Evaluating the Precision of Estimators of Quantile-Based Risk Measures
AbstractThis paper examines the precision of estimators of Quantile-Based Risk Measures (Value at Risk, Expected Shortfall, Spectral Risk Measures). It first addresses the question of how to estimate the precision of these estimators, and proposes a Monte Carlo method that is free of some of the limitations of existing approaches. It then investigates the distribution of risk estimators, and presents simulation results suggesting that the common practice of relying on asymptotic normality results might be unreliable with the sample sizes commonly available to them. Finally, it investigates the relationship between the precision of different risk estimators and the distribution of underlying losses (or returns), and yields a number of useful conclusions.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 3504.
Date of creation: 2007
Date of revision:
Other versions of this item:
- Kevin Dowd & John Cotter, 2011. "Evaluating the Precision of Estimators of Quantile-Based Risk Measures," Papers 1103.5665, arXiv.org.
- John Cotter & Kevin Dowd, 2011. "Evaluating the Precision of Estimators of Quantile-Based Risk Measures," Working Papers 200743, Geary Institute, University College Dublin.
- G00 - Financial Economics - - General - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-06-18 (All new papers)
- NEP-ECM-2007-06-18 (Econometrics)
- NEP-RMG-2007-06-18 (Risk Management)
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- Christian Gourieroux & J. P. Laurent & Olivier Scaillet, 2000.
"Sensitivity Analysis of Values at Risk,"
Econometric Society World Congress 2000 Contributed Papers
0162, Econometric Society.
- Christian Gourieroux & Jean-Paul Laurent & Olivier Scaillet, 2000. "Sensitivity Analysis of Values at Risk," Working Papers 2000-05, Centre de Recherche en Economie et Statistique.
- Gouriéroux, Christian & Laurent, J.P. & Scaillet, Olivier, 1999. "Sensitivity Analysis of Values at Risk," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2000002, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES), revised 00 Jan 2000.
- C. Gourieroux & J.P. Laurent & O. Scaillet, 2000. "Sensitivity analysis of values at risk," THEMA Working Papers 2000-04, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- Cotter, JOhn & Dowd, Kevin, 2006.
"Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements,"
3505, University Library of Munich, Germany.
- Cotter, John & Dowd, Kevin, 2006. "Extreme spectral risk measures: An application to futures clearinghouse margin requirements," Journal of Banking & Finance, Elsevier, vol. 30(12), pages 3469-3485, December.
- John Cotter & Kevin Dowd, 2011. "Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements," Papers 1103.5653, arXiv.org.
- John Cotter & Kevin Dowd, 2011. "Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements," Working Papers 200516, Geary Institute, University College Dublin.
- 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.
- Frey, Rudiger & McNeil, Alexander J., 2002. "VaR and expected shortfall in portfolios of dependent credit risks: Conceptual and practical insights," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1317-1334, July.
- repec:fth:inseep:2000-05 is not listed on IDEAS
- Yamai, Yasuhiro & Yoshiba, Toshinao, 2002. "Comparative Analyses of Expected Shortfall and Value-at-Risk: Their Estimation Error, Decomposition, and Optimization," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 20(1), pages 87-121, January.
- Tak Siu & Howell Tong & Hailiang Yang, 2004. "On Bayesian Value at Risk: From Linear to Non-Linear Portfolios," Asia-Pacific Financial Markets, Springer, vol. 11(2), pages 161-184, June.
- Matthew Pritsker, 1997. "Evaluating Value at Risk Methodologies: Accuracy versus Computational Time," Journal of Financial Services Research, Springer, vol. 12(2), pages 201-242, October.
- O. Scaillet, 2004. "Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall," Mathematical Finance, Wiley Blackwell, vol. 14(1), pages 115-129.
- Song Xi Chen, 2005. "Nonparametric Inference of Value-at-Risk for Dependent Financial Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(2), pages 227-255.
- Acerbi, Carlo, 2002. "Spectral measures of risk: A coherent representation of subjective risk aversion," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1505-1518, July.
- Christian Gourieroux & Wei Liu, 2006. "Sensitivity Analysis of Distortion Risk Measures," Working Papers 2006-33, Centre de Recherche en Economie et Statistique.
- Song Xi Chen, 2008. "Nonparametric Estimation of Expected Shortfall," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(1), pages 87-107, Winter.
- Wächter, Hans Peter & Mazzoni, Thomas, 2013. "Consistent modeling of risk averse behavior with spectral risk measures," European Journal of Operational Research, Elsevier, vol. 229(2), pages 487-495.
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