The Heavy-Tailed Gleser Model: Properties, Estimation, and Applications

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datacite.alternateIdentifier.citationMATHEMATICS,Vol.10,,2022
datacite.alternateIdentifier.doi10.3390/math10234577
datacite.creatorOlmos, Neveka M.
datacite.creatorGomez Deniz, Emilio
datacite.creatorVenegas, Osvaldo
datacite.date2022
datacite.subject.englishgleser distribution
datacite.subject.englishheavy-tailed distribution
datacite.subject.englishmaximum likelihood
datacite.subject.englishVaR
datacite.titleThe Heavy-Tailed Gleser Model: Properties, Estimation, and Applications
dc.date.accessioned2023-06-08T15:48:08Z
dc.date.available2023-06-08T15:48:08Z
dc.description.abstractIn actuarial statistics, distributions with heavy tails are of great interest to actuaries, as they represent a better description of risk exposure through a type of indicator with a certain probability. These risk indicators are used to determine companies' exposure to a particular risk. In this paper, we present a distribution with heavy right tail, studying its properties and the behaviour of the tail. We estimate the parameters using the maximum likelihood method and evaluate the performance of these estimators using Monte Carlo. We analyse one set of simulated data and another set of real data, showing that the distribution studied can be used to model income data.
dc.identifier.urihttps://repositoriodigital.uct.cl/handle/10925/5223
dc.language.isoen
dc.publisherMDPI
dc.sourceMATHEMATICS
oaire.resourceTypeArticle
uct.indizacionSCI
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