Time-Varying Systemic Risk: Evidence from a Dynamic Copula Model of CDS Spreads
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This paper proposes a new class of copula-based dynamic models for high dimension conditional distributions, facilitating the estimation of a wide variety of measures of systemic risk. Our proposed models draw on successful ideas from the literature on modeling high dimension covariance matrices and on recent work on models for general time-varying distributions. Our use of copula-based models enable the estimation of the joint model in stages, greatly reducing the computational burden. We use the proposed new models to study a collection of daily credit default swap (CDS) spreads on 100 U.S. firms over the period 2006 to 2012. We find that while the probability of distress for individual firms has greatly reduced since the financial crisis of 2008-09, the joint probability of distress (a measure of systemic risk) is substantially higher now than in the pre-crisis period.
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Zelter Family Professor
Professor Patton’s research areas include econometrics, financial economics and forecasting. His work focuses on improved models for risk and dependence between financial assets, methods for forecast evaluation and comparison, and empirical asset pricing. Patton's recent publications include "Simulated Method of Moments Estimation for Copula-Based Multivariate Models" (2013, Journal of the American Statistical Association, joint with Dong Hwan Oh), "On the High Frequency Dynamics of Hedge Fund R