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http://hdl.handle.net/2445/156040
Title: | Aggregation of dependent risks with heavy-tail distributions |
Author: | Guillén, Montserrat Sarabia Alegría, José María Prieto, Faustino Jordá, Vanesa |
Keywords: | Risc (Assegurances) Avaluació del risc Distribució (Teoria de la probabilitat) Mètode de Montecarlo Risk (Insurance) Risk assessment Distribution (Probability theory) Monte Carlo method |
Issue Date: | Dec-2019 |
Publisher: | World Scientific Publishing |
Abstract: | Straightforward methods to evaluate risks arising from several sources are specially difficult when risk components are dependent and, even more if that dependence is strong in the tails. We give an explicit analytical expression for the probability distribution of the sum of non-negative losses that are tail-dependent. Our model allows dependence in the extremes of the marginal beta distributions. The proposed model is flexible in the choice of the parameters in the marginal distribution. The estimation using the method of moments is possible and the calculation of risk measures is easily done with a Monte Carlo approach. An illustration on data for insurance losses is presented. |
Note: | Versió postprint del document publicat a: https://doi.org/10.1142/S021848851940004X |
It is part of: | International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 2019, vol. 27, num. Supp 01, p. 77-88 |
URI: | http://hdl.handle.net/2445/156040 |
Related resource: | https://doi.org/10.1142/S021848851940004X |
ISSN: | 0218-4885 |
Appears in Collections: | Articles publicats en revistes (Econometria, Estadística i Economia Aplicada) |
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File | Description | Size | Format | |
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698164.pdf | 1.52 MB | Adobe PDF | View/Open |
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