Default Clustering in Large Portfolios: Typical Events

Abstract

We develop a dynamic point process model of correlated default timing in a portfolio of firms, and analyze default profiles in the limit as the size of the pool grows. In our model, a firm defaults at a stochastic intensity that is influenced by an idiosyncratic risk process, a systematic risk process common to all firms, and past defaults. We prove a law of large numbers for the default rate in the pool, which describes the typical behavior of defaults.