Private Firm Default Probabilities Via Statistical Learning Theory and Utility Maximization

TLDR: In this paper, the authors estimate real-world private firm default probabilities over a fixed time horizon, conditioned on a vector of explanatory variables, which include financial ratios, economic indicators, and market prices.

Abstract: We estimate real-world private firm default probabilities over a fixed time horizon,conditioned on a vector of explanatory variables, which include financial ratios, economic indicators, and market prices. To estimate our model, we apply a recently developed method from statistical learning theory. This method leads to a model that is particularly appropriate for financial market participants who would use the model to make financial decisions. We compare our model with various benchmark models, with respect to a number of performance measures. In all of these tests, our model outperformed the benchmark models. We also discuss possible reasons for this outperformance. A revised version of this paper appeared in the Journal of Credit Risk, Volume 2/Number 1, Spring 2006.