), pages 157-174.
    7. 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).
    8. 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.
    9. 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.
    10. Fried, Roland, 2012. "On the online estimation of local constant volatilities," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3080-3090.
    11. 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.
    12. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    13. 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.
    14. Dovonon, Prosper & Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping high-frequency jump tests," TSE Working Papers 17-810, Toulouse School of Economics (TSE).
    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. Michael C. Tseng & Soheil Mahmoodzadeh, 2022. "Information Jumps, Liquidity Jumps, and Market Efficiency," JRFM, MDPI, vol. 15(3), pages 1-21, February.
    17. 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).
    18. Deniz Erdemlioglu & Nikola Gradojevic, 2020. "Heterogeneous investment horizons, risk regimes, and realized jumps," Post-Print hal-02995997, HAL.
    19. 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.
    20. 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.
    21. Novotný, Jan & Petrov, Dmitri & Urga, Giovanni, 2015. "Trading price jump clusters in foreign exchange markets," Journal of Financial Markets, Elsevier, vol. 24(C), pages 66-92.
    22. Holger Dette & Vasyl Golosnoy & Janosch Kellermann, 2023. "The effect of intraday periodicity on realized volatility measures," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(3), pages 315-342, April.
    23. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    24. Hans DEWACHTER & Deniz ERDEMLIOGLU & Jean-Yves GNABO & Christelle LECOURT, 2013. "The intra-day impact of communication on euro-dollar volatility and jumps," Working Papers of Department of Economics, Leuven ces13.04, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    25. Massimiliano Caporin & Chia-Lin Chang & Michael McAleer, 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures Related for Intra-Day Data?," Documentos de Trabajo del ICAE 2016-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    26. Sébastien Laurent & Shuping Shi, 2018. "Volatility Estimation and Jump Detection for drift-diffusion Processes," Working Papers halshs-01944449, HAL.
    27. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in Equilibrium Prices and Asymmetric News in Foreign Exchange Markets," Working Papers hal-04141414, HAL.
    28. Caporin, Massimiliano & Poli, Francesco, 2022. "News and intraday jumps: Evidence from regularization and class imbalance," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    29. 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.
    30. Ao Kong & Hongliang Zhu & Robert Azencott, 2019. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Papers 1912.07165, arXiv.org.
    31. 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.
    32. Aysan, Ahmet Faruk & Caporin, Massimiliano & Cepni, Oguzhan, 2024. "Not all words are equal: Sentiment and jumps in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    33. 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.
    34. Barbara Bedowska-Sojka, 2011. "The Impact of Macro News on Volatility of Stock Exchanges," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 99-110.
    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. Jerome Lahaye & Christopher J. Neely, 2014. "The role of jumps in volatility spillovers in foreign exchange markets: meteor shower and heat waves revisited," Working Papers 2014-034, Federal Reserve Bank of St. Louis.
    37. 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.
    38. 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.
    39. 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.
    40. 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.
    41. Kris Boudt & James Thewissen, 2019. "Jockeying for Position in CEO Letters: Impression Management and Sentiment Analytics," Financial Management, Financial Management Association International, vol. 48(1), pages 77-115, March.
    42. Ben Omrane, Walid & Saadi, Samir & Savaser, Tanseli, 2024. "Sustainable energy practices and cryptocurrency market behavior," Energy Economics, Elsevier, vol. 139(C).
    43. Boudt, Kris & Petitjean, Mikael, 2014. "Intraday liquidity dynamics and news releases around price jumps: Evidence from the DJIA stocks," LIDAM Reprints LFIN 2014006, Université catholique de Louvain, Louvain Finance (LFIN).
    44. Tsai, Ping Chen & Eom, Cheoljun & Wang, Chou Wen, 2024. "State-dependent intra-day volatility pattern and its impact on price jump detection - Evidence from international equity indices," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    45. 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.
    46. 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.
    47. 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).
    48. 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.
    49. Erdemlioglu, Deniz & Laurent, Sébastien & Neely, Christopher J., 2015. "Which continuous-time model is most appropriate for exchange rates?," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 256-268.
    50. 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.
    51. Turiel, Jeremy D. & Aste, Tomaso, 2022. "Heterogeneous criticality in high frequency finance: a phase transition in flash crashes," LSE Research Online Documents on Economics 113892, London School of Economics and Political Science, LSE Library.
    52. Lee, Suzanne S. & Wang, Minho, 2020. "Tales of tails: Jumps in currency markets," Journal of Financial Markets, Elsevier, vol. 48(C).
    53. Lucian Liviu Albu & Radu Lupu & Adrian Cantemir Călin, 2016. "Impact Of FOMC Official Speeches on the Intraday Dynamics of CDS Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-12, June.
    54. Denisa Georgiana Banulescu & Ferrara Laurent & Marsilli Clément, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," Working Papers hal-03563168, HAL.
    55. Adrian Cantemir CĂLIN & Radu LUPU, 2016. "The Effects Of Labor Market News On International Financial Markets," Romanian Economic Business Review, Romanian-American University, vol. 11(2), pages 207-215, June.
    56. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
    57. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    58. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    59. Eichler, M. & Türk, D.D.T., 2012. "Fitting semiparametric Markov regime-switching models to electricity spot prices," Research Memorandum 035, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    60. Dumitru, Ana Maria H. & Hizmeri, Rodrigo & Izzeldin, Marwan, 2025. "Forecasting the realized variance in the presence of intraday periodicity," Journal of Banking & Finance, Elsevier, vol. 170(C).
    61. Tao Chen & Kam C. Chan & Haodong Chang, 2022. "Periodicity of trading activity in foreign exchange markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(2), pages 445-465, June.
    62. 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.
    63. Noemi Nava & Tiziana Di Matteo & Tomaso Aste, 2015. "Time-dependent scaling patterns in high frequency financial data," Papers 1508.07428, arXiv.org, revised Dec 2015.
    64. 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.
    65. Usman Arief & Zaäfri Ananto Husodo, 2021. "Private Information from Extreme Price Movements (Empirical Evidences from Southeast Asia Countries)," International Symposia in Economic Theory and Econometrics, in: Recent Developments in Asian Economics International Symposia in Economic Theory and Econometrics, volume 28, pages 221-242, Emerald Group Publishing Limited.
    66. Ayadi, Mohamed A. & Ben Omrane, Walid & Das, Deepan Kumar, 2024. "Macroeconomic news, senior officials' speeches, and emerging currency markets: An intraday analysis of price jump reaction," Emerging Markets Review, Elsevier, vol. 60(C).
    67. 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.
    68. 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.
    69. 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).
    70. 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.
    71. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market instability and technical trading at high frequency: Evidence from NASDAQ stocks," Economic Modelling, Elsevier, vol. 102(C).
    72. 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.
    73. 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).
    74. Chae-Deug, Yi, 2024. "Realized normal volatility and maximum outlying jumps in high frequency returns for Korean won–US Dollar," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    75. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    76. Seema REHMAN & Saqib SHARIF & Wali ULLAH, 2023. "Relative Signed Jump and Future Stock Returns," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 25-45, March.
    77. 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).
    78. Kris Boudt & Koen Schoors & Milan van den Heuvel & Johannes Weytjens, 2023. "Taming the Zoo of Consumption Responses to Labour Income Changes," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 23/1067, Ghent University, Faculty of Economics and Business Administration.
    79. 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.
    80. 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.
    81. Zu, Yang & Peter Boswijk, H., 2014. "Estimating spot volatility with high-frequency financial data," Journal of Econometrics, Elsevier, vol. 181(2), pages 117-135.
    82. Jian Chen & Michael P Clements & Andrew Urquhart, 2024. "Modeling Price and Variance Jump Clustering Using the Marked Hawkes Process," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 743-772.
    83. Dumitru, Ana-Maria & Urga, Giovanni, 2016. "Jumps and Information Asymmetry in the US Treasury Market," EconStor Preprints 130148, ZBW - Leibniz Information Centre for Economics.
    84. Eichler, M. & Türk, D., 2013. "Fitting semiparametric Markov regime-switching models to electricity spot prices," Energy Economics, Elsevier, vol. 36(C), pages 614-624.
    85. Wu, Fan & Wang, Guan-jun & Kong, Xin-bing, 2022. "Inference on common intraday periodicity at high frequencies," Statistics & Probability Letters, Elsevier, vol. 191(C).
    86. 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.
    87. 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.
    88. Anzarut, Michelle & Mena, Ramsés H., 2019. "A Harris process to model stochastic volatility," Econometrics and Statistics, Elsevier, vol. 10(C), pages 151-169.
    89. 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.
    90. 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.
    91. 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).
    92. Walid Ben Omrane & Khaled Guesmi & Qi Qianru & Samir Saadi, 2023. "The high-frequency impact of macroeconomic news on jumps and co-jumps in the cryptocurrency markets," Annals of Operations Research, Springer, vol. 330(1), pages 177-209, November.

  20. Jérôme Lahaye & Sébastien Laurent & Christopher J. Neely, 2011. "Jumps, cojumps and macro announcements," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 893-921, September.
    See citations under working paper version above.
  21. Christophe Croux & Sébastien Laurent, 2011. "Outlyingness Weighted Covariation," Journal of Financial Econometrics, Oxford University Press, vol. 9(4), pages 657-684.
    See citations under working paper version above.
  22. 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.
    See citations under working paper version above.
  23. 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.
    See citations under working paper version above.
  24. 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.
    See citations under working paper version above.
  25. 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.
    See citations under working paper version above.
  26. Michel Beine & Charles S. Bos & Sébastien Laurent, 2007. "The Impact of Central Bank FX Interventions on Currency Components," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 154-183.
    See citations under working paper version above.
  27. Michel Beine & Jérôme Lahaye & Sébastien Laurent & Christopher J. Neely & Franz C. Palm, 2007. "Central bank intervention and exchange rate volatility, its continuous and jump components," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(2), pages 201-223.
    See citations under working paper version above.
  28. Pierre Giot & Sébastien Laurent, 2007. "The information content of implied volatility in light of the jump/continuous decomposition of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(4), pages 337-359, April.

    Cited by:

    1. Fulvio Corsi & Davide Pirino & Roberto Renò, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Post-Print hal-00741630, HAL.
    2. Ricardo Crisóstomo & Lorena Couso, 2017. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    3. Anupam Dutta, 2025. "Assessing the Risk of Bitcoin Futures Market: New Evidence," Annals of Data Science, Springer, vol. 12(2), pages 481-497, April.
    4. Özbekler, Ali Gencay & Kontonikas, Alexandros & Triantafyllou, Athanasios, 2021. "Volatility forecasting in European government bond markets," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1691-1709.
    5. Weiwei ZHANG & Tiezhu SUN & Yechi MA & Zilong WANG, 2021. "New Evidence on the Information Content of Implied Volatility of S&P 500: Model-Free versus Model-Based," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 109-121, December.
    6. 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.
    7. 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.
    8. Byun, Suk Joon & Kim, Jun Sik, 2013. "The information content of risk-neutral skewness for volatility forecasting," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 142-161.
    9. Frantiv{s}ek v{C}ech & Jozef Barun'ik, 2018. "Panel quantile regressions for estimating and predicting the Value--at--Risk of commodities," Papers 1807.11823, arXiv.org.
    10. 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.
    11. 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.
    12. Po-Chin Wu & Sheng-Chieh Pan & Xue-Ling Tai, 2015. "Non-linearity, persistence and spillover effects in stock returns: the role of the volatility index," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 597-613, August.
    13. Ahoniemi, Katja & Lanne, Markku, 2010. "Realized volatility and overnight returns," Bank of Finland Research Discussion Papers 19/2010, Bank of Finland.
    14. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian & Yoon, Seong-Min, 2021. "OPEC news and jumps in the oil market," Energy Economics, Elsevier, vol. 96(C).
    15. 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.
    16. 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.
    17. Anupam Dutta & Kakali Kanjilal & Sajal Ghosh & Donghyun Park & Gazi Salah Uddin, 2023. "Impact of crude oil volatility jumps on sustainable investments: Evidence from India," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1450-1468, October.
    18. Lim, Dominic & Durand, Robert B. & Yang, Joey Wenling, 2014. "The microstructure of fear, the Fama–French factors and the global financial crisis of 2007 and 2008," Global Finance Journal, Elsevier, vol. 25(3), pages 169-180.
    19. Kim, Jun Sik & Ryu, Doojin, 2015. "Are the KOSPI 200 implied volatilities useful in value-at-risk models?," Emerging Markets Review, Elsevier, vol. 22(C), pages 43-64.
    20. Rui Fan & Stephen J. Taylor & Matteo Sandri, 2018. "Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 83-103, January.
    21. Fassas, Athanasios P. & Siriopoulos, Costas, 2021. "Implied volatility indices – A review," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 303-329.
    22. Gaurav Raizada & Vartika Srivastava & S. V. D. Nageswara Rao, 2020. "Shall One Sit “Longer” for a Free Lunch? Impact of Trading Durations on the Realized Variances and Volatility Spillovers," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 1-28, March.
    23. Han, Heejoon & Kutan, Ali M. & Ryu, Doojin, 2015. "Effects of the US stock market return and volatility on the VKOSPI," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-34.
    24. 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.
    25. Shu-Fang Yuan, 2024. "Realized higher moments and trading activity," Review of Quantitative Finance and Accounting, Springer, vol. 62(3), pages 971-1005, April.
    26. Leonidas S. Rompolis & Elias Tzavalis, 2010. "Risk Premium Effects On Implied Volatility Regressions," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(2), pages 125-151, June.
    27. Dehua Shen & Andrew Urquhart & Pengfei Wang, 2020. "Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks," European Financial Management, European Financial Management Association, vol. 26(5), pages 1294-1323, November.
    28. 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.
    29. Benoît Sévi, 2014. "Forecasting the volatility of crude oil futures using intraday data," Working Papers 2014-53, Department of Research, Ipag Business School.
    30. H. Kent Baker & Satish Kumar & Nitesh Pandey, 2021. "Forty years of the Journal of Futures Markets: A bibliometric overview," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1027-1054, July.
    31. Han, Heejoon & Kutan, Ali M. & Ryu, Doojin, 2015. "Modeling and predicting the market volatility index: The case of VKOSPI," Economics Discussion Papers 2015-7, Kiel Institute for the World Economy (IfW Kiel).
    32. Dian‐Xuan Kao & Wei‐Che Tsai & Yaw‐Huei Wang & Kuang‐Chieh Yen, 2018. "An analysis on the intraday trading activity of VIX derivatives," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 158-174, February.
    33. Ewa Ratuszny, 2015. "Risk Modeling of Commodities using CAViaR Models, the Encompassing Method and the Combined Forecasts," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 129-156.
    34. 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.
    35. 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.
    36. Dutta, Anupam & Uddin, Gazi Salah & Sheng, Lin Wen & Park, Donghyun & Zhu, Xuening, 2024. "Volatility dynamics of agricultural futures markets under uncertainties," Energy Economics, Elsevier, vol. 136(C).

  29. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    See citations under working paper version above.
  30. Jean-Pierre Urbain & Sébastien Laurent, 2005. "Bridging the gap between Ox and Gauss using OxGauss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 131-139.
    See citations under working paper version above.
  31. Bauwens, Luc & Laurent, Sebastien, 2005. "A New Class of Multivariate Skew Densities, With Application to Generalized Autoregressive Conditional Heteroscedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 346-354, July.
    See citations under working paper version above.
  32. Sébastien Laurent, 2004. "Analytical Derivates of the APARCH Model," Computational Economics, Springer;Society for Computational Economics, vol. 24(1), pages 51-57, August.

    Cited by:

    1. Stavros Degiannakis & George Filis & Renatas Kizys, 2014. "The Effects of Oil Price Shocks on Stock Market Volatility: Evidence from European Data," The Energy Journal, , vol. 35(1), pages 35-56, January.
    2. Philippe Lambert & Sébastien Laurent & David Veredas, 2012. "Testing conditional asymmetry. A residual based approach," ULB Institutional Repository 2013/136195, ULB -- Universite Libre de Bruxelles.
    3. Výrost, Tomáš & Baumöhl, Eduard, 2009. "Asymmetric GARCH and the financial crisis: a preliminary study," MPRA Paper 27939, University Library of Munich, Germany.
    4. Liu, Yan & Luger, Richard, 2009. "Efficient estimation of copula-GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2284-2297, April.
    5. K. Diamantopoulos & I. Vrontos, 2010. "A Student-t Full Factor Multivariate GARCH Model," Computational Economics, Springer;Society for Computational Economics, vol. 35(1), pages 63-83, January.
    6. Samet Gunay & Audil Rashid Khaki, 2018. "Best Fitting Fat Tail Distribution for the Volatilities of Energy Futures: Gev, Gat and Stable Distributions in GARCH and APARCH Models," JRFM, MDPI, vol. 11(2), pages 1-19, June.
    7. Charles, Amélie & Darné, Olivier, 2019. "The accuracy of asymmetric GARCH model estimation," International Economics, Elsevier, vol. 157(C), pages 179-202.
    8. 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.
    9. Tak Siu & John Lau & Hailiang Yang, 2007. "On Valuing Participating Life Insurance Contracts with Conditional Heteroscedasticity," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(3), pages 255-275, September.
    10. Vikash Gautam & Vikash Vaibhav, 2017. "Investment, Uncertainty and Credit Market Imperfection in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(2), pages 265-289, June.
    11. Hartwell, Christopher A., 2018. "The impact of institutional volatility on financial volatility in transition economies," Journal of Comparative Economics, Elsevier, vol. 46(2), pages 598-615.
    12. Alex Huang, 2011. "Volatility Modeling by Asymmetrical Quadratic Effect with Diminishing Marginal Impact," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 301-330, March.
    13. Loi, Tian Sheng Allan & Ng, Jia Le, 2018. "Anticipating electricity prices for future needs – Implications for liberalised retail markets," Applied Energy, Elsevier, vol. 212(C), pages 244-264.

  33. Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
    See citations under working paper version above.
  34. Beine, Michel & Laurent, Sebastien, 2003. "Central bank interventions and jumps in double long memory models of daily exchange rates," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 641-660, December.
    See citations under working paper version above.
  35. Giot, Pierre & Laurent, Sebastien, 2003. "Market risk in commodity markets: a VaR approach," Energy Economics, Elsevier, vol. 25(5), pages 435-457, September.
    See citations under working paper version above.
  36. Pierre Giot & Sébastien Laurent, 2003. "Value-at-risk for long and short trading positions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 641-663.
    See citations under working paper version above.
  37. Beine, Michel & Laurent, Sebastien & Lecourt, Christelle, 2003. "Official central bank interventions and exchange rate volatility: Evidence from a regime-switching analysis," European Economic Review, Elsevier, vol. 47(5), pages 891-911, October.
    See citations under working paper version above.
  38. Michel Beine & Sebastien Laurent & Christelle Lecourt, 2002. "Accounting for conditional leptokurtosis and closing days effects in FIGARCH models of daily exchange rates," Applied Financial Economics, Taylor & Francis Journals, vol. 12(8), pages 589-600.
    See citations under working paper version above.
  39. Sébastien Laurent & Jean–Philippe Peters, 2002. "G@RCH 2.2: An Ox Package for Estimating and Forecasting Various ARCH Models," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 447-484, July.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2019. "The accuracy of asymmetric GARCH model estimation," Post-Print hal-01943883, HAL.
    2. González-Pla, Francisco & Lovreta, Lidija, 2022. "Modeling and forecasting firm-specific volatility: The role of asymmetry and long-memory," Finance Research Letters, Elsevier, vol. 48(C).
    3. Xiaolei He & Weiguo Zhang, 2024. "Vine copula‐based scenario tree generation approaches for portfolio optimization," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1936-1955, September.
    4. Ranajit Kumar Bairagi, 2022. "Dynamic Impacts of Economic Policy Uncertainty on Australian Stock Market: An Intercontinental Evidence," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 21(1), pages 64-91, March.

  40. Beine, Michel & Bismans, Francis & Docquier, Frederic & Laurent, Sebastien, 2001. "Life-cycle behaviour of US households: A nonlinear GMM estimation on pseudopanel data," Journal of Policy Modeling, Elsevier, vol. 23(7), pages 713-729, October.

    Cited by:

    1. Dimitris K. Christopoulos & Karine Gente & Miguel A. Leon-Ledesma, 2008. "Net Foreign Assets, Productivity and Real Exchange Rates in Constrained Economies," Discussion Papers 2008-17, School of Economics, The University of New South Wales.

  41. Aurélie Boubel & Sébastien Laurent & Christelle Lecourt, 2001. "L'impact des signaux de politique monétaire sur la volatilité intrajournalière du taux de change Deutsche Mark-dollar," Revue économique, Presses de Sciences-Po, vol. 52(2), pages 353-370.
    See citations under working paper version above.
  42. Sébastien Laurent, 2001. "Capital humain, emploi et salaire en Belgique et dans ses régions," Reflets et perspectives de la vie économique, De Boeck Université, vol. 0(1), pages 25-36.

    Cited by:

    1. Robert Plasman & François Rycx & Ilan Tojerow, 2006. "Industry wage differentials, unobserved ability, and rent-sharing: evidence from matched employer-employee, 1992-2005," DULBEA Working Papers 06-14.RS, ULB -- Universite Libre de Bruxelles.
    2. Anna Cristina d'Addio & Isabelle De Greef & Michael Rosholm, 2002. "Assessing Unemployment Traps in Belgium using Panel Data Sample Selection models," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C1-3, International Conferences on Panel Data.
    3. Abdoulaye Diagne & Dorothée Boccanfuso & Djibril Gassama Barry, 2003. "La rentabilité de l'investissement dans l'éducation au Sénégal," Cahiers de recherche 0345, CIRPEE.

  43. Michel Beine & Sébastien Laurent, 2000. "La persistance des chocs de volatilité sur le marché des changes s'est-elle modifée depuis le debut des annees 1980 ?," Revue Économique, Programme National Persée, vol. 51(3), pages 703-711.

    Cited by:

    1. Michel Beine & Sébastien Laurent, 2000. "Structural change and long memory in volatility: new evidence from daily exchange rates," ULB Institutional Repository 2013/10473, ULB -- Universite Libre de Bruxelles.

  44. Frédéric Docquier & Sébastien Laurent & Sergio Perelman, 1999. "Capital humain, emploi et revenus du travail: Belgique, 1992," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 161, pages 77-103.

    Cited by:

    1. Philip Du Caju & François Rycx & Ilan Tojerow, 2011. "Inter-industry wage differentials: How much does rent sharing matter?," ULB Institutional Repository 2013/138898, ULB -- Universite Libre de Bruxelles.
    2. Guy Navon & Ilan Tojerow, 2013. "Does Rent-sharing Profit Female and Male Workers? Evidence from Israeli Matched Employer–Employee Data," LABOUR, CEIS, vol. 27(3), pages 331-349, September.
    3. Robert Plasman & François Rycx & Ilan Tojerow, 2007. "Wage differentials in Belgium: the role of worker and employer characteristics," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 50(1), pages 11-40.
    4. Plasman, Robert & Rycx, François & Tojerow, Ilan, 2006. "Industry Wage Differentials, Unobserved Ability, and Rent-Sharing: Evidence from Matched Worker-Firm Data, 1995-2002," IZA Discussion Papers 2387, Institute of Labor Economics (IZA).
    5. Robert Plasman & François Rycx & Ilan Tojerow, 2006. "Industry wage differentials, unobserved ability, and rent-sharing : Evidence from matched worker-firm data, 1995-2002," Working Paper Research 90, National Bank of Belgium.
    6. Philip Du Caju & François Ryckx & Ilan Tojerow, 2009. "Inter-industry wage differentials : How much does rent sharing matter ?," Working Paper Research 180, National Bank of Belgium.
    7. Latifa EL BARDIY & Abdeljalil LOUHMADI, 2017. "Human capital and its impact on employment quality: Sector and wage," Journal of Economics and Political Economy, KSP Journals, vol. 4(4), pages 408-419, December.

Chapters

  1. 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.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.