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Default and Recovery Risk Dependencies in a Simple Credit Risk Model

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Listed:
  • Benjamin Bade
  • Daniel Rösch
  • Harald Scheule

Abstract

This paper provides evidence for the relationship between credit quality, recovery rate, and correlation. The paper finds that rating grade, rating shift, and macroeconomic factors provide a highly significant explanation for default risk and recovery risk of US bond issues. The empirical data suggest that default and recovery processes are highly correlated. Therefore, a joint approach is required for estimating time†varying default probabilities and recovery rates that are conditional on default. This paper develops and applies such a model.

Suggested Citation

  • Benjamin Bade & Daniel Rösch & Harald Scheule, 2011. "Default and Recovery Risk Dependencies in a Simple Credit Risk Model," European Financial Management, European Financial Management Association, vol. 17(1), pages 120-144, January.
  • Handle: RePEc:bla:eufman:v:17:y:2011:i:1:p:120-144
    DOI: 10.1111/j.1468-036X.2010.00582.x
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    References listed on IDEAS

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    1. Hans Gersbach & Alexander Lipponer, 2003. "Firm Defaults and the Correlation Effect," European Financial Management, European Financial Management Association, vol. 9(3), pages 361-378, September.
    2. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
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    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.
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    More about this item

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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