On comparing the accuracy of default predictions in the rating industry
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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|Date of creation:|
|Date of revision:||Oct 2006|
|Publication status:||Published in Empirical Economics, May 2008, pages 343-356|
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- 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.
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- Crouhy, Michel & Galai, Dan & Mark, Robert, 2001. "Prototype risk rating system," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 47-95, January.
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- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Krämer, Walter, 2003.
"Evaluating probability forecasts in terms of refinement and strictly proper scoring rules,"
2003,24, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Walter Krämer, 2006. "Evaluating probability forecasts in terms of refinement and strictly proper scoring rules," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(3), pages 223-226.
- Carey, Mark & Hrycay, Mark, 2001. "Parameterizing credit risk models with rating data," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 197-270, January.
- Krämer, Walter, 2002.
"On the ordering of probability forecasts,"
2002,50, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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