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Extreme dependence for multivariate data

Damien Bosc and Alfred Galichon

Quantitative Finance, 2014, vol. 14, issue 7, 1187-1199

Abstract: This article proposes a generalized notion of extreme multivariate dependence between two random vectors which relies on the extremality of the cross-covariance matrix between these two vectors. Using a partial ordering on the cross-covariance matrices, we also generalize the notion of positive upper dependence. We then propose a means to quantify the strength of the dependence between two given multivariate series and to increase this strength while preserving the marginal distributions. This allows for the design of stress-tests of the dependence between two sets of financial variables that can be useful in portfolio management or derivatives pricing.

Date: 2014
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Working Paper: Extreme dependence for multivariate data (2010) Downloads
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