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A new algorithm for the loss distribution function with applications to Operational Risk Management
TL;DR: This paper proposes an adaptation of the Panjer algorithm in order to improve the computation of convolutions between Panjer class distributions and continuous distributions to reduce drastically the variance of the estimated VAR associated to the operational risks.
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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.
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Citations
Operational Risk: Modeling Analytics
TL;DR: The first part of the book focuses on finite-dimensional multivariate EV theory, which provides a complete picture of multivariate max-stable laws, which are the limit laws of componentwise maxima of iid random vectors.
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