Abstract
Although copula modeling has been applied in a growing number of financial applications, high-dimensional copula modeling is still in its early stages. Vine copula modeling not only has the advantage of extending to higher dimensions easily, but also provides a more flexible measure to capture an asymmetric dependence among assets. CoVaR, the Value-at-Risk of institutions conditional on other institutions being in distress, is introduced by Adrian and Brunnermeier (2011). ∆CoVaR is the risk contribution that the institution adds to the entire system. Combined with the modified CoVaR methodology and estimation of the dependence structures through vine copula modeling, we empirically investigate systemic risk in 10 S&P 500 sector indices in the U.S. stock market by estimating daily Copula ∆CoVaR and Copula ∆CoES from January 1, 1995 to July 31, 2013. Our model (Copula CoVaR) reveals a real-time and efficient tool that can be used to analyze systemic risk. Furthermore, this approach could offer a systemic risk index for those countries which do not have an instrument like VIX, and can be tailored to any underlying sector, country or financial market easily.
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