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

Dong Hwan Oh and Andrew Patton

Journal of Business & Economic Statistics, 2018, vol. 36, issue 2, 181-195

Abstract: This article proposes a new class of copula-based dynamic models for high-dimensional 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-dimensional covariance matrices and on recent work on models for general time-varying distributions. Our use of copula-based models enables 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 2008–2009, the joint probability of distress (a measure of systemic risk) is substantially higher now than in the precrisis period. Supplementary materials for this article are available online.

Date: 2018
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Working Paper: Time-Varying Systemic Risk: Evidence from a Dynamic Copula Model of CDS Spreads (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:36:y:2018:i:2:p:181-195

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DOI: 10.1080/07350015.2016.1177535

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