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On comparing the accuracy of default predictions in the rating industry

  • Prof. Dr. Walter Krämer

    ()

    (Faculty of Statistics, Dortmund University of Technology)

  • Andre Güttler

    (Universität Frankfurt, Finance Department)

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.

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Paper provided by Business and Social Statistics Department, Technische Universität Dortmund in its series Working Papers with number 2.

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Length: 26 pages
Date of creation:
Date of revision: Oct 2006
Publication status: Published in Empirical Economics, May 2008, pages 343-356
Handle: RePEc:dor:wpaper:2
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  1. Moon, Choon-Geol & Stotsky, Janet G, 1993. "Testing the Differences between the Determinants of Moody's and Standard & Poor's Ratings: An Application of Smooth Simulated Maximum Likelihood Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 51-69, Jan.-Marc.
  2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  3. Krämer, Walter, 2003. "Evaluating probability forecasts in terms of refinement and strictly proper scoring rules," Technical Reports 2003,24, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  4. Crouhy, Michel & Galai, Dan & Mark, Robert, 2001. "Prototype risk rating system," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 47-95, January.
  5. Krämer, Walter, 2002. "On the ordering of probability forecasts," Technical Reports 2002,50, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  6. Carey, Mark & Hrycay, Mark, 2001. "Parameterizing credit risk models with rating data," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 197-270, January.
  7. Robert L. Winkler, 1994. "Evaluating Probabilities: Asymmetric Scoring Rules," Management Science, INFORMS, vol. 40(11), pages 1395-1405, November.
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