Abstract
Management of extreme events is required of a special consideration, as well as a sufficiently wide time horizon for solvency evaluation. Whereas their classical adjustment is usually carried out with Extreme Value Theory (EVT)-based distributions (namely, the Generalized Pareto Distribution), Evolutionary Techniques have been tried herein to fit the GPD parameters as an optimisation problem. The comparison between classical and evolutionary techniques highlights the accuracy of the evolutionary process. Data adjusted in this paper come from a Spanish motor liability insurance portfolio.
Funded by CICYT TSI2005-07344, MADRINET S-0505/TIC/0255 and AUTOPIA IMSERSO.
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Pérez-Fructuoso, M.J., García, A., Berlanga, A., Molina, J.M. (2007). Adjusting the Generalized Pareto Distribution with Evolution Strategies – An application to a Spanish Motor Liability Insurance Database. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2007. IDEAL 2007. Lecture Notes in Computer Science, vol 4881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77226-2_101
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DOI: https://doi.org/10.1007/978-3-540-77226-2_101
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