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Operational risk : A Basel II++ step before Basel III

Author

Listed:
  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Bertrand Hassani

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

Abstract

Following Banking Committee on Banking Supervision, operational risk quantification is based on the Basel matrix which enables sorting incidents. In this paper, we deeply analyze these incidents and propose strategies for carrying out the supervisory guidelines proposed by the regulators. The objectives are as follows. On the first hand, banks need to provide a univariate capital charge for each cell of the Basel matrix. On the other hand, banks need also to provide a global capital charge corresponding to the whole matrix taking into account dependences. This paper proposes several solutions and attracts the regulators and managers attention on two crucial points : the granularity and the risk measures.

Suggested Citation

  • Dominique Guegan & Bertrand Hassani, 2012. "Operational risk : A Basel II++ step before Basel III," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00722029, HAL.
    • Handle: RePEc:hal:cesptp:halshs-00722029
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00722029
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    References listed on IDEAS

    as
    1. Luceno, Alberto, 2006. "Fitting the generalized Pareto distribution to data using maximum goodness-of-fit estimators," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 904-917, November.
    2. 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.
    3. Dominique Guegan & Pierre-André Maugis, 2010. "New Prospects on Vines," Post-Print halshs-00348884, HAL.
    4. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    5. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    6. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    7. Hall, Peter, 1990. "Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems," Journal of Multivariate Analysis, Elsevier, vol. 32(2), pages 177-203, February.
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    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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    Cited by:

    1. Bertrand K. Hassani, 2014. "Risk Appetite in Practice: Vulgaris Mathematica," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01020293, HAL.
    2. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    3. Dominique Gu�gan & Xin Zhao, 2014. "Alternative modeling for long term risk," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2237-2253, December.
    4. Dominique Guegan & Bertrand Hassani, 2011. "Multivariate VaRs for Operational Risk Capital Computation: a Vine Structure Approach," Documents de travail du Centre d'Economie de la Sorbonne 11017rr, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Apr 2012.
    5. Bertrand K. Hassani, 2014. "Risk Appetite in Practice: Vulgaris Mathematica," Post-Print halshs-01020293, HAL.
    6. repec:hal:journl:halshs-01163837 is not listed on IDEAS
    7. Bertrand K Hassani, 2015. "Model Risk - From Epistemology to Management. Ipse se nihil scire id unum sciat. (Socrates' Plato)," Documents de travail du Centre d'Economie de la Sorbonne 15026, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    8. Bertrand K Hassani, 2014. "Risk Appetite in Practice: Vulgaris Mathematica," Documents de travail du Centre d'Economie de la Sorbonne 14037, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. Dominique Guegan & Bertrand K. Hassani, 2011. "A mathematical resurgence of risk management: an extreme modeling of expert opinions," Documents de travail du Centre d'Economie de la Sorbonne 11057, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    10. Bryce, Cormac & Webb, Rob & Cheevers, Carly & Ring, P. & Clark, G., 2016. "Should the insurance industry be banking on risk escalation for solvency II?," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 131-139.
    11. Dominique Guegan & Bertrand Hassani, 2012. "Multivariate VaRs for Operational Risk Capital Computation: a Vine Structure Approach," Post-Print halshs-00587706, HAL.
    12. Bertrand K. Hassani, 2015. "Model Risk – From Epistemology to Management. Ipse se nihil scire id unum sciat. (Socrates' Plato)," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01163837, HAL.

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    More about this item

    Keywords

    Operational risks; Loss Distribution Function; risk measures; EVT; Vine copula; Risque opérationnel; Distribution de perte; mesures de risques; copules;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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