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Measuring systemic risk with a dynamic copula-based approach

Author

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  • Hyun Jin Jang
  • Xiao Pan
  • Sumin Park

Abstract

This study examines the extent of systemic risk embedded in the credit and equity markets using a conditional value-at-risk (CoVaR) measure. We implement a copula-based CoVaR approach with different perspectives of a dependence structure based on a generalized autoregressive score model. In parallel, we select the credit default swap spread and stock price data of five companies in the financial sector – American Express, BBVA, Goldman Sachs, Morgan Stanley, and Wells Fargo – from 2001 to 2013, and include data on the global financial crisis of 2007–2008. We then divide the data into three time periods: pre-crisis, during the crisis, and post-crisis. We conduct time-varying marginal modelling, and copula parameter estimation, and then compute CoVaR values with the best-fit copula model. Comparative empirical tests provide financial implications for systemic risk management.

Suggested Citation

  • Hyun Jin Jang & Xiao Pan & Sumin Park, 2021. "Measuring systemic risk with a dynamic copula-based approach," Applied Economics, Taylor & Francis Journals, vol. 53(50), pages 5843-5863, October.
    • Handle: RePEc:taf:applec:v:53:y:2021:i:50:p:5843-5863
    DOI: 10.1080/00036846.2021.1931007
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