Dynamic Copula Methods in Finance

Abstract

Beginning with a review of the issues surrounding dependence and correlation in finance and the basic concepts of copulas as they have been applied to financial problems up until now, the book goes on to introduce the theory of convolution-based copulas, and the concept of C-convolution within the mainstream of Darsow-Nguyen and Olsen (DNO) application to Markov processes. The authors explain how the C-convolution approach can be exploited to address both spatial and temporal dependence and demonstrate how it can be applied to the problems of evaluating multivariate equity derivatives, analyzing the credit risk exposure of a portfolio, and aggregating Value-at-Risk measures across risk-factors and business units.

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