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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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    4. 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.
    5. 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.
    6. 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.
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    8. 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. Mariano González-Sánchez & Eva M. Ibáñez Jiménez & Ana I. Segovia San Juan, 2022. "Market and model risks: a feasible joint estimate methodology," Risk Management, Palgrave Macmillan, vol. 24(3), pages 187-213, September.
    2. Stahl, Gerhard & Sibbertsen, Philipp & Bertram, Philip, 2011. "Modellrisiko = Spezifikation + Validierung," Hannover Economic Papers (HEP) dp-468, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Gourieroux, Christian & Tiomo, Andre, 2019. "The Evaluation of Model Risk for Probability of Default and Expected Loss," MPRA Paper 95795, University Library of Munich, Germany.
    4. 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.
    5. Dannenberg, Henry, 2011. "The Importance of Estimation Uncertainty in a Multi-Rating Class Loan Portfolio," IWH Discussion Papers 11/2011, Halle Institute for Economic Research (IWH).
    6. 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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