On Multivariate Extensions of Value-at-Risk
Abstract
In this paper, we introduce two alternative extensions of the classical univariate Value-at-Risk (VaR) in a multivariate setting. The two proposed multivariate VaR are vector-valued measures with the same dimension as the underlying risk portfolio. The lower-orthant VaR is constructed from level sets of multivariate distribution functions whereas the upper-orthant VaR is constructed from level sets of multivariate survival functions. Several properties have been derived. In particular, we show that these risk measures both satisfy the positive homogeneity and the translation invariance property. Comparison between univariate risk measures and components of multivariate VaR are provided. We also analyze how these measures are impacted by a change in marginal distributions, by a change in dependence structure and by a change in risk level. Illustrations are given in the class of Archimedean copulas.Download Info
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Paper provided by arXiv.org in its series Papers with number 1111.1349.Length:
Date of creation: Nov 2011
Date of revision: Apr 2013
Handle: RePEc:arx:papers:1111.1349
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Web page: http://arxiv.org/
Related research
Keywords:This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-11-14 (All new papers)
References
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Elena Di Bernardino & Didier Rullière, 2013. "Distortions of multivariate distribution functions and associated level curves: applications in multivariate risk theory," Working Papers hal-00750873, HAL.
- Elena Di Bernardino & Didier Rullière, 2012. "Distortions of multivariate risk measures: a level-sets based approach," Working Papers hal-00756387, HAL.
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