Redefinition of the KMV model's optimal default point based on genetic algorithms - Evidence from Taiwan
In this paper, we propose a new method based on genetic algorithms to solve the optimal default point of the KMV model. In our empirical study, we compare the GA-KMV model with the QR-KMV and KMV models. The results indicate that the percentage of correctness of the GA-KMV model is higher than those for the other two models. This is to say, the GA-KMV model has a better goodness of fit. We also obtain the optimal default point for a Taiwan listed company. This can help us to predict the default point and improve the bank's risk management performance. (C) 2011 Elsevier Ltd. All rights reserved.
kmv genetic algorithms credit risk default probability quantile regression