Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis

Guoqiang Zhang, Michael Y. Hu, B Eddy Patuwo, Daniel C. Indro
1999 European Journal of Operational Research  
In this paper, we present a general framework for understanding the role of arti®cial neural networks (ANNs) in bankruptcy prediction. We give a comprehensive review of neural network applications in this area and illustrate the link between neural networks and traditional Bayesian classi®cation theory. The method of cross-validation is used to examine the between-sample variation of neural networks for bankruptcy prediction. Based on a matched sample of 220 ®rms, our ®ndings indicate that
more » ... l networks are signi®cantly better than logistic regression models in prediction as well as classi®cation rate estimation. In addition, neural networks are robust to sampling variations in overall classi-®cation performance. Ó
doi:10.1016/s0377-2217(98)00051-4 fatcat:irbshy4t4be7dnia2xndlnxkde