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Extreme dependence for multivariate data

Author

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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 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.

Suggested Citation

  • Damien Bosc & Alfred Galichon, 2014. "Extreme dependence for multivariate data," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1187-1199, July.
    • Handle: RePEc:taf:quantf:v:14:y:2014:i:7:p:1187-1199
    DOI: 10.1080/14697688.2014.886777
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