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dc.contributor.authorGuillen, Montserrates_ES
dc.contributor.authorSarabia Alegría, José María es_ES
dc.contributor.authorPrieto Mendoza, Faustino es_ES
dc.contributor.authorJordá, Vanesa es_ES
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2025-01-24T09:35:14Z
dc.date.available2025-01-24T09:35:14Z
dc.date.issued2019-12es_ES
dc.identifier.issn1793-6411es_ES
dc.identifier.issn0218-4885es_ES
dc.identifier.otherECO2016-476203-C2-1-Pes_ES
dc.identifier.otherECO2016-476203-C2-2-Pes_ES
dc.identifier.urihttps://hdl.handle.net/10902/35153
dc.description.abstractStraightforward 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 presentedes_ES
dc.format.extent12 p.es_ES
dc.language.isoenges_ES
dc.publisherWorld Scientific Publishinges_ES
dc.rightsAlojado según Resolución CNEAI 9/12/24 (ANECA) ©World Scientic Publishing Companyes_ES
dc.sourceInternational Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2019, 27(1), 77-88es_ES
dc.titleAggregation of dependent risks with heavy-tail distributionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1142/S021848851940004Xes_ES
dc.rights.accessRightsclosedAccess
dc.identifier.DOI10.1142/S021848851940004Xes_ES
dc.type.versionpublishedVersiones_ES


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