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Business failure prediction using rough sets: a comparison with multivariate analysis techniques

C. Zopounidis, M. Doumpos. Technical University of Crete

R. Slowinski, R. Susmaga. Poznan University of Technology

A.I. Dimitras. University of Crete


Several multivariate analysis techniques have been used in the past for the prediction of business failure. Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt firms, they suffer from some limitations, often due to the unrealistic assumption of statistical hypotheses or due to a confusing language of communication with the decision makers. The aim of this research is to overcome these limitations. In this pa-per the rough set approach, an alter-native method, is used to provide a set of rules able to discriminate between healthy and bankrupt firms in order to predict business failure. Financial characteristics of a large sample of 80 Greek firms are used to derive a set of rules and to evaluate its prediction ability. The results are very encouraging, compared with those of discriminant, logit and probit analyses, and prove the usefulness of the proposed method for business failure prediction.

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