An efficient threshold choice for operational risk capital computation
Dominique Guegan (dominique.guegan@univ-paris1.fr),
Bertrand Hassani (bertrand.hassani@malix.univ-paris1.fr) and
Cédric Naud (cedric.naud@aon.fr)
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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, BPCE - BPCE
Bertrand Hassani: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, BPCE - BPCE
Cédric Naud: AON - AON
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Abstract:
Operational risk quantification requires dealing with data sets which often present extreme values which have a tremendous impact on capital computations (VaR). In order to take into account these effects we use extreme value distributions, and propose a two pattern model to characterize loss distribution functions associated to operational risks : a lognormal on the corpus of the severity distribution and a Generalized Pareto Distribution on the right tail. The threshold from which the model switches form a scheme to the other one is obtained using a bootstrap method. We use an extension of the Peak-over-threshold method to fit the GPD and the EM algorithm to estimate the lognormal distribution parameters. Through the VaR, we show the impact of the GPD estimation procedure on the capital requirements. Besides, our work points out the importance of the building's choice of the information set by practitioners to compute capital requirements and we exhibit some incoherences with the actual rules. Particularly, we highlight a problem arising from the granularity which has recently been mentioned by the Basel Committee for Banking Supervision.
Keywords: Operational risk; generalized Pareto distribution; Picklands estimate; Hill estimate; Expectation Maximization algorithm; Monte Carlo simulations; VaR; Risques opérationnels; distribution de pareto généralisée; estimateur de Pickland; estimateur de Hill; algorithme EM; méthodes de Monte Carlo (search for similar items in EconPapers)
Date: 2011
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00790217
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Citations: View citations in EconPapers (25)
Published in The Journal of Operational Risk, 2011, 6 (4), pp.3 - 19
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-00790217
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