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On Comparing the Accuracy of Default Predictions in the Rating Industry

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  • André Güttler
  • Walter Kraemer

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.

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Bibliographic Info

Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 2202.

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Date of creation: 2008
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Handle: RePEc:ces:ceswps:_2202

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Keywords: credit rating; probability forecasts; calibration;

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  1. 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.
  2. 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.
  3. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  4. Prof. Dr. Walter Krämer, . "On the ordering of probability forecasts," Working Papers 1, Business and Social Statistics Department, Technische Universität Dortmund, revised May 2003.
  5. Crouhy, Michel & Galai, Dan & Mark, Robert, 2001. "Prototype risk rating system," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 47-95, January.
  6. Robert L. Winkler, 1994. "Evaluating Probabilities: Asymmetric Scoring Rules," Management Science, INFORMS, vol. 40(11), pages 1395-1405, November.
  7. Carey, Mark & Hrycay, Mark, 2001. "Parameterizing credit risk models with rating data," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 197-270, January.
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Cited by:
  1. Darrell Duffie & Leandro Siata & Ke Wang, 2006. "Multi-Period Corporate Default Prediction With Stochastic Covariates," NBER Working Papers 11962, National Bureau of Economic Research, Inc.
  2. Simon Cornée, 2014. "Soft Information and Default Prediction in Cooperative and Social Banks," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 201402, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
  3. Kurt Hornik & Rainer Jankowitsch & Manuel Lingo & Stefan Pichler & Gerhard Winkler, 2010. "Determinants of heterogeneity in European credit ratings," Financial Markets and Portfolio Management, Springer, vol. 24(3), pages 271-287, September.
  4. Andre Güttler & Peter Raupach, 2010. "The Impact of Downward Rating Momentum," Journal of Financial Services Research, Springer, vol. 37(1), pages 1-23, February.
  5. Christophe Godlewski, 2004. "Are Bank Ratings Coherent with Bank Default Probabilities in Emerging Market Economies ?," Finance 0409023, EconWPA.
  6. 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.

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