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Combining risk measures to overcome their limitations - spectrum representation of the sub-additivity issue, distortion requirement and added-value of the Spatial VaR solution: An application to Regulatory Requirement for Financial Institutions

Author

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  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Bertrand K. Hassani

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

To measure the major risks experienced by financial institutions, for instance Market, Credit and Operational, regarding the risk measures, the distributions used to model them and the level of confidence, the regulation either offers a limited choice or demands the implementation of a particular approach. In this paper, we highlight and illustrate the paradoxes and issues observed when implementing an approach over another, the inconsistencies between the methodologies suggested and the problems related to their interpretation. Starting from the notion of coherence, we discuss their properties, we propose alternative solutions, new risk measures like spectrum and spatial approaches, and we provide practitioners and supervisor with some recommendations to assess, manage and control risks in a financial institution.

Suggested Citation

  • Dominique Guegan & Bertrand K. Hassani, 2016. "Combining risk measures to overcome their limitations - spectrum representation of the sub-additivity issue, distortion requirement and added-value of the Spatial VaR solution: An application to Regul," Post-Print halshs-01391103, HAL.
    • Handle: RePEc:hal:journl:halshs-01391103
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01391103
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    References listed on IDEAS

    as
    1. Dominique Guegan & Pierre-André Maugis, 2008. "New prospects on vines," Documents de travail du Centre d'Economie de la Sorbonne b08095, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Mar 2010.
    2. Dominique Guegan & Bertrand Hassani & Cédric Naud, 2011. "An efficient threshold choice for operational risk capital computation," Post-Print halshs-00790217, HAL.
    3. Dominique Guegan & Bertrand Hassani, 2015. "Stress Testing Engineering: The Real Risk Measurement?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01310469, HAL.
    4. Dominique Guegan & Bertrand Hassani, 2013. "Multivariate VaRs for operational risk capital computation: a vine structure approach," Post-Print halshs-00645778, HAL.
    5. Dominique Guegan & Bertrand Hassani, 2015. "Distorsion Risk Measure or the Transformation of Unimodal Distributions into Multimodal Functions," Post-Print hal-01310467, HAL.
    6. Dominique Guegan & Bertrand Hassani, 2013. "Multivariate VaRs for operational risk capital computation: a vine structure approach," PSE-Ecole d'économie de Paris (Postprint) halshs-00645778, HAL.
    7. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Documents de travail du Centre d'Economie de la Sorbonne 10040, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    8. J. Dhaene & R. J. A. Laeven & S. Vanduffel & G. Darkiewicz & M. J. Goovaerts, 2008. "Can a Coherent Risk Measure Be Too Subadditive?," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(2), pages 365-386, June.
    9. Dominique Guegan & Bertrand Hassani, 2015. "Stress Testing Engineering: The Real Risk Measurement?," Post-Print hal-01310469, HAL.
    10. Dominique Guegan & Bertrand Hassani, 2015. "Distorsion Risk Measure or the Transformation of Unimodal Distributions into Multimodal Functions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01310467, HAL.
    11. Daníelsson, Jón & Jorgensen, Bjørn N. & Samorodnitsky, Gennady & Sarma, Mandira & de Vries, Casper G., 2013. "Fat tails, VaR and subadditivity," Journal of Econometrics, Elsevier, vol. 172(2), pages 283-291.
    Full references (including those not matched with items on IDEAS)

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