A new algorithm for the loss distribution function with applications to Operational Risk Management

Dominique Guegan () and Bertrand Hassani ()
Additional contact information
Dominique Guegan: Centre d'Economie de la Sorbonne - Paris School of Economics, https://cv.archives-ouvertes.fr/dominique-guegan
Bertrand Hassani: CNCE 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: Operational risks inside banks and insurance companies is currently an important task. The computation of a risk measure associated to these risks lies on the knowledge of the so-called Loss Distribution Function. Traditionally this distribution function is computed via the Panjer algorithm which is an iterative algorithm. In this paper, we propose an adaptation of this last algorithm in order to improve the computation of convolutions between Panjer class distributions and continuous distributions. This new approach permits to reduce drastically the variance of the estimated VAR associated to the operational risks

Keywords: Operational risk; Panjer algorithm; Kernel; numerical integration; convolution (search for similar items in EconPapers)
JEL-codes: C1 C6 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2009-04, Revised 2009-11
New Economics Papers: this item is included in nep-rmg
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ftp://mse.univ-paris1.fr/pub/mse/CES2009/09023.pdf (application/pdf)

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Working Paper: A new algorithm for the loss distribution function with applications to Operational Risk Management (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:09023

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