Multivariate VaRs for Operational Risk Capital Computation: a Vine Structure Approach

Dominique Guegan () and Bertrand Hassani ()
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Dominique Guegan: Centre d'Economie de la Sorbonne - Paris School of Economics, https://cv.archives-ouvertes.fr/dominique-guegan
Bertrand Hassani: BPCE et Centre d'Economie de la Sorbonne, https://centredeconomiesorbonne.cnrs.fr

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: The Basel Advanced Measurement Approach requires financial institutions to compute capital requirements on internal data sets. In this paper we introduce a new methodology permitting capital requirements to take into account the embedded dependence structures of operational risks. The loss distributions are provided in a matrix of 56 cells. Constructing a vine architecture, which is a bivariate decomposition of a n-dimensional structure (n > 2), we use this approach to compute multivariate operational risk VaRs. We analyse the results and compare them with classical methodologies based on LDF modelings. Our method is simple to carry out, easy to interpret and complies with the new Basel Committee requirements

Keywords: Operational risks; vine copula; loss distribution function; nested structure; VaR (search for similar items in EconPapers)
JEL-codes: C1 C6 (search for similar items in EconPapers)
Date: 2011-04, Revised 2011-10
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Related works:
Working Paper: Multivariate VaRs for Operational Risk Capital Computation: a Vine Structure Approach (2012)
Working Paper: Multivariate VaRs for Operational Risk Capital Computation: a Vine Structure Approach (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:11017r

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