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Measuring Model Risk

Author

Listed:
  • Sibbertsen, Philipp
  • Stahl, Gerhard
  • Luedtke, Corinna

Abstract

Model risk as part of the operational risk is a serious problem for financial institutions. As the pricing of derivatives as well as the computation of the market or credit risk of an institution depend on statistical models the application of a wrong model can lead to a serious over- or underestimation of the institution’s risk. Because the underlying data generating process is unknown in practice evaluating the model risk is a challenge. So far, definitions of model risk are either application-oriented including risk induced by the statistician rather than by the statistical model or research-oriented and too abstract to be used in practice. Especially, they are not data-driven. We introduce a data driven notion of model risk which includes the features of the research-oriented approach by extending it by a statistical model building procedure and therefore compromises between the two definitions at hand. We furthermore suggest the application of robust estimates to reduce the model risk and advocate the application of stress tests with respect to the valuation of the portfolio.

Suggested Citation

  • Sibbertsen, Philipp & Stahl, Gerhard & Luedtke, Corinna, 2008. "Measuring Model Risk," Hannover Economic Papers (HEP) dp-409, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  • Handle: RePEc:han:dpaper:dp-409
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    References listed on IDEAS

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    1. Stefan Jaschke & Gerhard Stahl & Richard Stehle, 2007. "Value-at-risk forecasts under scrutiny—the German experience," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 621-636.
    2. Kerkhof, F.L.J. & Melenberg, B. & Schumacher, J.M., 2002. "Model Risk and Regulatory Capital," Other publications TiSEM 6b857b42-548f-416f-b37f-d, Tilburg University, School of Economics and Management.
    3. Philipp Sibbertsen, 1999. "S-Estimation in the Linear Regression Model with Long-Memory Error Terms," Computing in Economics and Finance 1999 512, Society for Computational Economics.
    4. Bakshi, Gurdip & Cao, Charles & Chen, Zhiwu, 1997. "Empirical Performance of Alternative Option Pricing Models," Journal of Finance, American Finance Association, vol. 52(5), pages 2003-2049, December.
    5. T. Clifton Green & Stephen Figlewski, 1999. "Market Risk and Model Risk for a Financial Institution Writing Options," Journal of Finance, American Finance Association, vol. 54(4), pages 1465-1499, August.
    6. Rama Cont & Romain Deguest & Giacomo Scandolo, 2010. "Robustness and sensitivity analysis of risk measurement procedures," Quantitative Finance, Taylor & Francis Journals, vol. 10(6), pages 593-606.
    7. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    8. Carol Alexander, 2005. "The Present and Future of Financial Risk Management," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(1), pages 3-25.
    9. Corradi, Valentina & Swanson, Norman R., 2006. "Predictive Density Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 5, pages 197-284, Elsevier.
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    Citations

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    Cited by:

    1. Stahl, Gerhard & Sibbertsen, Philipp & Bertram, Philip, 2011. "Modellrisiko = Spezifikation + Validierung," Hannover Economic Papers (HEP) dp-468, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Schlegel, Friederike & Hakenes, Hendrik, 2013. "Model Risk - an Agency Theoretic Approach," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79954, Verein für Socialpolitik / German Economic Association.
    3. Volker Stein & Arnd Wiedemann, 2016. "Risk governance: conceptualization, tasks, and research agenda," Journal of Business Economics, Springer, vol. 86(8), pages 813-836, November.

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    More about this item

    Keywords

    risk evaluation; model risk; robust estimation; stress tests;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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