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Improvements in rating models for the German corporate sector

Till Förstemann

No 2011,11, Discussion Paper Series 2: Banking and Financial Studies from Deutsche Bundesbank

Abstract: Group-specific estimations can significantly improve the predictive power of accountingbased rating models. This is shown using a binary logistic regression model applied to the Deutsche Bundesbank's USTAN dataset, which contains 300,000 financial statements provided by German companies for the years 1994 to 2002, i. e. throughout a complete business-cycle. The robustness and the representability of this result is verified through out-of-sample tests and through comparisons with a benchmark model which applies the variables of Moody's RiskCalcTM for Germany.

Keywords: Credit Risk; Credit Rating; Probability of Default; Logistic Regression (search for similar items in EconPapers)
JEL-codes: C52 G21 G33 (search for similar items in EconPapers)
Date: 2011
New Economics Papers: this item is included in nep-rmg
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