The purpose of this work is to introduce one of the most promising among recentlydeveloped statistical techniques – the support vector machine (SVM) –to corporate bankruptcy analysis. An SVM is implemented for analysing suchpredictors as financial ratios. A method of adapting it to default...

Graphical data representation is an important tool for model selection in bankruptcy analysis since the problem is highly non-linear and its numerical representation is much less transparent. In classical rating models a convenient representation of ratings in a closed form is possible reducing...

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...

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...

Die Rekordzahlen an Unternehmensinsolvenzen, die schlechte Ertragslage der deutschen Kreditinstitute in den vergangenen Jahren und der von Basel II ausgehende Druck zur Verwendung von realitätsnahen Ausfallwahrscheinlichkeiten haben es überdeutlich gemacht: Der Bedarf an leistungsfähigen...

SFB 649 Discussion Paper 2007-035 Estimating Probabilities of Default With Support Vector Machines Wolfgang Härdle* Rouslan Moro** Dorothea Schäfer*** * Humboldt-Universität zu Berlin, Germany ** Humboldt-Universität zu Berlin & DIW Berlin, Germany *** DIW...

The purpose of this work is to introduce one of the most promising among recently developed statistical techniques – the support vector machine (SVM) – to corporate bankruptcy analysis. An SVM is implemented for analysing such predictors as financial ratios. A method of adapting it to...