Improvements in rating models for the German corporate sector
AbstractGroup-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. --
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Bibliographic InfoPaper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 2: Banking and Financial Studies with number 2011,11.
Date of creation: 2011
Date of revision:
Credit Risk; Credit Rating; Probability of Default; Logistic Regression;
Find related papers by JEL classification:
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- G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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