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Application of Vine Copulas to Credit Portfolio Risk Modeling

Marco Geidosch () and Matthias Fischer ()
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Marco Geidosch: UniCredit Bank AG, Munich, Germany
Matthias Fischer: Department of Statistics and Econometrics, University of Erlangen-Nürnberg, Germany

Journal of Risk and Financial Management, 2016, vol. 9, issue 2, 1-15

Abstract: In this paper, we demonstrate the superiority of vine copulas over conventional copulas when modeling the dependence structure of a credit portfolio. We show statistical and economic implications of replacing conventional copulas by vine copulas for a subportfolio of the Euro Stoxx 50 and the S&P 500 companies, respectively. Our study includes D-vines and R-vines where the bivariate building blocks are chosen from the Gaussian, the t and the Clayton family. Our findings are (i) the conventional Gauss copula is deficient in modeling the dependence structure of a credit portfolio and economic capital is seriously underestimated; (ii) D-vine structures offer a better statistical fit to the data than classical copulas, but underestimate economic capital compared to R-vines; (iii) when mixing different copula families in an R-vine structure, the best statistical fit to the data can be achieved which corresponds to the most reliable estimate for economic capital.

Keywords: pair-copula constructions; vine copulas; Archimedean and elliptical copulas; credit portfolio risk; economic capital; R-vine; D-vine (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2016
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