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Auswirkungen unterschiedlicher Assetkorrelationen in Mehr-Sektoren-Kreditportfoliomodellen

Listed author(s):
  • Hamerle, Alfred
  • Knapp, Michael
  • Wildenauer, Nicole
Registered author(s):

    Im vorliegenden Beitrag wird untersucht, wie die Assetkorrelation zwischen zwei Sektoren auf einfache Weise berechnet werden kann und wie sich unterschiedliche Korrelationsannahmen auf die Form und Risikomaße von Verlustverteilungen auswirken. Dazu werden Ausfallzeitreihen von zwei us-amerikanischen Sektoren untersucht. Zum einen wird das Segment Industrieunternehmen und zum anderen das Retailsegment Kreditkarten betrachtet. Es wird gezeigt, wie unter Verwendung eines dynamischen Modells die Schuldnerbonität bzw. die Ausfallwahrscheinlichkeit unter Einbeziehung schuldnerspezifischer und makroökonomischer Faktoren geschätzt werden kann. Es stellt sich heraus, dass durch die Einbeziehung vor allem makroökonomischer Größen die Ausfallwahrscheinlichkeit Point in Time prognostiziert und sowohl die Assetkorrelation innerhalb eines Sektors bzw. Risikosegments als auch die intersektorale Korrelation verringert werden können. Dies führt im Allgemeinen zu präziseren Prognosen der Verlustverteilungen. In this paper we focus on the analysis of the effect of the asset correlation between two segments, its basic calculation and its impacts on the risk measures of loss distributions. For an empirical study we examine default histories of two American segments. One is the sector industry and the other is the (retail) segment credit cards. We show how the borrowers creditworthiness and the probability of default can be estimated using issuer-specific and macroeconomic variables in a dynamic approach. Using macroeconomic variables the probability of default can be predicted point in time. The asset correlation within a sector as well as the asset correlation between sectors can be reduced leading to a more precise prediction of loss distributions.

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    Paper provided by University of Regensburg, Department of Economics in its series University of Regensburg Working Papers in Business, Economics and Management Information Systems with number 409.

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    Date of creation: 2005
    Handle: RePEc:bay:rdwiwi:582
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    1. Merton, Robert C., 1977. "On the pricing of contingent claims and the Modigliani-Miller theorem," Journal of Financial Economics, Elsevier, vol. 5(2), pages 241-249, November.
    2. Rösch, Daniel, 2003. "Correlations and Business Cycles of Credit Risk: Evidence from Bankruptcies in Germany," University of Regensburg Working Papers in Business, Economics and Management Information Systems 380, University of Regensburg, Department of Economics.
    3. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
    4. Robert A. Jarrow & Stuart M. Turnbull, 2008. "Pricing Derivatives on Financial Securities Subject to Credit Risk," World Scientific Book Chapters,in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 17, pages 377-409 World Scientific Publishing Co. Pte. Ltd..
    5. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    6. Hamerle, Alfred & Liebig, Thilo & Rösch, Daniel, 2003. "Credit Risk Factor Modeling and the Basel II IRB Approach," Discussion Paper Series 2: Banking and Financial Studies 2003,02, Deutsche Bundesbank, Research Centre.
    7. Duffie, Darrell & Singleton, Kenneth J, 1999. "Modeling Term Structures of Defaultable Bonds," Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 687-720.
    8. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    9. Hamerle, Alfred & Liebig, Thilo & Scheule, Harald, 2004. "Forecasting Credit Portfolio Risk," Discussion Paper Series 2: Banking and Financial Studies 2004,01, Deutsche Bundesbank, Research Centre.
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