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Bayesian Value-at-Risk and expected shortfall forecasting via the asymmetric Laplace distribution
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- Chen, Qian & Gerlach, Richard H., 2013. "The two-sided Weibull distribution and forecasting financial tail risk," International Journal of Forecasting, Elsevier, vol. 29(4), pages 527-540.
- Chen, Liyuan & Zerilli, Paola & Baum, Christopher F., 2019.
"Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications,"
Energy Economics, Elsevier, vol. 79(C), pages 111-129.
- Liyuan Chen & Paola Zerilli & Christopher F Baum, 2018. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Boston College Working Papers in Economics 953, Boston College Department of Economics.
- Alexander, Carol & Kaeck, Andreas & Sumawong, Anannit, 2019. "A parsimonious parametric model for generating margin requirements for futures," European Journal of Operational Research, Elsevier, vol. 273(1), pages 31-43.
- Cathy W. S. Chen & Edward M. H. Lin & Tara F. J. Huang, 2022. "Bayesian quantile forecasting via the realized hysteretic GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1317-1337, November.
- Xiaochun Liu, 2017.
"An integrated macro‐financial risk‐based approach to the stressed capital requirement,"
Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 86-98, September.
- Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.
- Dimitriadis, Timo & Liu, Xiaochun & Schnaitmann, Julie, 2020.
"Encompassing tests for value at risk and expected shortfall multi-step forecasts based on inference on the boundary,"
Hohenheim Discussion Papers in Business, Economics and Social Sciences
11-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
- Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
- Ahmed Ali & Granberg Mark & Uddin Gazi Salah & Troster Victor, 2022.
"Asymmetric dynamics between uncertainty and unemployment flows in the United States,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 155-172, February.
- Ahmed, Ali & Granberg, Mark & Troster, Victor & Uddin, Gazi Salah, 2020. "Asymmetric Dynamics between Uncertainty and Unemployment Flows in the United States," LiU Working Papers in Economics 7, Linköping University, Division of Economics, Department of Management and Engineering.
- Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
- Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
- Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.
- 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.
- Francq, Christian & Jiménez Gamero, Maria Dolores & Meintanis, Simos, 2015. "Tests for sphericity in multivariate garch models," MPRA Paper 67411, University Library of Munich, Germany.
- C. A. Abanto-Valle & V. H. Lachos & Dipak K. Dey, 2015. "Bayesian Estimation of a Skew-Student-t Stochastic Volatility Model," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 721-738, September.
- Li, Leon, 2017. "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 116-135.
- Karmakar, Madhusudan & Paul, Samit, 2016. "Intraday risk management in International stock markets: A conditional EVT approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 34-55.
- Xiaochun Liu, 2016.
"Markov switching quantile autoregression,"
Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
- Liu, Xiaochun, 2013. "Markov-Switching Quantile Autoregression," MPRA Paper 55800, University Library of Munich, Germany.
- Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
- Wilson Ye Chen & Richard H. Gerlach, 2017. "Semiparametric GARCH via Bayesian model averaging," Papers 1708.07587, arXiv.org.
- Marius Lux & Wolfgang Karl Härdle & Stefan Lessmann, 2020.
"Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid,"
Computational Statistics, Springer, vol. 35(3), pages 947-981, September.
- Lux, Marius & Härdle, Wolfgang Karl & Lessmann, Stefan, 2018. "Data Driven Value-at-Risk Forecasting using a SVR-GARCH-KDE Hybrid," IRTG 1792 Discussion Papers 2018-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Saralees Nadarajah & Bo Zhang & Stephen Chan, 2014. "Estimation methods for expected shortfall," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 271-291, February.
- Chao Wang & Qian Chen & Richard Gerlach, 2017. "Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution," Papers 1707.03715, arXiv.org.
- Emrah Altun, 2019. "Two-sided exponential–geometric distribution: inference and volatility modeling," Computational Statistics, Springer, vol. 34(3), pages 1215-1245, September.
- Vica Tendenan & Richard Gerlach & Chao Wang, 2020. "Tail risk forecasting using Bayesian realized EGARCH models," Papers 2008.05147, arXiv.org, revised Aug 2020.
- Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2014. "Bayesian estimation of smoothly mixing time-varying parameter GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 194-209.
- Francq, C. & Jiménez-Gamero, M.D. & Meintanis, S.G., 2017. "Tests for conditional ellipticity in multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 196(2), pages 305-319.
- Gerlach, Richard & Abeywardana, Sachin, 2016. "Variational Bayes for assessment of dynamic quantile forecasts," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1385-1402.
- Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
- Cerqueti, Roy & Giacalone, Massimiliano & Panarello, Demetrio, 2019. "A Generalized Error Distribution Copula-based method for portfolios risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 687-695.
- Richard Gerlach & Chao Wang, 2016. "Bayesian Semi-parametric Realized-CARE Models for Tail Risk Forecasting Incorporating Realized Measures," Papers 1612.08488, arXiv.org.
- Richard Gerlach & Declan Walpole & Chao Wang, 2017. "Semi-parametric Bayesian tail risk forecasting incorporating realized measures of volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 199-215, February.
- Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.