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Bayesian forecasting of Value at Risk and Expected Shortfall using adaptive importance sampling
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- Christophe M. Boucher & Bertrand B. Maillet, 2013. "Learning by Failing: A Simple VaR Buffer," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 22(2), pages 113-127, May.
- Stavros Degiannakis & Pamela Dent & Christos Floros, 2014.
"A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification,"
Manchester School, University of Manchester, vol. 82(1), pages 71-102, January.
- 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.
- Parrini, Alessandro, 2013. "Importance Sampling for Portfolio Credit Risk in Factor Copula Models," MPRA Paper 103745, University Library of Munich, Germany.
- Lennart F. Hoogerheide & David Ardia & Nienke Corre, 2011.
"Stock Index Returns' Density Prediction using GARCH Models: Frequentist or Bayesian Estimation?,"
Tinbergen Institute Discussion Papers
11-020/4, Tinbergen Institute.
- Ardia, David & Lennart, Hoogerheide & Nienke, Corré, 2011. "Stock index returns’ density prediction using GARCH models: Frequentist or Bayesian estimation?," MPRA Paper 28259, University Library of Munich, Germany.
- Ardia, David & Hoogerheide, Lennart F., 2014.
"GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts,"
Economics Letters, Elsevier, vol. 123(2), pages 187-190.
- David Ardia & Lennart Hoogerheide, 2013. "GARCH Models for Daily Stock Returns: Impact of Estimation Frequency on Value-at-Risk and Expected Shortfall Forecasts," Tinbergen Institute Discussion Papers 13-047/III, Tinbergen Institute.
- Hoogerheide, Lennart & Opschoor, Anne & van Dijk, Herman K., 2012.
"A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation,"
Journal of Econometrics, Elsevier, vol. 171(2), pages 101-120.
- Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2012. "A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation," Tinbergen Institute Discussion Papers 12-026/4, Tinbergen Institute.
- Bruno Bouchard & Adil Reghai & Benjamin Virrion, 2021. "Computation of Expected Shortfall by fast detection of worst scenarios," Post-Print hal-02619589, HAL.
- Ardia, David & Hoogerheide, Lennart F. & van Dijk, Herman K., 2009.
"Adaptive Mixture of Student-t Distributions as a Flexible Candidate Distribution for Efficient Simulation: The R Package AdMit,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i03).
- David Ardia & Lennart F. Hoogerheide & Herman K. van Dijk, 2008. "Adaptive Mixture of Student-t distributions as a Flexible Candidate Distribution for Efficient Simulation: the R Package AdMit," Tinbergen Institute Discussion Papers 08-062/4, Tinbergen Institute, revised 15 Dec 2008.
- Ardia, David & Hoogerheide, Lennart F. & van Dijk, Herman K., 2008. "Adaptive mixture of Student-t distributions as a flexible candidate distribution for efficient simulation: the R package AdMit," DQE Working Papers 9, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 07 Jan 2009.
- Borowska, Agnieszka & Hoogerheide, Lennart & Koopman, Siem Jan & van Dijk, Herman K., 2020.
"Partially censored posterior for robust and efficient risk evaluation,"
Journal of Econometrics, Elsevier, vol. 217(2), pages 335-355.
- Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman K. van Dijk, 2019. "Partially Censored Posterior for robust and efficient risk evaluation," Working Paper 2019/12, Norges Bank.
- Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
- 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.
- Aknouche Abdelhakim & Demmouche Nacer & Dimitrakopoulos Stefanos & Touche Nassim, 2020. "Bayesian analysis of periodic asymmetric power GARCH models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-24, September.
- Kim, Dongwhan & Kang, Kyu Ho, 2021. "Conditional value-at-risk forecasts of an optimal foreign currency portfolio," International Journal of Forecasting, Elsevier, vol. 37(2), pages 838-861.
- Begen, Mehmet A. & Pun, Hubert & Yan, Xinghao, 2016. "Supply and demand uncertainty reduction efforts and cost comparison," International Journal of Production Economics, Elsevier, vol. 180(C), pages 125-134.
- Qiang Xia & Heung Wong & Jinshan Liu & Rubing Liang, 2017. "Bayesian Analysis of Power-Transformed and Threshold GARCH Models: A Griddy-Gibbs Sampler Approach," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 353-372, October.
- Lukasz Gatarek & Lennart Hoogerheide & Koen Hooning & Herman K. van Dijk, 2013. "Censored Posterior and Predictive Likelihood in Left-Tail Prediction for Accurate Value at Risk Estimation," Tinbergen Institute Discussion Papers 13-060/III, Tinbergen Institute, revised 06 Mar 2014.
- Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
- Aknouche, Abdelhakim & Demmouche, Nacer & Touche, Nassim, 2018. "Bayesian MCMC analysis of periodic asymmetric power GARCH models," MPRA Paper 91136, University Library of Munich, Germany.
- Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman, 2019. "Bayesian Risk Forecasting for Long Horizons," Tinbergen Institute Discussion Papers 19-018/III, Tinbergen Institute.
- Fu, Jin-Yu & Lin, Jin-Guan & Hao, Hong-Xia, 2023. "Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1698-1712.
- Hoogerheide, Lennart F. & Ardia, David & Corré, Nienke, 2012. "Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?," Economics Letters, Elsevier, vol. 116(3), pages 322-325.
- Bruno Bouchard & Adil Reghai & Benjamin Virrion, 2020. "Computation of Expected Shortfall by fast detection of worst scenarios," Papers 2005.12593, arXiv.org.
- Chen, Qian & Gerlach, Richard & Lu, Zudi, 2012. "Bayesian Value-at-Risk and expected shortfall forecasting via the asymmetric Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3498-3516.
- Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2011. "A Class of Adaptive EM-based Importance Sampling Algorithms for Efficient and Robust Posterior and Predictive Simulation," Tinbergen Institute Discussion Papers 11-004/4, Tinbergen Institute.
- Spada, Matteo & Paraschiv, Florentina & Burgherr, Peter, 2018. "A comparison of risk measures for accidents in the energy sector and their implications on decision-making strategies," Energy, Elsevier, vol. 154(C), pages 277-288.
- Olofsson, Petter & Råholm, Anna & Uddin, Gazi Salah & Troster, Victor & Kang, Sang Hoon, 2021. "Ethical and unethical investments under extreme market conditions," International Review of Financial Analysis, Elsevier, vol. 78(C).
- Bruno Bouchard & Adil Reghai & Benjamin Virrion, 2020. "Computation of Expected Shortfall by fast detection of worst scenarios," Working Papers hal-02619589, HAL.
- Lennart F. Hoogerheide & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Backtesting Value-at-Risk using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann," Tinbergen Institute Discussion Papers 11-131/4, Tinbergen Institute.
- Gerlach, Richard & Abeywardana, Sachin, 2016. "Variational Bayes for assessment of dynamic quantile forecasts," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1385-1402.
- Jiarui Chu & Ludovic Tangpi, 2021. "Non-asymptotic estimation of risk measures using stochastic gradient Langevin dynamics," Papers 2111.12248, arXiv.org, revised Feb 2023.