Estimating Probabilities of Default with Support Vector Machines

44 Pages Posted: 8 Jun 2016

See all articles by Wolfgang K. Härdle

Wolfgang K. Härdle

Humboldt University of Berlin - Institute for Statistics and Econometrics; Xiamen University - Wang Yanan Institute for Studies in Economics (WISE); Charles University; Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Rouslan Moro

German Institute for Economic Research (DIW Berlin)

Dorothea Schaefer

German Institute for Economic Research (DIW Berlin); JIBS

Date Written: 2007

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 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.

Keywords: Bankruptcy, Company rating, Default probability, Support vector machines

JEL Classification: C45, G33, C14

Suggested Citation

Härdle, Wolfgang K. and Moro, Rouslan and Schaefer, Dorothea, Estimating Probabilities of Default with Support Vector Machines (2007). Bundesbank Series 2 Discussion Paper No. 2007,18, Available at SSRN: https://ssrn.com/abstract=2794004

Wolfgang K. Härdle (Contact Author)

Humboldt University of Berlin - Institute for Statistics and Econometrics ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 10246
China

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Unter den Linden 6
Berlin, D-10099
Germany

Rouslan Moro

German Institute for Economic Research (DIW Berlin)

Mohrenstraße 58
Berlin, 10117
Germany

Dorothea Schaefer

German Institute for Economic Research (DIW Berlin) ( email )

Mohrenstraße 58
Berlin, 10117
Germany
+49 30 8978 9162 (Phone)
+49 30 8978 9104 (Fax)

JIBS ( email )

Jönköping, 55111
Sweden

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