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Extreme dependence for multivariate data

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  • Damien Bosc
  • Alfred Galichon

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 proposes 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.

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  • Damien Bosc & Alfred Galichon, 2021. "Extreme dependence for multivariate data," Papers 2102.04461, arXiv.org.
    • Handle: RePEc:arx:papers:2102.04461
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    File URL: http://arxiv.org/pdf/2102.04461
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