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Systemic Risk Modeling with Lévy Copulas

Yuhao Liu (), Petar M. Djurić (), Young Shin Kim (), Svetlozar T. Rachev () and James Glimm ()
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Yuhao Liu: Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, USA
Petar M. Djurić: Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY 11794, USA
Young Shin Kim: College of Business, Stony Brook University, Stony Brook, NY 11794, USA
Svetlozar T. Rachev: Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409, USA
James Glimm: GlimmAnalyitcs, Port Jefferson, NY 11777, USA

JRFM, 2021, vol. 14, issue 6, 1-20

Abstract: We investigate a systemic risk measure known as CoVaR that represents the value-at-risk (VaR) of a financial system conditional on an institution being under distress. For characterizing and estimating CoVaR, we use the copula approach and introduce the normal tempered stable (NTS) copula based on the Lévy process. We also propose a novel backtesting method for CoVaR by a joint distribution correction. We test the proposed NTS model on the daily S&P 500 index and Dow Jones index with in-sample and out-of-sample tests. The results show that the NTS copula outperforms traditional copulas in the accuracy of both tail dependence and marginal processes modeling.

Keywords: CoVaR; NTS copula; Lévy process; backtesting (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2021
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