Measurement of aggregate risk with copulas

Markus Junker and Angelika May

Econometrics Journal, 2005, vol. 8, issue 3, 428-454

Abstract: When aggregating financial risk on a portfolio level, the specification of the dependence structure between the risk factors plays an important role. Promising parametric models are often based on a so-called copula approach. Case studies of market crashes suggest the application of concepts allowing for extremal dependence. We present a transformed copula as a new model that both fits the data and allows for exact prediction in the tails. It turns out that the new model improves benchmark models like the t- or Clayton copula with respect to risk measures like VaR or Expected Shortfall. By performing different goodness-of-fit tests, the quality of the estimation is examined. Copyright 2005 Royal Economic Society

Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:8:y:2005:i:3:p:428-454

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