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Sonderforschungsbereich 649: Ökonomisches Risiko, Humboldt-Universität Berlin >
SFB 649 Discussion Papers, HU Berlin >
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http://hdl.handle.net/10419/25207
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| Title: | | Estimating probabilities of default with support vector machines  |
| Authors: | | Härdle, Wolfgang Karl Moro, Rouslan A. Schäfer, Dorothea |
| Issue Date: | | 2007 |
| Series/Report no.: | | SFB 649 discussion paper 2007,035 |
| Abstract: | | This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on German Bundesbank data. In particular we discuss the selection of variables and give a comparison with more traditional approaches such as discriminant analysis and the logit regression. The results demonstrate that the SVM has clear advantages over these methods for all variables tested. |
| Subjects: | | Bankruptcy Company rating Default probability Support vector machines |
| JEL: | | C14 G33 C45 |
| Document Type: | | Working Paper |
| Appears in Collections: | | SFB 649 Discussion Papers, HU Berlin
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