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The Riskiness of Risk Models

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  • Christophe Boucher

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, A.A.Advisors-QCG - ABN AMRO)

  • Bertrand Maillet

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, A.A.Advisors-QCG - ABN AMRO, EIF - Europlace Institute of Finance)

Abstract

We provide an economic valuation of the riskiness of risk models by directly measuring the impact of model risks (specification and estimation risks) on VaR estimates. We find that integrating the model risk into the VaR computations implies a substantial minimum correction of the order of 10-40% of VaR levels. We also present results of a practical method - based on a backtesting framework - for incorporating the model risk into the VaR estimates.

Suggested Citation

  • Christophe Boucher & Bertrand Maillet, 2011. "The Riskiness of Risk Models," Post-Print halshs-00587779, HAL.
    • Handle: RePEc:hal:journl:halshs-00587779
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00587779
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    References listed on IDEAS

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    1. 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.).
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    3. Kerkhof, Jeroen & Melenberg, Bertrand & Schumacher, Hans, 2010. "Model risk and capital reserves," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 267-279, January.
    4. Rama Cont, 2006. "Model Uncertainty And Its Impact On The Pricing Of Derivative Instruments," Mathematical Finance, Wiley Blackwell, vol. 16(3), pages 519-547, July.
    5. Rama Cont, 2006. "Model uncertainty and its impact on the pricing of derivative instruments," Post-Print halshs-00002695, HAL.
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