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dc.contributor.authorGuillén, Montserrat-
dc.contributor.authorSarabia Alegría, José María-
dc.contributor.authorPrieto, Faustino-
dc.contributor.authorJordá, Vanesa-
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 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.-
dc.format.extent12 p.-
dc.publisherWorld Scientific Publishing-
dc.relation.isformatofVersió postprint del document publicat a:
dc.relation.ispartofInternational Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 2019, vol. 27, num. Supp 01, p. 77-88-
dc.rights(c) World Scientific Publishing, 2019-
dc.subject.classificationRisc (Assegurances)-
dc.subject.classificationAvaluació del risc-
dc.subject.classificationDistribució (Teoria de la probabilitat)-
dc.subject.classificationMètode de Montecarlo-
dc.subject.otherRisk (Insurance)-
dc.subject.otherRisk assessment-
dc.subject.otherDistribution (Probability theory)-
dc.subject.otherMonte Carlo method-
dc.titleAggregation of dependent risks with heavy-tail distributions-
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

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