An extension of Davis and Lo's contagion model

The present paper provides a multi-period contagion model in the credit risk field. Our model is an extension of Davis and Lo's infectious default model. We consider an economy of n firms that may default directly or may be infected by other defaulting firms (a domino effect also being possible). Spontaneous defaults without external influence and infection are described by not necessarily independent Bernoulli-type random variables. Moreover, several sources of contamination could be required to infect another firm. In this paper we compute the probability distribution function of the total number of defaults in a dependency context. We also give a simple recursive algorithm to compute this distribution in an exchangeability context. Numerical applications illustrate the impact of exchangeability among direct defaults and among contaminations, on different indicators calculated from the law of the total number of defaults. We then calibrate the model on iTraxx data before and during the crisis. The dynamic feature together with the contagion effect have a significant impact on the model performance, especially during the recent distressed period.