New evolutionary bankruptcy forecasting model based on genetic algorithms and neural networks

One of the problem still gaining a great attention in finance is the bankruptcy forecasts. The problem of efficient bankruptcy prognosis is of great interest both to scientists and practitioners. Numerous models have been developed to forecast bankruptcy prediction from statistical models to artificial intelligence techniques. We propose, in this study, a new hybrid model (EBM: evolutionary bankruptcy model) based on genetic algorithms and artificial neural networks. Our evolutionary model is able of: selecting the best set of predictive variables, then, searching for the best neural network classifier and improving classification and generalization accuracies. Carried out experiments have shown a very promising results of EBM for bankruptcy prediction in terms of predictive accuracy and adaptability.