Default Clustering in Large Portfolios: Typical events

by Kay Giesecke of Stanford University,
Konstantinos Spiliopoulos of Brown University, and
Richard B. Sowers of University of Illinois at Urbana-Champaign

March 4, 2012

Abstract: We develop a dynamic point process model of correlated default timing in a portfolio of firms, and analyze typical 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.

AMS Classification: 91G40, 60F05, 60F10.

Keywords: credit derivatives, collateralized debt obligation, credit swap.

Previously titled: Default Clustering in Large Portfolios: Typical and atypical events

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