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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, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.

    Cited by:

    1. Artemova, Mariia, 2025. "An order-invariant score-driven dynamic factor model," Journal of Econometrics, Elsevier, vol. 251(C).
    2. Beutner, Eric & Lin, Yicong & Lucas, Andre, 2026. "Consistency, distributional convergence, and optimality of time-varying parameters in score-driven models," Journal of Econometrics, Elsevier, vol. 255(C).
    3. Alexander Mayer & Davide Raggi, 2025. "Estimation and inference in models with multiple behavioural equilibria," Papers 2512.04541, arXiv.org, revised Sep 2026.

  2. 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. "Expected Kullback-Leibler-based characterizations of score-driven updates," Papers 2408.02391, arXiv.org, revised Mar 2026.
    2. Hafner, Christian & Harvey, Andrew & Wang, Linqi, 2025. "Modeling prices from speculative markets: bursting bubbles or deflating balloons?," LIDAM Discussion Papers ISBA 2025008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Artemova, Mariia, 2025. "An order-invariant score-driven dynamic factor model," Journal of Econometrics, Elsevier, vol. 251(C).
    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. Yinhao Wu & Ping He, 2024. "The continuous-time limit of quasi score-driven volatility models," Papers 2409.14734, arXiv.org, revised Jun 2025.
    8. 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.
    9. Antonis Demos, 2025. "Statistical Properties of Two Asymmetric Stochastic Volatility in Power Mean Models," DEOS Working Papers 2546, Athens University of Economics and Business.
    10. Bidoia, M. & Harvey, A. & Palumbo, D., 2026. "Dynamic Models for Climate Extremes," Cambridge Working Papers in Economics 2620, Faculty of Economics, University of Cambridge.
    11. 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.
    12. 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.
    13. Catania, Leopoldo & D’Innocenzo, Enzo & Luati, Alessandra, 2026. "Unobserved component models, approximate filters and dynamic adaptive mixture models," Journal of Econometrics, Elsevier, vol. 253(C).
    14. Pierluigi Vallarino, 2024. "Dynamic kernel models," Tinbergen Institute Discussion Papers 24-082/III, Tinbergen Institute.
    15. Andre Lucas & Yicong Lin, 2025. "Testing for the Absence of Score-Driven Parameter Dynamics," Tinbergen Institute Discussion Papers 25-063/III, Tinbergen Institute.
    16. Thomas Giroux & Julien Royer & Olivier David Zerbib, 2024. "Empirical Asset Pricing with Score-Driven Conditional Betas," Post-Print hal-05415058, HAL.

  3. Emmanuel Flachaire & Sullivan Hué & Sébastien Laurent & Gilles Hacheme, 2023. "Interpretable Machine Learning Using Partial Linear Models," Post-Print hal-04529011, HAL.

    Cited by:

    1. Sullivan Hu'e & S'ebastien Laurent & Ulrich Aiounou & Emmanuel Flachaire, 2025. "Estimation in high-dimensional linear regression: Post-Double-Autometrics as an alternative to Post-Double-Lasso," Papers 2511.21257, arXiv.org.

  4. 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. Zac Chen & George Milunovich & Shuping Shi & Ben Wang, 2026. "Forecasting House Prices: The Role of Market Interconnectedness," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(4), pages 1847-1877, July.
    2. 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 06-24, Association Française de Cliométrie (AFC).
    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. Anna Mikusheva & Mikkel Sølvsten, 2025. "Linear regression with weak exogeneity," Quantitative Economics, Econometric Society, vol. 16(2), pages 367-403, May.
    5. Castro, Tomas del Barrio & Escribano, Alvaro & Sibbertsen, Philipp, 2025. "Modeling and forecasting the long memory of Cyclical Trends in paleoclimate data," Energy Economics, Elsevier, vol. 147(C).
    6. Edwin Fourrier-Nicolaï & Michel Lubrano, 2023. "Bayesian inference for non-anonymous growth incidence curves using Bernstein polynomials: an application to academic wage dynamics," Post-Print hal-04356211, HAL.
    7. Maung, Kenwin & Swanson, Norman R., 2025. "A survey of models and methods used for forecasting when investing in financial markets," International Journal of Forecasting, Elsevier, vol. 41(4), pages 1355-1382.

  5. 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. Shi, Shuping & Phillips, Peter C.B., 2026. "Uncovering mild drift in asset prices with intraday high-frequency data," Journal of Econometrics, Elsevier, vol. 253(C).
    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. H. Peter Boswijk & Jun Yu & Yang Zu, 2024. "Testing for an Explosive Bubble using High-Frequency Volatility," Papers 2405.02087, arXiv.org, revised Oct 2026.
    5. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    6. Laurent, Sébastien & Renò, Roberto & Shi, Shuping, 2026. "Realized drift," Journal of Econometrics, Elsevier, vol. 254(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. Leone, Maria & Manelli, Alberto & Pace, Roberta, 2025. "Energy, metals, cereals and G7 indices: Russia–Ukraine conflict and risk spillovers," Finance Research Letters, Elsevier, vol. 82(C).

  6. Aloy, Marcel & Laly, Floris & Laurent, Sébastien & Lecourt, Christelle, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," LIDAM Reprints LFIN 2021021, Université catholique de Louvain, Louvain Finance (LFIN).

    Cited by:

    1. Bohan Zhao & Hong Yin & Yonghong Long, 2024. "An Advanced Time-Varying Capital Asset Pricing Model via Heterogeneous Autoregressive Framework: Evidence from the Chinese Stock Market," Mathematics, MDPI, vol. 13(1), pages 1-14, December.

  7. 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. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers (2017-2023 papers hosted by The National Institute of Economic and Social Research) ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    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. Blasques, F. & Francq, Christian & Laurent, Sébastien, 2023. "Quasi score-driven models," Journal of Econometrics, Elsevier, vol. 234(1), pages 251-275.

  8. 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. Shi, Shuping & Phillips, Peter C.B., 2026. "Uncovering mild drift in asset prices with intraday high-frequency data," Journal of Econometrics, Elsevier, vol. 253(C).
    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. 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).
    6. 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.
    7. Kolokolov, Aleksey & Renò, Roberto & Zoi, Patrick, 2026. "BUMVU estimators," Journal of Econometrics, Elsevier, vol. 254(PA).
    8. 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.
    9. Li, Qiyuan & Li, Yifan & Nolte, Ingmar & Nolte, Sandra & Yu, Shifan, 2026. "Testing for jumps in a discretely observed price process with endogenous sampling times," Journal of Econometrics, Elsevier, vol. 254(PA).
    10. Yi, Chae-Deug, 2026. "Volatility and jumps in the Chinese Yuan using Gumbel distribution during the trade war and COVID-19 pandemic," Journal of Empirical Finance, Elsevier, vol. 85(C).
    11. 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.
    12. Laurent, Sébastien & Renò, Roberto & Shi, Shuping, 2026. "Realized drift," Journal of Econometrics, Elsevier, vol. 254(PA).
    13. 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).
    14. 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).
    15. Li, Yifan & Nolte, Ingmar & Nolte, Sandra & Yu, Shifan, 2025. "Realized candlestick wicks," Journal of Econometrics, Elsevier, vol. 250(C).
    16. Kefu Liao, 2026. "The Role of Price‐Volatility Cojumps in Volatility Forecasting," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 46(5), pages 931-951, May.

  9. 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. "Solving penalised American options for jump diffusions using the POST algorithm," 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. 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.
    8. 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.
    9. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    10. Stefano Grassi & Francesco Violante, 2021. "Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas," CEIS Research Paper 510, Tor Vergata University, CEIS, revised 11 Mar 2021.
    11. Boubacar Maïnassara, Y. & Kadmiri, O. & Saussereau, B., 2022. "Estimation of multivariate asymmetric power GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    12. Chen Tong & Peter Reinhard Hansen, 2025. "Dynamic Factor Correlation Model," Papers 2503.01080, arXiv.org.
    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.
    14. Thomas Giroux & Julien Royer & Olivier David Zerbib, 2024. "Empirical Asset Pricing with Score-Driven Conditional Betas," Post-Print hal-05415058, HAL.

  10. 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. 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.
    2. 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.
    3. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2023. "We modeled long memory with just one lag!," Journal of Econometrics, Elsevier, vol. 236(1).
    4. Javier Haulde & Morten Ørregaard Nielsen, 2022. "Fractional integration and cointegration," CREATES Research Papers 2022-02, Department of Economics and Business Economics, Aarhus University.
    5. Anna Mikusheva & Mikkel Sølvsten, 2025. "Linear regression with weak exogeneity," Quantitative Economics, Econometric Society, vol. 16(2), pages 367-403, May.
    6. 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. Li, Yizhuo & Cao, Yijie, 2026. "Evolving contributions and collaboration efficiency of individual and organizational users on Gitee," Journal of Informetrics, Elsevier, vol. 20(2).
    8. Castro, Tomas del Barrio & Escribano, Alvaro & Sibbertsen, Philipp, 2025. "Modeling and forecasting the long memory of Cyclical Trends in paleoclimate data," Energy Economics, Elsevier, vol. 147(C).
    9. 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.

  11. 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. 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.
    3. 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.
    4. Sarlin, Peter & Holopainen, Markus, 2016. "Toward robust early-warning models: a horse race, ensembles and model uncertainty," Working Paper Series 1900, European Central Bank.
    5. Ophélie Couperier & Jérémy Leymarie, 2020. "Backtesting Expected Shortfall via Multi-Quantile Regression," Working Papers halshs-01909375, HAL.
    6. 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).
    7. Javier Ojea Ferreiro, 2025. "A Market-Based Approach to Reverse Stress Testing the Financial System," Staff Working Papers 25-32, Bank of Canada.
    8. 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.
    9. 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.
    10. Gordy, Michael B. & McNeil, Alexander J., 2020. "Spectral backtests of forecast distributions with application to risk management," Journal of Banking & Finance, Elsevier, vol. 116(C).
    11. Barde, Sylvain, 2026. "Large-scale model comparison with fast model confidence sets," Journal of Econometrics, Elsevier, vol. 253(C).
    12. 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.
    13. 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.

  12. 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), Paradigm, vol. 97(2), pages 55-69, December.
    2. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    3. 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.
    4. Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    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.

  13. 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. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    2. 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.
    3. Prosper Dovonon & Eric Renault, 2012. "Testing for Common GARCH Factors," CIRANO Working Papers 2012s-34, CIRANO.
    4. Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2017. "A vector heterogeneous autoregressive index model for realized volatility measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 337-344.
    5. Chevillon, G. & Hecq, A.W. & Laurent, S.F.J.A., 2015. "Long memory through marginalization of large systems and hidden cross-section dependence," Research Memorandum 014, Maastricht University, Graduate School of Business and Economics (GSBE).
    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.
    7. 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.
    8. 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.
    9. Gianluca Cubadda & Alain Hecq, 2020. "Dimension Reduction for High Dimensional Vector Autoregressive Models," Papers 2009.03361, arXiv.org, revised Feb 2022.

  14. 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. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    3. 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.
    4. 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.
    5. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    6. 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).
    7. 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.
    8. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2021. "Oil Price Shocks, Real Economic Activity and Uncertainty," Post-Print hal-03284089, HAL.
    9. 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).
    10. Yinhao Wu & Ping He, 2024. "The continuous-time limit of quasi score-driven volatility models," Papers 2409.14734, arXiv.org, revised Jun 2025.
    11. Olivier Darné & Amélie Charles, 2019. "Volatility estimation for Bitcoin: Replication and robustness," Post-Print hal-01941102, HAL.
    12. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    13. M. Angeles Carnero Fernández & Ana Pérez Espartero, 2018. "Outliers and misleading leverage effect in asymmetric GARCH-type models," Working Papers. Serie AD 2018-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    14. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    15. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    16. 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.
    17. Amélie Charles & Olivier Darné, 2021. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 15(2), pages 419-442, May.
    18. 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.
    19. Perez Riaza, Baptiste & Gnabo, Jean-Yves, 2025. "From depegs to jumps: The role of stablecoin instabilities in crypto market dynamics," Journal of International Money and Finance, Elsevier, vol. 155(C).
    20. 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).
    21. Tafakori, Laleh & Pourkhanali, Armin & Fard, Farzad Alavi, 2018. "Forecasting spikes in electricity return innovations," Energy, Elsevier, vol. 150(C), pages 508-526.
    22. Wang, Jying-Nan & Vigne, Samuel A. & Liu, Hung-Chun & Hsu, Yuan-Teng, 2024. "Divergent jump characteristics in brown and green cryptocurrencies: The role of energy-related uncertainty," Energy Economics, Elsevier, vol. 138(C).
    23. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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).
    29. 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.
    30. 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).
    31. 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.
    32. Thomas Chuffart & Emmanuel Flachaire & Anne Peguin-Feissolle, 2018. "Testing for misspecification in the short-run component of GARCH-type models," Post-Print hal-02083772, HAL.
    33. 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.
    34. 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.
    35. Collet, Jerome & Ielpo, Florian, 2018. "Sector spillovers in credit markets," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 267-278.
    36. 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.

  15. 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. 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.
    2. Haoyuan Wang & Chen Liu & Minh-Ngoc Tran & Chao Wang, 2025. "Deep Learning Enhanced Multivariate GARCH," Papers 2506.02796, arXiv.org.
    3. Yinhao Wu & Ping He, 2024. "The continuous-time limit of quasi score-driven volatility models," Papers 2409.14734, arXiv.org, revised Jun 2025.
    4. 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.
    5. Ding, Y., 2020. "Diffusion Limits of Real-Time GARCH," Cambridge Working Papers in Economics 20112, Faculty of Economics, University of Cambridge.
    6. 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.
    7. Hafner, C. & Laurent, S. & Violante, F., 2016. "Weak Diffusion Limits of Dynamic Conditional Correlation Models," LIDAM Discussion Papers ISBA 2016034, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  16. 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. 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.
    2. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.

  17. 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. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    2. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "Solving penalised American options for jump diffusions using the POST algorithm," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    3. 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.
    4. Liyuan Cui & Yongmiao Hong & Yingxing Li & Junhui Wang, 2024. "A Regularized High-Dimensional Positive Definite Covariance Estimator with High-Frequency Data," Management Science, INFORMS, vol. 70(10), pages 7242-7264, October.
    5. 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).
    6. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    7. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).
    8. 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.
    9. 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.
    10. Nabil Bouamara & Kris Boudt & S'ebastien Laurent & Christopher J. Neely, 2023. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Papers 2309.15705, arXiv.org.
    11. 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.
    12. 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).
    13. Hugo Gobato Souto & Amir Moradi, 2026. "Enhancing financial risk management: a novel multivariate neural network approach for realized covariance matrix prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 12(1), pages 1-26, December.
    14. 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.
    15. Sébastien Laurent & Shuping Shi, 2018. "Volatility Estimation and Jump Detection for drift-diffusion Processes," Working Papers halshs-01944449, HAL.
    16. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    17. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2020. "A Dynamic Component Model for Forecasting High-Dimensional Realized Covariances Matrices," Working Papers 3_234, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno, revised Jul 2020.

  18. Deniz Erdemlioglu & Sébastien 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. 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).
    2. 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.
    3. Gavronski, Pedro & De Genaro, Alan, 2026. "Jumps and jolts: A continuous-time model for electricity future contract pricing," Journal of Commodity Markets, Elsevier, vol. 41(C).
    4. 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.
    5. 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.
    6. Hizmeri, Rodrigo & Izzeldin, Marwan & Urga, Giovanni, 2025. "Identifying the underlying components of high-frequency data: Pure vs jump diffusion processes," Journal of Empirical Finance, Elsevier, vol. 81(C).

  19. 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. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    2. Sucarrat, Genaro, 2020. "Identification of Volatility Proxies as Expectations of Squared Financial Return," MPRA Paper 101953, University Library of Munich, Germany.
    3. 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.
    4. 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., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • 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. 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.
    6. 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.
    7. 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).
    8. Bucci, Andrea, 2017. "Forecasting realized volatility: a review," MPRA Paper 83232, University Library of Munich, Germany.

  20. Deniz Erdemlioglu & Sébastien 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. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in Equilibrium Prices and Asymmetric News in Foreign Exchange Markets," Working Papers hal-04141414, HAL.
    2. Imane El Ouadghiri & Valérie Mignon & Nicolas Boitout, 2016. "On the impact of macroeconomic news surprises on Treasury-bond returns," Annals of Finance, Springer, vol. 12(1), pages 29-53, February.
    3. 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.
    4. 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.
    5. 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.
    6. Su, Fei, 2021. "Conditional volatility persistence and volatility spillovers in the foreign exchange market," Research in International Business and Finance, Elsevier, vol. 55(C).
    7. Dondukova Oyuna & Liu Yaobin, 2021. "Forecasting the Crude Oil Prices Volatility With Stochastic Volatility Models," SAGE Open, , vol. 11(3), pages 21582440211, July.
    8. 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.
    9. 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.
    10. El Ouadghiri, Imane & Uctum, Remzi, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Economic Modelling, Elsevier, vol. 54(C), pages 218-234.
    11. 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, International Journal of Economics and Financial Issues, vol. 7(4), pages 119-131.
    12. 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.
    13. Imane El Ouadghiri & Valérie Mignon & Nicolas Boitout, 2014. "On the impact of macroeconomic news surprises on Treasury-bond yields," Working Papers hal-04141345, HAL.
    14. 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.
    15. 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).

  21. 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. Yves Dominicy & Hiroaki Ogata & David Veredas, 2013. "Inference for vast dimensional elliptical distributions," Computational Statistics, Springer, vol. 28(4), pages 1853-1880, August.
    2. 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.
    3. Banulescu-Radu, Denisa & Hurlin, Christophe & Leymarie, Jeremy & Scaillet, Olivier, 2020. "Backtesting marginal expected shortfalland related systemic risk measures," Working Papers unige:134136, University of Geneva, Geneva School of Economics and Management.
    4. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
    5. Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
    6. 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.
    7. 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.
    8. Werker, Bas J M & Andreou, Elena, 2013. "Residual-based Rank Specification Tests for AR-GARCH type models," CEPR Discussion Papers 9583, Centre for Economic Policy Research.

  22. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    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. 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).
    8. 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.
    9. 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.
    10. 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., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • 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).
    11. 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.
    12. 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.
    13. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Jump-Robust Volatility Estimation using Nearest Neighbor Truncation," NBER Working Papers 15533, National Bureau of Economic Research, Inc.
    14. 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.
    15. 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.
    16. 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).
    17. Cecilia Mancini & Vanessa Mattiussi & Roberto Renò, 2015. "Spot volatility estimation using delta sequences," Finance and Stochastics, Springer, vol. 19(2), pages 261-293, April.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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).
    23. 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).
    24. Yi, Chae-Deug, 2026. "Volatility and jumps in the Chinese Yuan using Gumbel distribution during the trade war and COVID-19 pandemic," Journal of Empirical Finance, Elsevier, vol. 85(C).
    25. 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.
    26. 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).
    27. 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.
    28. 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.
    29. 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.
    30. 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).

  23. 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. 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.
    2. 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.
    3. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "The Rise and Fall of S&P500 Variance Futures," Working Papers in Economics 11/32, University of Canterbury, Department of Economics and Finance.
    5. Fei Chen & Francis X. Diebold & Frank Schorfheide, 2012. "A Markov-Switching Multi-Fractal Inter-Trade Duration Model, with Application to U.S. Equities," PIER Working Paper Archive 12-020, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    6. Jean-François Carpantier & Arnaud Dufays, 2013. "Commodities Inventory Effect," DEM Discussion Paper Series 13-07, Department of Economics at the University of Luxembourg.
    7. Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2017. "A vector heterogeneous autoregressive index model for realized volatility measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 337-344.
    8. 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.
    9. 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.
    10. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    11. H. F. Lopes & R. E. McCulloch & R. S. Tsay, 2014. "Parsimony Inducing Priors for Large Scale State-Space Models," Business and Economics Working Papers 205, Unidade de Negocios e Economia, Insper.
    12. 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.
    13. 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.
    14. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    15. 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.
    16. Yuta Kurose & Yasuhiro Omori, 2013. "Dynamic Equicorrelation Stochastic Volatility," CIRJE F-Series CIRJE-F-907, CIRJE, Faculty of Economics, University of Tokyo.
    17. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.

  24. 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. 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).

  25. 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).

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    1. 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".
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
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    11. 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.
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    14. 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.
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    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. del Barrio Castro, Tomás & Hecq, Alain, 2016. "Testing for deterministic seasonality in mixed-frequency VARs," Economics Letters, Elsevier, vol. 149(C), pages 20-24.
    3. 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.
    4. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    5. Deniz Erdemlioglu & Sébastien 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.
    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. 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.
    8. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
    9. Dewachter, Hans & Erdemlioglu, Deniz & Gnabo, Jean-Yves & Lecourt, Christelle, 2014. "The intra-day impact of communication on euro-dollar volatility and jumps," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 131-154.

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    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.
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    4. 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.
    5. 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.
    6. Rasmus Søndergaard Pedersen & Anders Rahbek, 2012. "Multivariate Variance Targeting in the BEKK-GARCH Model," Discussion Papers 12-23, University of Copenhagen. Department of Economics.
    7. 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.
    8. 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.
    9. 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).
    10. 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.
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    15. 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.
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    20. 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.
    21. Tobias Fissler & Yannick Hoga, 2024. "How to Compare Copula Forecasts?," Papers 2410.04165, arXiv.org.
    22. 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.
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    25. Guo, Hongfei & Marín, Juan Miguel & Veiga, Helena, 2026. "Diagnosing and Stabilizing Dynamic Correlations in Multivariate Stochastic Volatility Models," DES - Working Papers. Statistics and Econometrics. WS 50561, Universidad Carlos III de Madrid. Departamento de Estadística.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling and Estimation," Papers 2206.14275, arXiv.org, revised Jan 2025.
    31. 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.
    32. 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.
    33. 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.
    34. 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).
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    38. Manabu Asai & Chia-Lin Chang & Michael McAleer & Laurent Pauwels, 2018. "Asymptotic Theory for Rotated Multivariate GARCH Models," Documentos de Trabajo del ICAE 2018-27, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    39. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
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    64. 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.
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    66. 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.
    67. 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.
    68. 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.
    69. 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.
    70. 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.
    71. 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.
    72. 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.
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    74. 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.
    75. Shu-Fang Yuan, 2024. "Realized higher moments and trading activity," Review of Quantitative Finance and Accounting, Springer, vol. 62(3), pages 971-1005, April.
    76. Yi Zhang & Long Zhou & Zhidong Liu, 2025. "The Information Content of Overnight Information for Volatility Forecasting: Evidence From China's Stock Market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(8), pages 2331-2345, December.
    77. 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).
    78. 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.
    79. Maki, Daiki, 2024. "Asymmetric effect of trading volume on realized volatility," International Review of Economics & Finance, Elsevier, vol. 94(C).
    80. 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.
    81. Gkillas Konstantinos & Tantoula Maria & Tzagarakis Manolis, 2025. "Heterogeneity, Jumps and Co-Movements in Transmission of Volatility Spillovers Among Cryptocurrencies," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 29(5), pages 621-649.
    82. 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.
    83. 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.
    84. 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).
    85. 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.
    86. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Business Applications and State-Level Stock Market Realized Volatility: A Forecasting Experiment," Working Papers 202247, University of Pretoria, Department of Economics.
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    90. Richard Mawulawoe Ahadzie & Dan Daugaard & Moses Kangogo & Faisal Khan & Joaquin Vespignani, 2024. "COVID‐19, Mobility Restriction Policies and Stock Market Volatility: A Cross‐Country Empirical Study," Economic Papers, The Economic Society of Australia, vol. 43(2), pages 184-203, June.
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  29. 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. Rasmus Tangsgaard Varneskov & Valeri Voev, 2010. "The Role of Realized Ex-post Covariance Measures and Dynamic Model Choice on the Quality of Covariance Forecasts," CREATES Research Papers 2010-45, Department of Economics and Business Economics, Aarhus University.
    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. 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.
    5. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    6. Kevin Sheppard & Wen Xu, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    7. Audrino, Francesco, 2011. "Forecasting correlations during the late-2000s financial crisis: short-run component, long-run component, and structural breaks," Economics Working Paper Series 1112, University of St. Gallen, School of Economics and Political Science.
    8. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    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.

  30. 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. Yahya, Farzan & Lee, Chien-Chiang & Chen, Pei-Fen, 2025. "Is central bank resilience vulnerable to climate risks? The role of exchange rate stability and green policies," Journal of Asian Economics, Elsevier, vol. 99(C).
    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. 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.
    8. 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.
    9. Papadamou, Stephanos & Sidiropoulos, Moïse & Spyromitros, Eleftherios, 2014. "Does central bank transparency affect stock market volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 362-377.
    10. 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.
    11. 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.
    12. 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.
    13. Dewachter, Hans & Erdemlioglu, Deniz & Gnabo, Jean-Yves & Lecourt, Christelle, 2014. "The intra-day impact of communication on euro-dollar volatility and jumps," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 131-154.

  31. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Buccheri, Giuseppe & Renò, Roberto & Vocalelli, Giorgio, 2025. "Taking advantage of biased proxies for forecast evaluation," Journal of Econometrics, Elsevier, vol. 251(C).
    8. 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.
    9. 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.
    10. 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.
    11. 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).
    12. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    13. 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.
    14. Chen, Yi-Ting & Liu, Chu-An & Su, Jiun-Hua, 2025. "Bregman model averaging for forecast combination," Journal of Econometrics, Elsevier, vol. 251(C).
    15. 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.
    16. 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.
    17. Tobias Fissler & Yannick Hoga, 2024. "How to Compare Copula Forecasts?," Papers 2410.04165, arXiv.org.
    18. 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).
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. Andrea Bucci & Michele Palma & Chao Zhang, 2024. "Geometric Deep Learning for Realized Covariance Matrix Forecasting," Papers 2412.09517, arXiv.org.
    24. 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.
    25. 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.
    26. Bauwens, Luc & Otranto, Edoardo, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," LIDAM Discussion Papers CORE 2020034, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    27. 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.
    28. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," CIRJE F-Series CIRJE-F-742, CIRJE, Faculty of Economics, University of Tokyo.
    29. 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.
    30. Brownlees, Christian & Llorens-Terrazas, Jordi, 2024. "Empirical risk minimization for time series: Nonparametric performance bounds for prediction," Journal of Econometrics, Elsevier, vol. 244(1).
    31. 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).
    32. Rombouts, Jeroen & Stentoft, Lars & Violante, Franceso, 2014. "The value of multivariate model sophistication: An application to pricing Dow Jones Industrial Average options," International Journal of Forecasting, Elsevier, vol. 30(1), pages 78-98.
    33. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    34. Shin, Minseok & Kim, Donggyu & Wang, Yazhen & Fan, Jianqing, 2025. "Factor and idiosyncratic VAR volatility matrix models for heavy-tailed high-frequency financial observations," Journal of Econometrics, Elsevier, vol. 252(PA).
    35. Gneiting, Tilmann, 2011. "Making and Evaluating Point Forecasts," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 746-762.
    36. 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.
    37. Christophe Hurlin & Jérémy Leymarie & Antoine Patin, 2018. "Loss functions for LGD model comparison," Working Papers halshs-01516147, HAL.
    38. Ralf Becker & Adam Clements & Robert O'Neill, 2010. "A Kernel Technique for Forecasting the Variance-Covariance Matrix," Centre for Growth and Business Cycle Research Discussion Paper Series 151, Economics, The University of Manchester.
    39. 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.
    40. 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.
    41. Yan, Lili & Kellard, Neil M. & Lambercy, Lyudmyla, 2025. "Multivariate range-based EGARCH models," International Review of Financial Analysis, Elsevier, vol. 100(C).
    42. 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.
    43. Weigand, Roland, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," University of Regensburg Working Papers in Business, Economics and Management Information Systems 478, University of Regensburg, Department of Economics.
    44. 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".
    45. 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.
    46. 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.
    47. Emilio Zanetti Chini, 2018. "Forecasters’ utility and forecast coherence," CREATES Research Papers 2018-23, Department of Economics and Business Economics, Aarhus University.
    48. Chini, Emilio Zanetti, 2023. "Can we estimate macroforecasters’ mis-behavior?," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    49. Timo Dimitriadis & Yannick Hoga, 2026. "Systemic Risk Surveillance," Papers 2601.08598, arXiv.org.
    50. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
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    105. 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.
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  32. Michel Beine & Jerome Lahaye & Sébastien 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. 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.
    2. 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 Economía, Universidad Autónoma de Nuevo León, vol. 31(2), pages 87-113, November.
    3. 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).
    4. 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).
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. Bauer, Christian & De Grauwe, Paul & Reitz, Stefan, 2009. "Exchange rate dynamics in a target zone--A heterogeneous expectations approach," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 329-344, February.
    11. 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.
    12. Ozili, Peterson K, 2024. "Exchange Rate Unification in Nigeria: Benefits and Implications," MPRA Paper 120441, University Library of Munich, Germany.
    13. Rasmus Fatum & Yohei Yamamoto, 2012. "Does Foreign Exchange Intervention Volume Matter?," EPRU Working Paper Series 2012-03, Economic Policy Research Unit (EPRU), University of Copenhagen. Department of Economics.
    14. 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.
    15. 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.
    16. 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.
    17. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    18. 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.
    19. 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.
    20. Sujay Mukhoti & Pritam Ranjan, 2017. "A New Class of Discrete-time Stochastic Volatility Model with Correlated Errors," Papers 1703.06603, arXiv.org.
    21. 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.
    22. José Eduardo Gómez-González & Andrés F. García-Suaza, 2012. "A Simple Test of Momentum in Foreign Exchange Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(5), pages 66-77, September.
    23. 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.
    24. 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.
    25. Serdengecti, Suleyman & Sensoy, Ahmet & Nguyen, Duc Khuong, 2020. "Dynamics of Return and Liquidity (Co)Jumps in Emerging Foreign Exchange Markets," MPRA Paper 105162, University Library of Munich, Germany, revised Jan 2021.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. Roy Trivedi, Smita, 2018. "Exchange rate volatility: Trader's beliefs and the role of news," MPRA Paper 89330, University Library of Munich, Germany.
    36. 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.
    37. 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.
    38. Jesus Crespo Cuaresma & Mauro Costantini & Jaroslava Hlouskova, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Papers wuwp176, Vienna University of Economics and Business, Department of Economics.
    39. Ghysels, Eric & Manganelli, Simone & , & Idier, Julien, 2013. "A high frequency assessment of the ECB Securities Markets Programme," CEPR Discussion Papers 9778, Centre for Economic Policy Research.
    40. Hillebrand, Eric & Schnabl, Gunther & Ulu, Yasemin, 2009. "Japanese foreign exchange intervention and the yen-to-dollar exchange rate: A simultaneous equations approach using realized volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(3), pages 490-505, July.
    41. Štefan Lyócsa & Roman Horváth, 2018. "Stock Market Contagion: a New Approach," Open Economies Review, Springer, vol. 29(3), pages 547-577, July.
    42. 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.
    43. Andersen, Peter & Kim, Suk-Joong, 2011. "Intraday timing of AUD intervention by the Reserve Bank of Australia: Evidence from microstructural analyses," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(2), pages 277-295, April.
    44. Gabriele Galati & Patrick Higgins & Owen Humpage & William Melick, 2007. "Option prices, exchange market intervention, and the higher moment expectations channel: a user's guide," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(2), pages 225-247.
    45. 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.
    46. 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.
    47. Daisuke Nagakura & Toshiaki Watanabe, 2011. "A State Space Approach to Estimating the Integrated Variance under the Existence of Market Microstructure Noise," Global COE Hi-Stat Discussion Paper Series gd11-200, Institute of Economic Research, Hitotsubashi University.
    48. 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.
    49. 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.
    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.

  33. 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. 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.
    2. 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.
    3. Costantini, Mauro & Crespo Cuaresma, Jesus & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Paper Series 176, WU Vienna University of Economics and Business.
    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. 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.
    9. 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.
    10. Neely, Christopher J., 2008. "Central bank authorities' beliefs about foreign exchange intervention," Journal of International Money and Finance, Elsevier, vol. 27(1), pages 1-25, February.
    11. 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.

  34. 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. 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.
    2. 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.
    3. Christophe Ley, 2014. "Flexible Modelling in Statistics: Past, present and Future," Working Papers ECARES ECARES 2014-42, ULB -- Universite Libre de Bruxelles.
    4. 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.
    5. 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.
    6. 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.
    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. 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.
    9. Mark J Jensen & John M Maheu, 2012. "Bayesian semiparametric multivariate GARCH modeling," Working Papers tecipa-458, University of Toronto, Department of Economics.
    10. 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.
    11. 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.
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    13. 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.
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    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.
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    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. Benoit Bellone, 2005. "Classical Estimation of Multivariate Markov-Switching Models using MSVARlib," Econometrics 0508017, University Library of Munich, Germany.
    3. 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).

  37. 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. 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.
    5. Kawakami, Tabito, 2023. "Quantile prediction for Bitcoin returns using financial assets’ realized measures," Finance Research Letters, Elsevier, vol. 55(PA).
    6. 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.
    7. 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.
    8. 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.
    9. Hammoudeh, S.M. & Malik, F. & McAleer, M.J., 2010. "Risk management of precious metals," Econometric Institute Research Papers EI 2010-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Anupam Dutta, 2025. "Assessing the Risk of Bitcoin Futures Market: New Evidence," Annals of Data Science, Springer, vol. 12(2), pages 481-497, April.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
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  39. 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).

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    1. Michel Beine & Charles S. Bos & Sebastian Laurent, 2005. "The Impact of Central Bank FX Interventions on Currency Components," Tinbergen Institute Discussion Papers 05-103/4, Tinbergen Institute.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
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    9. 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.
    10. Charles Bos & Neil Shephard, 2006. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 219-244.
    11. Michel Beine & Oscar Bernal Diaz, 2005. "Why do Central Banks intervene secretly? preliminary evidence of the BoJ," DULBEA Working Papers in, ULB -- Universite Libre de Bruxelles.
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    14. 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.
    15. 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.
    16. Pei-wen Chen & Han-Ching Huang & Yung-chern Su, 2019. "The Imbalance-Based Trading Strategies on Taiwan Exchange Rate Market," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(4), pages 1-8.
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    18. 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.
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  40. 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).

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    2. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2088-2125, September.
    3. 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.
    4. 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).
    5. Kulp-Tåg, Sofie, 2007. "An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions," Working Papers 526, Hanken School of Economics.
    6. Bernardina Algieri & Arturo Leccadito, 2020. "CARL and His POT: Measuring Risks in Commodity Markets," Risks, MDPI, vol. 8(1), pages 1-15, March.
    7. 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.
    8. Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2019. "Forecasting Realized Volatility of Agricultural Commodities," MPRA Paper 96267, University Library of Munich, Germany.
    9. 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.
    10. Joëts, Marc, 2014. "Energy price transmissions during extreme movements," Economic Modelling, Elsevier, vol. 40(C), pages 392-399.
    11. 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.
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    13. 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.
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    15. 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.
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    22. Cheong, Chin Wen, 2009. "Modeling and forecasting crude oil markets using ARCH-type models," Energy Policy, Elsevier, vol. 37(6), pages 2346-2355, June.
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    28. 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.
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  41. 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. 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.
    4. 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.
    5. Bertholon, H. & Alain Monfort & Fulvio Pegoraro, 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    6. 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.
    7. 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.
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    9. 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.
    10. Markus Haas & Stefan Mittnik & Bruce Mizrach, 2004. "Assessing Central Bank Credibility During the EMS Crises: Comparing Option and Spot Market-Based Forecasts," Departmental Working Papers 200424, Rutgers University, Department of Economics.
    11. 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.
    12. 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.
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    17. Junior Ojeda & Gabriel Rodriguez, 2014. "An Application of a Random Level Shifts Model to the Volatility of Peruvian Stock and Exchange Rates Returns," Documentos de Trabajo / Working Papers 2014-383, Departamento de Economía - Pontificia Universidad Católica del Perú.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. Owen F. Humpage, 2003. "Government intervention in the foreign exchange market," Working Papers (Old Series) 0315, Federal Reserve Bank of Cleveland.
    28. Valadkhani, Abbas, 2025. "A multi-pronged analysis of common and market-specific equity outliers across the G7, China, and global markets using country ETFs," Finance Research Letters, Elsevier, vol. 74(C).
    29. 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.
    30. 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.
    31. Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 551-565.
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    33. 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.
    34. Al-Khazali, Osamah & Bouri, Elie & Roubaud, David & Zoubi, Taisier, 2017. "The impact of religious practice on stock returns and volatility," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 172-189.
    35. John Goddard & Enrico Onali, 2016. "Long memory and multifractality: A joint test," Papers 1601.00903, arXiv.org.
    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. 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.
    38. Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
    39. 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.
    40. Caporin, Massimiliano & Preś, Juliusz, 2012. "Modelling and forecasting wind speed intensity for weather risk management," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3459-3476.
    41. Neely, Christopher J., 2008. "Central bank authorities' beliefs about foreign exchange intervention," Journal of International Money and Finance, Elsevier, vol. 27(1), pages 1-25, February.
    42. 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.
    43. 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.

  42. 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. 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.
    2. 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.
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  44. 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. 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.
    2. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Eric Jondeau & Michael Rockinger, 2004. "Optimal Portfolio Allocation Under Higher Moments," Working papers 108, Banque de France.
    8. John Galbraith & Dongming Zhu, 2009. "Forecasting Expected Shortfall With A Generalized Asymmetric Student-T Distribution," Departmental Working Papers 2009-01, McGill University, Department of Economics.
    9. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2016. "Cross-Commodity News Transmission and Volatility Spillovers in the German Energy Markets," Working Papers 2016:2, Lund University, Department of Economics, revised 11 Oct 2017.
    10. 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.
    11. 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.
    12. 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".
    13. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    14. 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).
    15. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    16. 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.
    17. F. Javier Mencía & Enrique Sentana, 2004. "Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations," Working Papers wp2004_0411, CEMFI.
    18. 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.
    19. Michal Kaut & Stein Wallace, 2011. "Shape-based scenario generation using copulas," Computational Management Science, Springer, vol. 8(1), pages 181-199, April.
    20. Balázs Égert & Evžen Kočenda, 2011. "Time-varying synchronization of European stock markets," Empirical Economics, Springer, vol. 40(2), pages 393-407, April.
    21. 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.
    22. Dongming Zhu & John W. Galbraith, 2009. "A Generalized Asymmetric Student-t Distribution with Application to Financial Econometrics," CIRANO Working Papers 2009s-13, CIRANO.
    23. 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.
    24. 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.
    25. 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).
    26. Dean Fantazzini, 2008. "An Econometric Analysis of Financial Data in Risk Management," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), vol. 10(2), pages 91-137.
    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. 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.
    32. 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.
    33. Lombardi, Marco J. & Veredas, David, 2009. "Indirect estimation of elliptical stable distributions," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2309-2324, April.

  45. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    13. 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.
    14. 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).
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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).
    22. 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.
    23. 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).
    24. Refk Selmi, 2025. "Changes in Inflation Expectations and Firm Performance during Recent Global Economic Shocks," Annals of Economics and Finance, Society for AEF, vol. 26(2), pages 731-764, November.
    25. 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.
    26. 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.
    27. Beine, Michel & Benassy-Quere, Agnes & Lecourt, Christelle, 2002. "Central bank intervention and foreign exchange rates: new evidence from FIGARCH estimations," Journal of International Money and Finance, Elsevier, vol. 21(1), pages 115-144, February.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. Sebastian Letmathe & Yuanhua Feng & André Uhde, 2021. "Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall," Working Papers CIE 141, Paderborn University, CIE Center for International Economics.

  46. 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. 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.
    2. 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.
    3. 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.
    4. Sylvain Benoît & Christophe Hurlin & Christophe Pérignon, 2014. "Implied Risk Exposures," Working Papers halshs-00836280, HAL.
    5. 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.
    6. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, June.
    7. 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.
    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. Anupam Dutta, 2025. "Assessing the Risk of Bitcoin Futures Market: New Evidence," Annals of Data Science, Springer, vol. 12(2), pages 481-497, April.
    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. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. David Ardia & S'ebastien Laurent & Rosnel Sessinou, 2024. "High-Dimensional Mean-Variance Spanning Tests," Papers 2403.17127, arXiv.org.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. Degiannakis, Stavros, 2018. "Multiple Days Ahead Realized Volatility Forecasting: Single, Combined and Average Forecasts," MPRA Paper 96272, University Library of Munich, Germany.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. Weshah Razzak, "undated". "On the GCC Currency Union," API-Working Paper Series 0910, Arab Planning Institute - Kuwait, Information Center.
    38. 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.
    39. 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.
    40. Jean-François Carpantier & Arnaud Dufays, 2013. "Commodities Inventory Effect," DEM Discussion Paper Series 13-07, Department of Economics at the University of Luxembourg.
    41. 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.
    42. 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.
    43. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    44. 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.
    45. Zhijie Xiao & Roger Koenker, 2009. "Conditional Quantile Estimation for GARCH Models," Boston College Working Papers in Economics 725, Boston College Department of Economics.
    46. 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.
    47. Angelidis, Timotheos & Degiannakis, Stavros, 2007. "Backtesting VaR Models: A Τwo-Stage Procedure," MPRA Paper 80418, University Library of Munich, Germany.
    48. 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.
    49. 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.
    50. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2016. "Cross-Commodity News Transmission and Volatility Spillovers in the German Energy Markets," Working Papers 2016:2, Lund University, Department of Economics, revised 11 Oct 2017.
    51. 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.
    52. Giannis Vardas & Anastasios Xepapadeas, 2006. "Preserving Biodiversity: Ambiguity and Safety Rules," Working Papers 0607, University of Crete, Department of Economics.
    53. Angelidis, Timotheos & Degiannakis, Stavros, 2005. "Modeling Risk for Long and Short Trading Positions," MPRA Paper 80467, University Library of Munich, Germany.
    54. 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.
    55. 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.
    56. Wong, Woon K., 2010. "Backtesting value-at-risk based on tail losses," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 526-538, June.
    57. 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.
    58. 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.
    59. 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.
    60. 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.
    61. 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.
    62. 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, International Journal of Economics and Financial Issues, vol. 8(3), pages 36-50.
    63. Bernardo León & Andr�s Mora, 2011. "CDS: relación con índices accionarios y medida de riesgo," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 29(64), pages 178-211.
    64. 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.
    65. 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.
    66. 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.
    67. 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.
    68. León, Ángel & Ñíguez, Trino-Manuel, 2020. "Modeling asset returns under time-varying semi-nonparametric distributions," Journal of Banking & Finance, Elsevier, vol. 118(C).
    69. Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.
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    75. Matteo Bonato, 2012. "Modeling fat tails in stock returns: a multivariate stable-GARCH approach," Computational Statistics, Springer, vol. 27(3), pages 499-521, September.
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    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. 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.
    3. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    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. 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.
    6. BAUWENS, Luc & BEN OMRANE, Walid & GIOT, Pierre, 2003. "News announcements, market activity and volatility in the Euro/Dollar foreign exchange market," LIDAM Discussion Papers CORE 2003029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  48. 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.

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    1. 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.
    2. 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.
    3. C. R. McKenzie & Sumiko Takaoka, 2007. "EViews 5.1," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1145-1152.
    4. 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.
    5. Sascha Mergner & Jan Bulla, 2005. "Time-varying Beta Risk of Pan-European Industry Portfolios: A Comparison of Alternative Modeling Techniques," Finance 0510029, University Library of Munich, Germany.
    6. Angelidis, Timotheos & Degiannakis, Stavros, 2007. "Backtesting VaR Models: A Τwo-Stage Procedure," MPRA Paper 80418, University Library of Munich, Germany.
    7. 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.
    8. Giannis Vardas & Anastasios Xepapadeas, 2006. "Preserving Biodiversity: Ambiguity and Safety Rules," Working Papers 0607, University of Crete, Department of Economics.
    9. 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.
    10. Atilla Çifter & Alper Özün, 2007. "The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 1(1), pages 7-34.
    11. Karanasos, M. & Sekioua, S.H. & Zeng, N., 2006. "On the order of integration of monthly US ex-ante and ex-post real interest rates: New evidence from over a century of data," Economics Letters, Elsevier, vol. 90(2), pages 163-169, February.
    12. Emese Lazar & Carol Alexander, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Eskandar A. Tooma, 2003. "Modeling and Forecasting Egyptian Stock Market Volatility Before and After Price Limits," Working Papers 0310, Economic Research Forum, revised 04 Mar 2003.
    20. 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.
    21. Amélie Charles, 2010. "The day-of-the week effects on the volatility: The role of the asymmetry," Post-Print hal-00771136, HAL.
    22. 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.
    23. 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.
    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. Amélie Charles & Olivier Darné, 2014. "Volatility persistence in crude oil markets," Post-Print hal-00940312, HAL.
    27. 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).
    28. 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.

  49. 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. Uctum, Remzi & Renou-Maissant, Patricia & Prat, Georges & Lecarpentier-Moyal, Sylvie, 2017. "Persistence of announcement effects on the intraday volatility of stock returns: Evidence from individual data," Review of Financial Economics, Elsevier, vol. 35(C), pages 43-56.
    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," Post-Print halshs-00174996, HAL.
    4. 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).
    5. Darmoul Mokhtar, 2006. "The impact of monetary policy signals on the intradaily euro-dollar volatility," Post-Print halshs-00118789, HAL.

  50. 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. 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.
    8. 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 the ARFIMA techniques]," MPRA Paper 38605, University Library of Munich, Germany.
    9. Belkhouja, Mustapha & Boutahary, Mohamed, 2011. "Modeling volatility with time-varying FIGARCH models," Economic Modelling, Elsevier, vol. 28(3), pages 1106-1116, May.
    10. Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
    11. 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.
    12. Claudio Morana, 2007. "On the macroeconomic causes of exchange rates volatility," ICER Working Papers 8-2007, ICER - International Centre for Economic Research.
    13. 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.
    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.

  51. 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 & 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.

Articles

  1. Blasques, F. & Francq, Christian & Laurent, Sébastien, 2024. "Autoregressive conditional betas," Journal of Econometrics, Elsevier, vol. 238(2).
    See citations under working paper version above.
  2. Emmanuel Flachaire & Sullivan Hué & Sébastien Laurent & Gilles Hacheme, 2024. "Interpretable Machine Learning Using Partial Linear Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 519-540, June.
    See citations under working paper version above.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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. 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. 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. 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.
    4. 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.
    5. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    6. 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.
    7. 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.
    8. 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.
    9. 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).
    10. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
    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. 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.
    13. 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.
    14. Olivier Darné & Amélie Charles, 2019. "Volatility estimation for Bitcoin: Replication and robustness," Post-Print hal-01941102, HAL.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    20. Amélie Charles & Olivier Darné, 2021. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 15(2), pages 419-442, May.
    21. 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.
    22. Barde, Sylvain, 2026. "Large-scale model comparison with fast model confidence sets," Journal of Econometrics, Elsevier, vol. 253(C).
    23. 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).
    24. 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.
    25. Christophe Hurlin & Sebastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2015. "Risk Measure Inference," Working Papers halshs-00877279, HAL.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. Christian Francq & Lajos Horváth & Jean-Michel Zakoïan, 2016. "Variance Targeting Estimation of Multivariate GARCH Models," Post-Print hal-05417486, HAL.
    36. 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).
    37. Charles, Amélie & Darné, Olivier, 2014. "Volatility persistence in crude oil markets," Energy Policy, Elsevier, vol. 65(C), pages 729-742.
    38. 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.
    39. Jincheng Gu & Shiqi Zhang & Yanling Yu & Feng Liu, 2025. "AB-LSTM-GRU: A Novel Ensemble Composite Deep Neural Network Model for Exchange Rate Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 66(2), pages 1767-1791, August.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    45. Almeida, Daniel de & Hotta, Luiz & Ruiz Ortega, Esther, 2015. "MGARCH models: tradeoff between feasibility and flexibility," DES - Working Papers. Statistics and Econometrics. WS ws1516, Universidad Carlos III de Madrid. Departamento de Estadística.
    46. 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.

  17. 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.
  18. 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.
  19. 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. Serdengecti, Suleyman & Sensoy, Ahmet & Nguyen, Duc Khuong, 2020. "Dynamics of Return and Liquidity (Co)Jumps in Emerging Foreign Exchange Markets," MPRA Paper 105162, University Library of Munich, Germany, revised Jan 2021.
    2. Dewachter, Hans & Erdemlioglu, Deniz & Gnabo, Jean-Yves & Lecourt, Christelle, 2014. "The intra-day impact of communication on euro-dollar volatility and jumps," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 131-154.

  20. 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.
  21. 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.
  22. 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. Christian Walter, 2020. "Sustainable Financial Risk Modelling Fitting the SDGs: Some Reflections," Sustainability, MDPI, vol. 12(18), pages 1-28, September.
    2. 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.
    3. 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.
    4. Louis R. Piccotti, 2026. "A multiscale estimator for pricing error decomposition in high-frequency financial markets," Review of Quantitative Finance and Accounting, Springer, vol. 66(2), pages 887-928, February.
    5. 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.
    6. Fried, Roland, 2012. "On the online estimation of local constant volatilities," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3080-3090.
    7. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    8. 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.
    9. 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.
    10. 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).
    11. 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.
    12. 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.
    13. 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.
    14. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2026. "Is the diurnal pattern sufficient to explain intraday variation in volatility? A nonparametric assessment," Papers 2601.16613, arXiv.org.
    15. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    16. 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.
    17. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in Equilibrium Prices and Asymmetric News in Foreign Exchange Markets," Working Papers hal-04141414, HAL.
    18. 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.
    19. 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.
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    Cited by:

    1. Anupam Dutta, 2025. "Assessing the Risk of Bitcoin Futures Market: New Evidence," Annals of Data Science, Springer, vol. 12(2), pages 481-497, April.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Ruijun Bu & Rodrigo Hizmeri & Marwan Izzeldin & Anthony Murphy & Mike G. Tsionas, 2021. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 202109, University of Liverpool, Department of Economics.
    8. Ricardo Crisostomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," Papers 1801.08007, arXiv.org, revised May 2018.
    9. 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.
    10. 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.
    11. 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.
    12. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch & Seong-Min Yoon, 2020. "OPEC News and Jumps in the Oil Market," Working Papers 202053, University of Pretoria, Department of Economics.
    13. 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.
    14. 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.
    15. 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.
    16. Gongyue Jiang & Gaoxiu Qiao & Chao Liang, 2025. "Unveiling Bidirectional Forecasting Between Volatility of VIX and Stock Market: Insights From Asymmetric Jumps and Cojumps," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(10), pages 1717-1739, October.
    17. Dutta, Anupam & Sihvonen, Jukka & Park, Donghyun & Lucey, Brian & Uddin, Gazi Salah, 2025. "Impact of news and social media sentiments on rare earth investments," Resources Policy, Elsevier, vol. 107(C).
    18. 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.
    19. 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.
    20. 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.
    21. 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).
    22. 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.
    23. Jaemin Son & Doojin Ryu, 2025. "Energy price shocks and stock market volatility in an energy-importing country," Energy & Environment, , vol. 36(8), pages 3737-3769, December.
    24. 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.
    25. 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.
    26. Ahoniemi, Katja & Lanne, Markku, 2010. "Realized volatility and overnight returns," Bank of Finland Research Discussion Papers 19/2010, Bank of Finland.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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, vol. 9, pages 1-34.
    33. Shu-Fang Yuan, 2024. "Realized higher moments and trading activity," Review of Quantitative Finance and Accounting, Springer, vol. 62(3), pages 971-1005, April.
    34. 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.
    35. Benoît Sévi, 2014. "Forecasting the volatility of crude oil futures using intraday data," Working Papers 2014-53, Department of Research, Ipag Business School.
    36. 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.
    37. 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.
    38. 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.
    39. Fulvio Corsi & Davide Pirino & Roberto Reno', 2010. "Threshold Bipower Variation and the Impact of Jumps on Volatility Forecasting," LEM Papers Series 2010/11, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  31. 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.
  32. 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.
  33. 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.
  34. 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. Liu, Yan & Luger, Richard, 2009. "Efficient estimation of copula-GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2284-2297, April.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Výrost, Tomáš & Baumöhl, Eduard, 2009. "Asymmetric GARCH and the financial crisis: a preliminary study," MPRA Paper 27939, University Library of Munich, Germany.
    8. 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.
    9. 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.
    10. 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.
    11. Amélie Charles & Olivier Darné, 2019. "The accuracy of asymmetric GARCH model estimation," International Economics, CEPII research center, issue 157, pages 179-202.
    12. 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.

  35. 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.
  36. 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.
  37. 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.
  38. 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.
  39. 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.
  40. 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.
  41. 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. 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).
    2. Amélie Charles & Olivier Darné, 2019. "The accuracy of asymmetric GARCH model estimation," Post-Print hal-01943883, HAL.
    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.

  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. 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.
    2. 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.
    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. 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.

  44. 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.
  45. 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 & 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.

  46. 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. 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.
    2. Du Caju, Philip & Rycx, François & Tojerow, Ilan, 2009. "Inter-industry wage differentials: how much does rent sharing matter?," Working Paper Series 1103, European Central Bank.
    3. 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.
    4. 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.
    5. 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, IZA Network @ LISER.

Chapters

  1. Marcel Aloy & Floris Laly & Sébastien Laurent & Christelle Lecourt, 2021. "Modeling Time-Varying Conditional Betas. A Comparison of Methods with Application for REITs," Dynamic Modeling and Econometrics in Economics and Finance, in: Gilles Dufrénot & Takashi Matsuki (ed.), Recent Econometric Techniques for Macroeconomic and Financial Data, pages 229-264, Springer.
    See citations under working paper version above.
  2. 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.
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