Choosing the Best Set of Bankruptcy Predictors

Discriminant analysis and logit analysis are traditionally used to predict company bankruptcies. More recently, neural networks have been shown to outperform these statistical methods for the problem. The selection of nancial indicators as independent variables for all these methods is a major problem. In this paper, we let a genetic algorithm operate on a set of variables. The goal is to nd the optimal set of nancial indicators for the bankruptcy prediction problem.