The risk of betting on risk: Conditional variance and correlation of bank credit default swaps |
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Authors: | Xin Huang |
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Affiliation: | Risk Analysis Section, Federal Reserve Board, Washington, District of Columbia |
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Abstract: | Credit default swaps (CDS) have been used to speculate on the default risk of the reference entity. The risk of CDS can be measured by their second moments. We apply a Glosten, Jagannathan, and Runkle (GJR)-t model for the conditional variance and a Dynamic Conditional Correlation (DCC)-t model for the conditional correlation. Based on the CDS of six large US banks from 2002 to 2018, we find that CDS conditional variance is asymmetric and leptokurtic. A positive innovation actually increases CDS conditional variance more than a negative innovation does. CDS conditional correlations have stayed elevated since the financial crisis, in contrast to the decreasing stock conditional correlations. |
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Keywords: | conditional correlation conditional variance credit default swaps |
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