A Comparison and Integration of Classification Techniques for the Prediction of Small UK Firms Failure

Journal of Financial Decision Making, Vol. 1, No. 1, pp. 55-69, 2005

Posted: 19 Apr 2006

See all articles by Chrysovalantis Gaganis

Chrysovalantis Gaganis

University of Crete - Faculty of Social Sciences - Department of Economics

Fotios Pasiouras

GSCM-Montpellier Business School

Alexander Tzanetoulakos

Financial Engineering Laboratory of Technical University of Crete

Abstract

In this paper we compare the efficiency of five classification techniques namely, discriminant analysis, logit analysis, Utilites Additives Discriminantes (UTADIS), Multi-Group Hierarchical DIScrimination (MHDIS), and Support Vector Machines (SVMs) in predicting small firms failure. We then investigate the efficiency of integrated models developed through a majority voting rule and stacked generalization. The sample consists of 984 small UK firms, half of which failed between 1997 and 2004. The models are evaluated both in terms of their prediction accuracy, as well as with ROC analysis.

Keywords: Bankruptcy, failure, integration, classification

JEL Classification: G33, C63

Suggested Citation

Gaganis, Chrysovalantis and Pasiouras, Fotios and Tzanetoulakos, Alexander, A Comparison and Integration of Classification Techniques for the Prediction of Small UK Firms Failure. Journal of Financial Decision Making, Vol. 1, No. 1, pp. 55-69, 2005, Available at SSRN: https://ssrn.com/abstract=897641

Chrysovalantis Gaganis

University of Crete - Faculty of Social Sciences - Department of Economics ( email )

University Campus
Rethymno, Crete, 74100
Greece

HOME PAGE: http://economics.soc.uoc.gr/en/staff/4551/17

Fotios Pasiouras (Contact Author)

GSCM-Montpellier Business School ( email )

2300, Avenue des Moulins
Montpellier, 34185
France

Alexander Tzanetoulakos

Financial Engineering Laboratory of Technical University of Crete ( email )

University Campus
Chania
Crete, 73100
Greece

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