A Comparison of Stochastic Default Rate Models
by Christopher C. Finger of the RiskMetrics Group
Abstract: For single horizon models of defaults in a portfolio, the effect of model and distribution choice on the model results is well understood. Collateralized Debt Obligations in particular have sparked interest in default models over multiple horizons. For these, however, there has been little research, and there is little understanding of the impact of various model assumptions. In this article, we investigate four approaches to multiple horizon modeling of defaults in a portfolio. We calibrate the four models to the same set of input data (average defaults and a single period correlation parameter), and examine the resulting default distributions. The differences we observe can be attributed to the model structures, and to some extent, to the choice of distributions that drive the models. Our results show a significant disparity. In the single period case, studies have concluded that when calibrated to the same first and second order information, the various models do not produce vastly different conclusions. Here, the issue of model choice is much more important, and any analysis of structures over multiple horizons should bear this in mind.
Keywords: Credit risk, default rate, collateralized debt obligations.
Published in: RiskMetrics Journal, Vol. 1, No. 2, (November 2000), pp. 49-73.