Extreme Dependence for Multivariate Data

23 Pages Posted: 27 Dec 2010 Last revised: 8 Apr 2013

Damien Bosc

Ecole Polytechnique, Paris - Department of Economic Sciences

Alfred Galichon

NYU, Department of Economics and Courant Institute

Date Written: April 6, 2013

Abstract

We present 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 quantify the strength of dependence between two given multivariate series using an entropic distance to extremally dependent distributions. We apply this method to build indices of exposure to a financial environment, and to do stress-tests on the correlation between two sets of financial variables.

Keywords: multivariate dependence, extreme dependence, multivariate stress tests

JEL Classification: C58, C02

Suggested Citation

Bosc, Damien and Galichon, Alfred, Extreme Dependence for Multivariate Data (April 6, 2013). Available at SSRN: https://ssrn.com/abstract=1731568 or http://dx.doi.org/10.2139/ssrn.1731568

Damien Bosc (Contact Author)

Ecole Polytechnique, Paris - Department of Economic Sciences ( email )

Ecole Polytechnique
Department of Economics
Paris, 75005
France

Alfred Galichon

NYU, Department of Economics and Courant Institute ( email )

269 Mercer Street, 7th Floor
New York, NY 10011
United States

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