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Modeling Dependent Credit Risks for Application to Off-Site Banking Supervision


  • Evgenia Glogova

    () (Oesterreichische Nationalbank)

  • Richard Warnung

    () (Institute of Mathematical Methods in Economics, Research Unit Financial and Actuarial Mathematics, Vienna University of Technology)


During the past five years the Oesterreichische Nationalbank (OeNB), together with the Austrian Financial Market Authority (FMA) and university experts, has developed and implemented several modern tools for the purposes of off-site banking analysis and supervision. One of these tools is the Value-at-Risk (VaR) model, which allows for the standardized quantification of every single bank’s economic capital. Within this portfolio model framework, a total VaR is calculated as an aggregation of credit, market and operational VaR, assuming perfect correlation between the risk categories. The methodology for measuring the credit risk of a bank’s portfolio is currently based on the standard CreditRisk+ model, an actuarial model for aggregating risks in a credit portfolio with a single risk factor. In 2005 the OeNB and the Vienna University of Technology launched a research project with the aim of developing an extended version of the credit risk model that is able to account better for portfolio diversification effects. As the background risk factors in the standard CreditRisk model have to be orthogonal, resemblance to real-world industrial sectors or other macroeconomic factors, which often appear to be strongly correlated, is not possible. This paper gives an overview of our approach to modeling correlations among systematic risk factors. Other extensions of the model, like the ability to calculate a single obligor’s risk contribution and the incorporation of stochastic loss given default, are touched upon.

Suggested Citation

  • Evgenia Glogova & Richard Warnung, 2006. "Modeling Dependent Credit Risks for Application to Off-Site Banking Supervision," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 12, pages 79-91.
  • Handle: RePEc:onb:oenbfs:y:2006:i:12:b:2

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    References listed on IDEAS

    1. Paul Louis Ceriel Hilbers & Matthew T Jones & Graham L Slack, 2004. "Stress Testing Financial Systems; What to Do When the Governor Calls," IMF Working Papers 04/127, International Monetary Fund.
    2. Ceyla Pazarbasioglu & Gudrun Johnsen & Paul Louis Ceriel Hilbers & Inci Ötker, 2005. "Assessing and Managing Rapid Credit Growth and the Role of Supervisory and Prudential Policies," IMF Working Papers 05/151, International Monetary Fund.
    3. Petr JAKUBÍK, 2007. "Macroeconomic Environment and Credit Risk (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(1-2), pages 60-78, March.
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    More about this item


    Financial Stability;

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation


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