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A Random Matrix Approach to Credit Risk

  • Michael C. M\"unnix
  • Rudi Sch\"afer
  • Thomas Guhr
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    We estimate generic statistical properties of a structural credit risk model by considering an ensemble of correlation matrices. This ensemble is set up by Random Matrix Theory. We demonstrate analytically that the presence of correlations severely limits the effect of diversification in a credit portfolio if the correlations are not identically zero. The existence of correlations alters the tails of the loss distribution considerably, even if their average is zero. Under the assumption of randomly fluctuating correlations, a lower bound for the estimation of the loss distribution is provided.

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    File URL: http://arxiv.org/pdf/1102.3900
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    Paper provided by arXiv.org in its series Papers with number 1102.3900.

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    Date of creation: Feb 2011
    Date of revision: Jun 2011
    Handle: RePEc:arx:papers:1102.3900
    Contact details of provider: Web page: http://arxiv.org/

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    1. Laurent Laloux & Pierre Cizeau & Jean-Philippe Bouchaud & Marc Potters, 1998. "Noise dressing of financial correlation matrices," Science & Finance (CFM) working paper archive 500051, Science & Finance, Capital Fund Management.
    2. Jarrow, Robert A & Turnbull, Stuart M, 1995. " Pricing Derivatives on Financial Securities Subject to Credit Risk," Journal of Finance, American Finance Association, vol. 50(1), pages 53-85, March.
    3. Jarrow, Robert A & Lando, David & Turnbull, Stuart M, 1997. "A Markov Model for the Term Structure of Credit Risk Spreads," Review of Financial Studies, Society for Financial Studies, vol. 10(2), pages 481-523.
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