Abstract

https://ssrn.com/abstract=1731568
 
 

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Extreme Dependence for Multivariate Data


Damien Bosc


Ecole Polytechnique, Paris - Department of Economic Sciences

Alfred Galichon


NYU, Department of Economics and Courant Institute

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.

Number of Pages in PDF File: 23

Keywords: multivariate dependence, extreme dependence, multivariate stress tests

JEL Classification: C58, C02


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Date posted: December 27, 2010 ; Last revised: April 8, 2013

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

Contact Information

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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