Note on new prospects on vines
Pierre-André Maugis and
Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL
In this paper, we present a new methodology based on vine copulas to estimate multivariate distributions in high dimensions, taking advantage of the diversity of vine copulas. Considering the huge number of vine copulas in dimension n, we introduce an efficient selection algorithm to build and select vine copulas with respect to any test T. Our methodology offers a great flexibility to practitioners to compute VaR associated to a portfolio in high dimension.
Keywords: Vines; multivariate copulas; model selection (search for similar items in EconPapers)
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Published in Insurance Markets and Companies : Analyses and Actuarial Computations, 2010, 1 (1), pp.15-22
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Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:halshs-00471362
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