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Aggregation of Dependent Risks with Heavy-Tail Distributions

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 exible 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.

 Autoría: Guillen M., Sarabia J.M., Prieto F., Jordá V.,

 Fuente: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 27, Suppl. 1 (December 2019) 77-88

 Editorial: World Scientific Publishing

 Fecha de publicación: 01/12/2019

 Nº de páginas: 12

 Tipo de publicación: Artículo de Revista

 DOI: 10.1142/S021848851940004X

 ISSN: 1793-6411,0218-4885

 Proyecto español: ECO2016-476203-C2-1-P

 Url de la publicación: http://dx.doi.org/10.1142/S021848851940004X