Stochastic modelling and prediction of contractor default risk

Abstract

The purpose of this paper is to describe a systematic framework of stochastic modelling and prediction of financial default risk of construction contractors. Net-worth-to-asset ratio is identified as an index for default process modelling. The default condition is defined as when the ratio becomes negative the first time. A mean-reverting dynamic model for the contractor default process is found by statistical analysis and is justified by using the theory of optimal capital structure. The stochastic modelling of default uses the time to default as the fundamental random variable. A discrete time trinomial Markov chain model is developed to assess default risk in terms of a cumulative default probability function, a default probability function, and the mean and variance of time to default. Practical examples are given to illustrate the stochastic methods. A default discriminant study on a group of contractors and publicly traded companies validates the methods, and indicates a high predictability of events of default and declines of credit rating.