A0381
Title: Financial distress prediction using machine learning: When Altman meets Merton in a transition economy
Authors: Minh Nguyen - University of Hawaii at Manoa (United States) [presenting]
Abstract: The purpose is to explore financial distress prediction for public firms in Vietnam as a transition economy by combining variables from the Altman and Merton model. In order to do that, we employ four machine learning methods, including linear discriminant analysis, logistic regression, support vector machines, and neural networks. Our results show that in most cases, the models combining the Altman's and Merton's variables outperform those that only use either of these lists of variables.
