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Title:Estimating probabilities of default with support vector machines PDF Logo
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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