Estimation du risque de défaut par une modélisation stochastique du bilan : application à des firmes industrielles françaises
Résumé
This paper proposes to estimate corporate default risk and to predict bankruptcy via an Asset Liability Management (ALM) method of risk estimation, which is an alternative to multivariate models such as multiple discriminant analysis or neural networks. The method is based on corporate bond valuation models. Whereas ALM is almost exclusively used by banks and insurance companies, we assess probabilities of default for French manufacturing firms. Following Janssen [1992], we suppose that the dynamics for the total assets and the total liabilities can be described by geometric Brownian motions. The probability of insolvency -- i.e. the probability that net worth is negative -- is then estimated and analysed as the probability of default. Firms are partitioned into two groups, based on the computed probabilities and a threshold level. The rate of correct classification is assessed from bootstrap samples and compared to other business failure prediction models. The assessed probabilities provide a good indicator of corporate bankruptcy risk for one to three years prior to failure.