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Time-Varying Systemic Risk: Evidence from a Dynamic Copula Model of CDS Spreads

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  • Dong Hwan Oh
  • Andrew J. Patton

Abstract

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.

Suggested Citation

  • Dong Hwan Oh & Andrew J. Patton, 2013. "Time-Varying Systemic Risk: Evidence from a Dynamic Copula Model of CDS Spreads," Working Papers 13-30, Duke University, Department of Economics.
    • Handle: RePEc:duk:dukeec:13-30
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    Keywords

    correlation; tail risk; financial crises; DCC;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises

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