An empirical investigation of multiperiod tail risk forecasting models
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DOI: 10.1016/j.irfa.2023.102498
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- Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2020. "Risk quantification for commodity ETFs: Backtesting value-at-risk and expected shortfall," International Review of Financial Analysis, Elsevier, vol. 70(C).
- 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.
- Degiannakis, Stavros & Potamia, Artemis, 2016. "Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: inter-day versus intra-day data," MPRA Paper 74670, University Library of Munich, Germany.
- Patton, Andrew J. & Ziegel, Johanna F. & Chen, Rui, 2019.
"Dynamic semiparametric models for expected shortfall (and Value-at-Risk),"
Journal of Econometrics, Elsevier, vol. 211(2), pages 388-413.
- Andrew J. Patton & Johanna F. Ziegel & Rui Chen, 2017. "Dynamic Semiparametric Models for Expected Shortfall (and Value-at-Risk)," Papers 1707.05108, arXiv.org.
- Fu, Tianwen & Zhuang, Xinkai & Hui, Yongchang & Liu, Jia, 2017. "Convex risk measures based on generalized lower deviation and their applications," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 27-37.
- Robert F. Engle & Simone Manganelli, 2004.
"CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
- Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
- Robert Engle & Simone Manganelli, 2000. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Econometric Society World Congress 2000 Contributed Papers 0841, Econometric Society.
- Annalisa Molino & Carlo Sala, 2021. "Forecasting value at risk and conditional value at risk using option market data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1190-1213, November.
- Bates, David S, 1996. "Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options," The Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 69-107.
- Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Didier Maillard, 2019.
"Computation of the corrected Cornish–Fisher expansion using the response surface methodology: application to VaR and CVaR,"
Annals of Operations Research, Springer, vol. 281(1), pages 423-453, October.
- Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Didier Maillard, 2017. "Computation of the Corrected Cornish-Fisher Expansion using the Response Surface Methodology: Application to V aR and CV aR," THEMA Working Papers 2017-21, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- Basak, Suleyman & Shapiro, Alexander, 2001.
"Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices,"
The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
- Suleyman Basak & Alex Shapiro, "undated". "Value-at-Risk Based Risk Management: Optimal Policies and Asset Prices," Rodney L. White Center for Financial Research Working Papers 6-99, Wharton School Rodney L. White Center for Financial Research.
- Suleyman Basak & Alexander Shapiro, 1999. "Value-at-Risk Based Risk Management: Optimal Policies and Asset Prices," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-032, New York University, Leonard N. Stern School of Business-.
- Suleyman Basak & Alex Shapiro, "undated". "Value-at-Risk Based Risk Management: Optimal Policies and Asset Prices," Rodney L. White Center for Financial Research Working Papers 06-99, Wharton School Rodney L. White Center for Financial Research.
- Zhiping Chen & Giorgio Consigli & Jia Liu & Gang Li & Tianwen Fu & Qianhui Hu, 2017. "Multi-Period Risk Measures and Optimal Investment Policies," International Series in Operations Research & Management Science, in: Giorgio Consigli & Daniel Kuhn & Paolo Brandimarte (ed.), Optimal Financial Decision Making under Uncertainty, chapter 0, pages 1-34, Springer.
- Haitao Li & Martin T. Wells & Cindy L. Yu, 2008. "A Bayesian Analysis of Return Dynamics with Lévy Jumps," The Review of Financial Studies, Society for Financial Studies, vol. 21(5), pages 2345-2378, September.
- Jin-Chuan Duan & Weiqi Zhang, 2014. "Forward-Looking Market Risk Premium," Management Science, INFORMS, vol. 60(2), pages 521-538, February.
- Brick, Ivan E. & Mellon, W. G. & Surkis, Julius & Mohl, Murray, 1983. "Optimal capital structure : A multi-period programming model for use in financial planning," Journal of Banking & Finance, Elsevier, vol. 7(1), pages 45-67, March.
- Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
- Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, August.
- Alexander, Carol & Lazar, Emese & Stanescu, Silvia, 2013. "Forecasting VaR using analytic higher moments for GARCH processes," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 36-45.
- Lazar, Emese & Xue, Xiaohan, 2020. "Forecasting risk measures using intraday data in a generalized autoregressive score framework," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1057-1072.
- Natalia Nolde & Johanna F. Ziegel, 2016. "Elicitability and backtesting: Perspectives for banking regulation," Papers 1608.05498, arXiv.org, revised Feb 2017.
- Lazar, Emese & Qi, Shuyuan, 2022. "Model risk in the over-the-counter market," European Journal of Operational Research, Elsevier, vol. 298(2), pages 769-784.
- Chrétien, Stéphane & Coggins, Frank, 2010. "Performance and conservatism of monthly FHS VaR: An international investigation," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 323-333, December.
- Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
- Duan, Jin-Chuan & Sun, Jie & Wang, Tao, 2012. "Multiperiod corporate default prediction—A forward intensity approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 191-209.
- James Ming Chen, 2017. "Risk and Uncertainty," Quantitative Perspectives on Behavioral Economics and Finance, in: Econophysics and Capital Asset Pricing, chapter 0, pages 189-211, Palgrave Macmillan.
- Stefania Corsaro & Valentina De Simone & Zelda Marino & Francesca Perla, 2020. "$$l_1$$ l 1 -Regularization for multi-period portfolio selection," Annals of Operations Research, Springer, vol. 294(1), pages 75-86, November.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006.
"Predicting volatility: getting the most out of return data sampled at different frequencies,"
Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," NBER Working Papers 10914, National Bureau of Economic Research, Inc.
- Giovanni Barone‐Adesi & Chiara Legnazzi & Carlo Sala, 2019. "Option‐implied risk measures: An empirical examination on the S&P 500 index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1409-1428, October.
- Ebnother, Silvan & Vanini, Paolo, 2007. "Credit portfolios: What defines risk horizons and risk measurement?," Journal of Banking & Finance, Elsevier, vol. 31(12), pages 3663-3679, December.
- Le, Trung H., 2020. "Forecasting value at risk and expected shortfall with mixed data sampling," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1362-1379.
- Eric Ghysels & Alberto Plazzi & Rossen Valkanov & Antonio Rubia & Asad Dossani, 2019. "Direct Versus Iterated Multiperiod Volatility Forecasts," Annual Review of Financial Economics, Annual Reviews, vol. 11(1), pages 173-195, December.
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- Mercik, Aleksander & Słoński, Tomasz & Karaś, Marta, 2024. "Understanding crypto-asset exposure: An investigation of its impact on performance and stock sensitivity among listed companies," International Review of Financial Analysis, Elsevier, vol. 92(C).
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More about this item
Keywords
Backtest; Expected shortfall; Multiperiod risk forecasting; Value-at-risk;All these keywords.
JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
- G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
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