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Modellkonsistente Bestimmung des LGD im IRB-Ansatz von Basel II

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  • Gürtler, Marc
  • Heithecker, Dirk

Abstract

Gemäß den im Juni 2004 durch den Baseler Ausschuss endgültig verabschiedeten Kapitalstandards (Basel II) sind Kredite in Höhe des so genannten unerwarteten Verlusts mit Eigenkapital zu unterlegen. Für erwartete Verluste hat das jeweilige Kreditinstitut Rückstellungen zu bilden, wobei hier etwaige Differenzen in der Eigenkapitalunterlegung zu berücksichtigen sind. Damit die folglich relevanten Größen des unerwarteten und des erwarteten Verlusts ermittelbar sind, benötigt man für einen Kredit die Kenntnis der erwarteten Ausfallwahrscheinlichkeit (PD) und der erwarteten Verlustquote bei Ausfall (LGD). Während in Basel II für die Größe PD konkrete Vorschriften zur Bestimmung vorliegen, die auf dem Kreditrisikomodell von Vasicek (1987/1991) basieren, sind die Vorgaben zur Ermittlung des LGD noch ungenau und bilden allenfalls einen Rahmen, der für die Umsetzung zu beachten ist. Inhalt dieses Beitrags ist daher die Entwicklung einer auf dem Modell von Vasicek basierenden Berechnungsvorschrift für die Größe LGD, die den Rahmenbedingungen von Basel II genügt und darüber hinaus eine sachgerechte Berücksichtigung von Kreditsicherheiten vorsieht.

Suggested Citation

  • Gürtler, Marc & Heithecker, Dirk, 2004. "Modellkonsistente Bestimmung des LGD im IRB-Ansatz von Basel II," Working Papers FW08V3, Technische Universität Braunschweig, Institute of Finance.
  • Handle: RePEc:zbw:tbsifw:fw08v3
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    References listed on IDEAS

    as
    1. Briys, Eric & de Varenne, François, 1997. "Valuing Risky Fixed Rate Debt: An Extension," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(2), pages 239-248, June.
    2. Black, Fischer & Cox, John C, 1976. "Valuing Corporate Securities: Some Effects of Bond Indenture Provisions," Journal of Finance, American Finance Association, vol. 31(2), pages 351-367, May.
    3. repec:zbw:bofrdp:2000_002 is not listed on IDEAS
    4. 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.
    5. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July.
    6. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
    7. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
    8. Düllmann, Klaus & Trapp, Monika, 2004. "Systematic Risk in Recovery Rates: An Empirical Analysis of US Corporate Credit Exposures," Discussion Paper Series 2: Banking and Financial Studies 2004,02, Deutsche Bundesbank.
    9. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
    10. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Basel II; Kapitalstandards; Loss Given Default; Probability of Default; Kreditrisiko; Kreditsicherheiten; Basel II; Capital Adequacy Requirements; Loss Given Default; Probability of Default; Collateral; Credit Risk;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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