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Stress testing German banks against a global cost-of-capital shock

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  • Duellmann, Klaus
  • Kick, Thomas

Abstract

This paper introduces a stress test of the corporate credit portfolios of 24 large German banks by a two-stage approach: First, a macro-econometric model is used to forecast the impact of a substantial increase of the user cost of business capital for firms worldwide on three particularly export-oriented industry sectors in Germany. Second, the impact of this economic multi-sector stress on banks' credit portfolios is captured by a state-of-theart CreditMetrics-type portfolio model with sector-dependant unobservable risk factors as drivers of the systematic risk. The German credit register provides us with access to highly granular risk information on loan volumes and banks' internal estimates of default probabilities which is key for an accurate assessment of the impact of the stress scenario. We find that the increase of the capital charge for the unexpected loss needs to be considered together with the increase in banks' expected losses in order to assess the change of banks' capital ratios. We also confirm that highly granular information on the level of borrowerspecific probabilities of default has a significant impact on the outcome of the stress test.

Suggested Citation

  • Duellmann, Klaus & Kick, Thomas, 2012. "Stress testing German banks against a global cost-of-capital shock," Discussion Papers 04/2012, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubdps:042012
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    References listed on IDEAS

    as
    1. Klaus Düllmann & Nancy Masschelein, 2007. "A Tractable Model to Measure Sector Concentration Risk in Credit Portfolios," Journal of Financial Services Research, Springer;Western Finance Association, vol. 32(1), pages 55-79, October.
    2. Klaus Duellmann & Martin Erdelmeier, 2009. "Crash Testing German Banks," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 139-175, September.
    3. Helmut Elsinger & Alfred Lehar & Martin Summer, 2006. "Using Market Information for Banking System Risk Assessment," International Journal of Central Banking, International Journal of Central Banking, vol. 2(1), March.
    4. Thomas Breuer & Martin Jandacka & Klaus Rheinberger & Martin Summer, 2009. "How to Find Plausible, Severe and Useful Stress Scenarios," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 205-224, September.
    5. De Graeve, F. & Kick, T. & Koetter, M., 2008. "Monetary policy and financial (in)stability: An integrated micro-macro approach," Journal of Financial Stability, Elsevier, vol. 4(3), pages 205-231, September.
    6. Hanson, Samuel G. & Pesaran, M. Hashem & Schuermann, Til, 2008. "Firm heterogeneity and credit risk diversification," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 583-612, September.
    7. Mojon, Benoît & Peersman, Gert, 2001. "A VAR description of the effects of monetary policy in the individual countries of the euro area," Working Paper Series 92, European Central Bank.
    8. Miguel A. Segoviano, 2006. "Portfolio Credit Risk and Macroeconomic Shocks: Applications to Stress Testing Under Data-Restricted Environments," IMF Working Papers 2006/283, International Monetary Fund.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Asset correlation; portfolio credit risk; macroeconomic stress tests;
    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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