A new algorithm for the loss distribution function with applications to Operational Risk Management
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.
|Date of creation:||Nov 2009|
|Publication status:||Published in Documents de travail du Centre d'Economie de la Sorbonne 2009.23 - ISSN : 1955-611X. 2009|
|Note:||View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00384398v2|
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- Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
- Grübel, Rudolf & Hermesmeier, Renate, 1999. "Computation of Compound Distributions I: Aliasing Errors and Exponential Tilting," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 29(02), pages 197-214, November.
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