José Manuel Pereira 1, Miguel Á. Crespo Domínguez 2, José L. Sáez Ocejo 3
jpereira@ipca.pt; macrespo@uvigo.es; jocejo@uvigo.es
Resumo. A previsão do fracasso empresarial é um tema que interessa cada vez mais aos diversos agentes económicos, em particular aos investidores, credores, entidades financeiras, mas também aos governos. Desde o trabalho pioneiro de Beaver (1966) diferentes métodos têm sido utilizados: análise discriminante, logit, probit, redes neuronais, indução de regras e árvores de decisão, algoritmos genéticos, conjuntos aproximados, entre outros modelos. O nosso objectivo é efectuar uma comparação dos métodos que têm sido mais utilizados, analisando as principais vantagens e inconvenientes bem como a sua aplicabilidade para os potenciais utilizadores. Concluímos que a capacidade predictiva dos modelos é em geral similar e que a maioria dos investigadores utilizou a análise discriminante ou o logit. Em geral, e para um utilizador comum, os modelos baseados em redes neuronais revelam-se difíceis de aplicar.
Palavras-chave: Fracasso Empresarial; Análise Discriminante; Logit; Probit; Redes Neuronais; Árvores de Decisão.
Abstract. Prediction of corporate bankruptcy is a phenomenon of increasing interest to investors, creditors, borrowing firms, and governments alike. Since the seminal work of Beaver (1966) different techniques have been used: discriminant analysis, logit, probit, neural networks, decision trees, genetic algorithms, rough sets, and some other techniques. Our intent is to provide a comparison of the most popular methods, analysing their own strengths and weaknesses and their applicability to potential users. We find that predictive accuracies of different models seem to be generally comparable and the use of discriminant analysis and logit models dominates the research. In general the neural networks models are the most difficult for the users.
Keywords: Bankruptcy; Discriminant Analysis; Logit; Probit; Neural Networks; Decision Trees.
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]]> 1 Escola Superior de Gestão do Instituto Politécnico do Cávado e Ave (IPCA)
2 Universidade de Vigo, Espanha
3 Universidade de Vigo, Espanha
(Recebido em 30 de Março de 2007; Aceite em 8 de Maio de 2007)
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