Note on new prospects on vines

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.

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Year of publication:	2010
Authors:	Maugis, Pierre-André ; Guegan, Dominique
Institutions:	HAL
Subject:	Vines \| multivariate copulas \| model selection

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Extent:	application/pdf
Series:	Post-Print.
Type of publication:	Book / Working Paper
Notes:	View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00471362 Published, Insurance Markets and Companies : Analyses and Actuarial Computations, 2010, 1, 1, 15-22
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010603636