Measuring the coupled risks: A copula-based CVaR model

Authors:
Xubiao He;Pu Gong
Affiliations:
School of Management, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, PR China;School of Management, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, PR China
Venue:
Journal of Computational and Applied Mathematics
Year:
2009

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Abstract

Integrated risk management for financial institutions requires an approach for aggregating risk types (such as market and credit) whose distributional shapes vary considerably. The financial institutions often ignore risks' coupling influence so as to underestimate the financial risks. We constructed a copula-based Conditional Value-at-Risk (CVaR) model for market and credit risks. This technique allows us to incorporate realistic marginal distributions that capture essential empirical features of these risks, such as skewness and fat-tails while allowing for a rich dependence structure. Finally, the numerical simulation method is used to implement the model. Our results indicate that the coupled risks for the listed company's stock maybe are undervalued if credit risk is ignored, especially for the listed company with bad credit quality.