Multiperiod Corporate Default Prediction - A Forward Intensity Approach

Abstract

A forward intensity model for the prediction of corporate defaults over different future periods is proposed. Maximum pseudo-likelihood analysis is then conducted on a large sample of the US industrial and financial firms spanning the period 1991-2011 on a monthly basis. Several commonly used factors and firm-specific attributes are shown to be useful for prediction at both short and long horizons. Our implementation also factors in momentum in some variables and documents their importance in default prediction. The prediction is very accurate for shorter horizons. The accuracy deteriorates somewhat when the horizon is increased to two or three years, but its performance still remains reasonable. The forward intensity model is also amenable to aggregation, which allows for an analysis of default behavior at the portfolio and/or economy level.

Keywords: default, bankruptcy, forward intensity, maximum pseudo-likelihood, forward default probability, cumulative default probability, accuracy ratio

JEL Classification: C41, C53, G33