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On comparing the accuracy of default predictions in the rating industry

Author

Listed:
  • Prof. Dr. Walter Krämer

    (Faculty of Statistics, Dortmund University of Technology)

  • Andre Güttler

    (Universität Frankfurt, Finance Department)

Abstract

We consider 1927 borrowers from 54 countries who had a credit rating by both Moody's and S&P at the end of 1998, and their subsequent default history up to the end of 2002. Viewing bond ratings as predicted probabilities of default, we consider partial orderings among competing probability forecasters and show that Moody's and S&P cannot be ordered according to any of these. Therefore, the relative performance of the agencies depends crucially on the way in which probability predictions are compared.

Suggested Citation

  • Prof. Dr. Walter Krämer & Andre Güttler, "undated". "On comparing the accuracy of default predictions in the rating industry," Working Papers 2, Business and Social Statistics Department, Technische Universität Dortmund, revised Oct 2006.
    • Handle: RePEc:dor:wpaper:2
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    Cited by:

    1. Kurt Hornik & Rainer Jankowitsch & Manuel Lingo & Stefan Pichler & Gerhard Winkler, 2010. "Determinants of heterogeneity in European credit ratings," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 24(3), pages 271-287, September.
    2. Simon Cornée, 2014. "Soft Information and Default Prediction in Cooperative and Social Banks," Journal of Entrepreneurial and Organizational Diversity, European Research Institute on Cooperative and Social Enterprises, vol. 3(1), pages 89-103, June.
    3. Morkoetter, Stefan & Stebler, Roman & Westerfeld, Simone, 2017. "Competition in the credit rating Industry: Benefits for investors and issuers," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 235-257.
    4. Chang, Charles & Fuh, Cheng-Der & Kao, Chu-Lan Michael, 2017. "Reading between the ratings: Modeling residual credit risk and yield overlap," Journal of Banking & Finance, Elsevier, vol. 81(C), pages 114-135.
    5. Orth, Walter, 2010. "The predictive accuracy of credit ratings: Measurement and statistical inference," MPRA Paper 30148, University Library of Munich, Germany, revised 16 Feb 2011.
    6. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    7. Andre Güttler & Peter Raupach, 2010. "The Impact of Downward Rating Momentum," Journal of Financial Services Research, Springer;Western Finance Association, vol. 37(1), pages 1-23, February.
    8. Christophe Godlewski, 2004. "Are Bank Ratings Coherent with Bank Default Probabilities in Emerging Market Economies ?," Finance 0409023, University Library of Munich, Germany.

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