Extreme dependence for multivariate data

Damien Bosc, Alfred Galichon

    Research output: Contribution to journalArticlepeer-review


    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.

    Original languageEnglish (US)
    Pages (from-to)1187-1199
    Number of pages13
    JournalQuantitative Finance
    Issue number7
    StatePublished - Jul 2014


    • Covariance set
    • Extreme dependence
    • Multivariate dependence

    ASJC Scopus subject areas

    • General Economics, Econometrics and Finance
    • Finance


    Dive into the research topics of 'Extreme dependence for multivariate data'. Together they form a unique fingerprint.

    Cite this