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Credit risk stress testing and copulas: Is the Gaussian copula better than its reputation?

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  • Koziol, Philipp
  • Schell, Carmen
  • Eckhardt, Meik

Abstract

In the last decade, stress tests have become indispensable in bank risk management which has led to significantly increased requirements for stress tests for banks and regulators. Although the complexity of stress testing frameworks has been enhanced considerably over the course of the last few years, the majority of credit risk models (e.g. Merton (1974), CreditMetrics, KMV) still rely on Gaussian copulas. This paper complements the finance literature providing new insights into the impact of different copulas in stress test applications using supervisory data of 17 large German banks. Our findings imply that the use of a Gaussian copula in credit risk stress testing should not by default be dismissed in favor of a heavy-tailed copula which is widely recommended in the finance literature. Gaussian copula would be the appropriate choice for estimating high stress effects under extreme scenarios. Heavy-tailed copulas like the Clayton or the t copula are recommended in the case of less severe scenarios. Furthermore, the paper provides clear advice for designing a credit risk stress test.

Suggested Citation

  • Koziol, Philipp & Schell, Carmen & Eckhardt, Meik, 2015. "Credit risk stress testing and copulas: Is the Gaussian copula better than its reputation?," Discussion Papers 46/2015, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdps:462015
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    References listed on IDEAS

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    Cited by:

    1. Nneka Umeorah & Phillip Mashele & Matthias Ehrhardt, 2021. "Pricing basket default swaps using quasi-analytic techniques," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 241-267, June.
    2. Siemsen, Thomas & Vilsmeier, Johannes, 2017. "A stress test framework for the German residential mortgage market: Methodology and application," Discussion Papers 37/2017, Deutsche Bundesbank.
    3. Lourme, Alexandre & Maurer, Frantz, 2017. "Testing the Gaussian and Student's t copulas in a risk management framework," Economic Modelling, Elsevier, vol. 67(C), pages 203-214.
    4. Ghufran Ahmad & Muhammad Suhail Rizwan & Dawood Ashraf, 2021. "Systemic risk and macroeconomic forecasting: A globally applicable copula‐based approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1420-1443, December.
    5. Christian Bucio Pacheco & Luis Villanueva & Raúl de Jesús Gutiérrez, 2021. "Dependence in the Banking Sector of the United States and Mexico: A Copula Approach," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(TNEA), pages 1-23, Septiembr.

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    More about this item

    Keywords

    credit risk; top-down stress tests; copulas; macroeconomic scenario;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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