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Measuring Economic Capital: Value-at-Risk, Expected Shortfall and Copula Approach


Jeungbo Shim


Illinois Wesleyan University

Seung-Hwan Lee


Illinois Wesleyan University

Richard D. MacMinn


Illinois State University

May 12, 2011


Abstract:     
It is important to incorporate diverse heavy-tailed dependency between risks in estimating economic capital. Copulas can be a useful technique to capture dependence structure where extreme events occur simultaneously. Using the sample of U.S. property liability insurance industry, we examine the impact of different dependence structure between market risk and underwriting risk of insurance portfolio on the economic capital measured by Value-at-Risk (VaR) and Expected Shortfall (ES). We identify the type of copula that best fits the given application data and perform a goodness of fit test to assess the adequacy of the copula model selected. The results suggest that the grouped t copula is better performed than the standard t copula to describe the dependence structure in an insurance setting where different type of risk factors coexists. The result also shows the incremental diversification benefit in the joint modeling of underwriting risk and market risk compared to the modeling of market risk only considered, indicating that both risks diversify against one another to some degree.

Number of Pages in PDF File: 43

Keywords: Economic Capital, Value-at-Risk, Grouped t Copula

JEL Classification: C00, C13

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Date posted: May 13, 2011  

Suggested Citation

Shim, Jeungbo, Lee, Seung-Hwan and MacMinn, Richard D., Measuring Economic Capital: Value-at-Risk, Expected Shortfall and Copula Approach (May 12, 2011). Available at SSRN: http://ssrn.com/abstract=1840124 or http://dx.doi.org/10.2139/ssrn.1840124

Contact Information

Jeungbo Shim (Contact Author)
Illinois Wesleyan University ( email )
P.O. Box 2900
Bloomington, IL 61702-2900
United States
Seung-Hwan Lee
Illinois Wesleyan University ( email )
P.O. Box 2900
Bloomington, IL 61702-2900
United States
Richard D. MacMinn
Illinois State University ( email )
Normal, IL 61790
United States
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