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Extreme dependence for multivariate data

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. [Résumé éditeur]
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Damien Bosc, Alfred Galichon. Extreme dependence for multivariate data. Quantitative Finance, Taylor & Francis (Routledge), 2014, 14 (7), pp.1187 - 1199. ⟨10.1080/14697688.2014.886777⟩. ⟨hal-03470461⟩



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