Rating Companies with Support Vector Machines

Wolfgang Härdle, Rouslan A. Moro and Dorothea Schäfer

No 416, Discussion Papers of DIW Berlin from DIW Berlin, German Institute for Economic Research

Abstract: The goal of this work is to introduce one of the most successful among recently developed statistical techniques - the support vector machine (SVM) - to the field of corporate bankruptcy analysis. The main emphasis is done on implementing SVMs for analysing predictors in the form of financial ratios. A method is proposed of adapting SVMs to default probability estimation. A survey of practically and commercially applied methods is given. This work proves that support vector machines are capable of extracting useful information from financial data although extensive data sets are required in order to fully utilise their classification power.

Keywords: Support vector machines; Company rating; Default probability estimation (search for similar items in EconPapers)
JEL-codes: C14 C45 G33 (search for similar items in EconPapers)
Pages: 30 p.
Date: 2004
New Economics Papers: this item is included in nep-cmp, nep-ent and nep-fin
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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