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Deutsche Bundesbank, Forschungszentrum, Frankfurt am Main >
Discussion Paper Series 2: Banking and Financial Studies, Deutsche Bundesbank >
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http://hdl.handle.net/10419/50001
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| Title: | | Improvements in rating models for the German corporate sector  |
| Authors: | | Förstemann, Till |
| Issue Date: | | 2011 |
| Series/Report no.: | | Discussion Paper Series 2: Banking and Financial Studies 2011,11 |
| 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. |
| Subjects: | | Credit Risk Credit Rating Probability of Default Logistic Regression |
| JEL: | | G21 G33 C52 |
| ISBN: | | 978-3-86558-745-9 |
| Document Type: | | Working Paper |
| Appears in Collections: | | Discussion Paper Series 2: Banking and Financial Studies, Deutsche Bundesbank
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