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| Exploring the Sources of Default Clustering by Shahriar Azizpour of Stanford University, June 15, 2011 Abstract: We develop and implement a filtering approach to maximum likelihood estimation, goodness-of-fit testing and prediction for event timing models in which the arrival intensity is in fluenced by past events and stochastic covariates, some of which cannot be measured. Applying these tools to default events of US firms between 1970 and 2010, we find that the response of the intensity to defaults is economically and statistically significant, after controlling for the in fluence of the macroeconomic covariates that prior studies have identified as predictors of US defaults, and for the role of an unobservable frailty risk factor whose importance for US default timing was recently established. Both frailty and contagion, by which the default by one firm has a direct impact on the health of other firms, are significant sources of default clustering. JEL Classification: C11, C15, C41, E44, G33. Keywords: Correlated default, event feedback, contagion, frailty, self-exciting point process, intensity, point process filtering and smoothing, measure change, likelihood, goodness-of-fit, time change. Previously titled: Self-exciting Corporate Defaults: Contagion vs. frailty Books Referenced in this paper: (what is this?)
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