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Extreme Value at Risk and Expected Shortfall during Financial Crisis

  • L. Kourouma

    (CERAG - Centre d'études et de recherches appliquées à la gestion - CNRS : UMR5820 - Université Pierre Mendès-France - Grenoble II)

  • D. Dupre

    (CERAG - Centre d'études et de recherches appliquées à la gestion - CNRS : UMR5820 - Université Pierre Mendès-France - Grenoble II, IAE Grenoble - Institut d'Administration des Entreprises - Grenoble - Université Pierre Mendès-France - Grenoble II)

  • G. Sanfilippo

    (CERAG - Centre d'études et de recherches appliquées à la gestion - CNRS : UMR5820 - Université Pierre Mendès-France - Grenoble II)

  • O. Taramasco

    (CERAG - Centre d'études et de recherches appliquées à la gestion - CNRS : UMR5820 - Université Pierre Mendès-France - Grenoble II)

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    This paper investigates Value at Risk and Expected Shortfall for CAC 40, S&P 500, Wheat and Crude Oil indexes during the 2008 financial crisis. We show an underestimation of the risk of loss for the unconditional VaR models as compared with the conditional models. This underestimation is stronger using the historical VaR approach than when using the extreme values theory VaR model. Even in 2008 financial crisis, the conditional EVT model is more accurate and reliable for predicting the asset risk losses. Banks have no interest in using it because the Basel II agreement penalizes banks using accuracy models like the conditional EVT model, and this is the case for the assets being studied in this paper.

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    Paper provided by HAL in its series Post-Print with number halshs-00658495.

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    Date of creation: 2011
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    Handle: RePEc:hal:journl:halshs-00658495
    Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00658495/en/
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    1. Longin, Francois M., 2000. "From value at risk to stress testing: The extreme value approach," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1097-1130, July.
    2. Jose A. Lopez, 1996. "Regulatory Evaluation of Value-at-Risk Models," Center for Financial Institutions Working Papers 96-51, Wharton School Center for Financial Institutions, University of Pennsylvania.
    3. 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.
    4. Viviana Fernández, 2003. "Extreme Value Theory and Value at Risk," Documentos de Trabajo 154, Centro de Economía Aplicada, Universidad de Chile.
    5. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics.
    6. Suleyman Basak & Alex Shapiro, . "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.
    7. Marimoutou, Velayoudoum & Raggad, Bechir & Trabelsi, Abdelwahed, 2009. "Extreme Value Theory and Value at Risk: Application to oil market," Energy Economics, Elsevier, vol. 31(4), pages 519-530, July.
    8. Gencay, Ramazan & Selcuk, Faruk, 2004. "Extreme value theory and Value-at-Risk: Relative performance in emerging markets," International Journal of Forecasting, Elsevier, vol. 20(2), pages 287-303.
    9. 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.
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