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A modified Panjer algorithm for operational risk capital calculations

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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, 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

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

Abstract

Operational risk management inside banks and insurance companies is an important task. The computation of a risk measure associated to these kinds of risks lies in the knowledge of the so-called loss distribution function (LDF). Traditionally, this LDF is computed via Monte Carlo simulations or using the Panjer recursion, 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, by mixing the Monte Carlo method, a progressive kernel lattice and the Panjer recursion. This new hybrid algorithm does not face the traditional drawbacks. This simple approach enables us to drastically reduce the variance of the estimated value-at-risk associated with the operational risks and to lower the aliasing error we would have using Panjer recursion itself. Furthermore, this method is much less timeconsuming than a Monte Carlo simulation. We compare our new method with more sophisticated approaches already developed in operational risk literature.

Suggested Citation

  • Dominique Guegan & Bertrand Hassani, 2009. "A modified Panjer algorithm for operational risk capital calculations," PSE-Ecole d'économie de Paris (Postprint) halshs-00443846, HAL.
    • Handle: RePEc:hal:pseptp:halshs-00443846
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00443846
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    References listed on IDEAS

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    1. Grübel, Rudolf & Hermesmeier, Renate, 1999. "Computation of Compound Distributions I: Aliasing Errors and Exponential Tilting," ASTIN Bulletin, Cambridge University Press, vol. 29(2), pages 197-214, November.
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    Cited by:

    1. Dominique Guégan & Wayne Tarrant, 2012. "On the necessity of five risk measures," Annals of Finance, Springer, vol. 8(4), pages 533-552, November.
    2. Dominique Guegan & Wayne Tarrant, 2012. "Viewing Risk Measures as information," Working Papers halshs-00721350, HAL.
    3. Bertrand K. Hassani & Wei Yang, 2016. "The Lila distribution and its applications in risk modelling," Documents de travail du Centre d'Economie de la Sorbonne 16068, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    4. Dominique Gu'egan & Wayne Tarrant, 2011. "On the Necessity of Five Risk Measures," Papers 1111.4414, arXiv.org.
    5. Dominique Guegan & Wayne Tarrant, 2012. "On the Necessity of Five Risk Measures," Post-Print halshs-00721339, HAL.
    6. repec:hal:wpaper:halshs-00721339 is not listed on IDEAS
    7. Dominique Guegan & Wayne Tarrant, 2011. "Viewing risk measures as information," Documents de travail du Centre d'Economie de la Sorbonne 11054, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    8. Dominique Guegan & Bertrand Hassani, 2012. "Operational risk : A Basel II++ step before Basel III," PSE-Ecole d'économie de Paris (Postprint) halshs-00722029, HAL.
    9. Chih-Kang Chu & Ruey-Ching Hwang, 2019. "Predicting Loss Distributions for Small-Size Defaulted-Debt Portfolios Using a Convolution Technique that Allows Probability Masses to Occur at Boundary Points," Journal of Financial Services Research, Springer;Western Finance Association, vol. 56(1), pages 95-117, August.
    10. 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 11017, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    11. Dominique Guegan & Wayne Tarrant, 2012. "On the Necessity of Five Risk Measures," PSE-Ecole d'économie de Paris (Postprint) halshs-00721339, HAL.
    12. Dominique Guegan & Wayne Tarrant, 2011. "Viewing Risk Measures as information," Post-Print halshs-00639489, HAL.
    13. Dominique Guegan & Wayne Tarrant, 2010. "On the necessity of five risk measures," Post-Print halshs-00460901, HAL.
    14. Dominique Gu/'egan & Wayne Tarrant, 2011. "Viewing Risk Measures as Information," Papers 1111.4417, arXiv.org.
    15. Vasileios M. Koutras & Markos V. Koutras, 2020. "Exact Distribution of Random Order Statistics and Applications in Risk Management," Methodology and Computing in Applied Probability, Springer, vol. 22(4), pages 1539-1558, December.
    16. Bertrand K. Hassani & Wei Yang, 2016. "The Lila distribution and its applications in risk modelling," Post-Print halshs-01400186, HAL.

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