Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10419/19777
Title: Estimating probabilities of default with support vector machines
Keywords: C45
G33
C14
ddc:330
Bankruptcy
Company rating
Default probability
Support vector machines
Kreditwürdigkeit
Konkurs
Prognoseverfahren
Support Vector Machine
Theorie
Deutschland
Issue Date: 16-Oct-2013
Description: 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 Deutsche 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.
URI: http://koha.mediu.edu.my:8181/xmlui/handle/10419/19777
Other Identifiers: http://hdl.handle.net/10419/19777
ppn:556818253
RePEc:zbw:bubdp2:6930
Appears in Collections:EconStor

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