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A Random Matrix Approach to Credit Risk

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  • Michael C Münnix
  • Rudi Schäfer
  • Thomas Guhr

Abstract

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.

Suggested Citation

  • Michael C Münnix & Rudi Schäfer & Thomas Guhr, 2014. "A Random Matrix Approach to Credit Risk," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-9, May.
    • Handle: RePEc:plo:pone00:0098030
    DOI: 10.1371/journal.pone.0098030
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    References listed on IDEAS

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    Cited by:

    1. Demidov, Denis & Frahm, Klaus M. & Shepelyansky, Dima L., 2020. "What is the central bank of Wikipedia?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    2. Andreas Muhlbacher & Thomas Guhr, 2018. "Credit Risk Meets Random Matrices: Coping with Non-Stationary Asset Correlations," Papers 1803.00261, arXiv.org.
    3. Joachim Sicking & Thomas Guhr & Rudi Schafer, 2016. "Concurrent Credit Portfolio Losses," Papers 1604.06917, arXiv.org, revised Jan 2017.
    4. Joachim Sicking & Thomas Guhr & Rudi Schäfer, 2018. "Concurrent credit portfolio losses," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-20, February.
    5. Leonardo Ermann & Dima L. Shepelyansky, 2015. "Google matrix analysis of the multiproduct world trade network," Papers 1501.03371, arXiv.org.
    6. Andreas Mühlbacher & Thomas Guhr, 2018. "Extreme Portfolio Loss Correlations in Credit Risk," Risks, MDPI, vol. 6(3), pages 1-25, July.
    7. Andreas Mühlbacher & Thomas Guhr, 2018. "Credit Risk Meets Random Matrices: Coping with Non-Stationary Asset Correlations," Risks, MDPI, vol. 6(2), pages 1-25, April.
    8. Andreas Muhlbacher & Thomas Guhr, 2017. "Extreme portfolio loss correlations in credit risk," Papers 1706.09809, arXiv.org.

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