dc.creator | Ramírez Cobo, Josefa | es |
dc.creator | Carrizosa Priego, Emilio José | es |
dc.creator | Lillo Rodríguez, Rosa Elvira | es |
dc.date.accessioned | 2021-04-23T09:59:49Z | |
dc.date.available | 2021-04-23T09:59:49Z | |
dc.date.issued | 2020-12-22 | |
dc.identifier.citation | Ramírez Cobo, J., Carrizosa Priego, E.J. y Lillo Rodríguez, R.E. (2020). Analysis of an aggregate loss model in a Markov renewal regime. Applied Mathematics and Computation, 396, 125869-1-125869-20. | |
dc.identifier.issn | 0096-3003 | es |
dc.identifier.issn | 1873-5649 | es |
dc.identifier.uri | https://hdl.handle.net/11441/107633 | |
dc.description.abstract | In this article we consider an aggregate loss model with dependent losses. The loss oc- currence process is governed by a two-state Markovian arrival process ( MAP 2 ), a Markov renewal process that allows for (1) correlated inter-loss times, (2) non-exponentially dis- tributed inter-loss times and, (3) overdisperse loss counts. Some quantities of interest to measure persistence in the loss occurrence process are obtained. Given a real OpRisk database, the aggregate loss model is estimated by fitting separately the inter-loss times and severities. The MAP 2 is estimated via direct maximization of the likelihood function, and severities are modeled by the heavy-tailed, double-Pareto Lognormal distribution. In comparison with the fit provided by the Poisson process, the results point out that taking into account the dependence and overdispersion in the inter-loss times distribution leads to higher capital charges. | es |
dc.format | application/pdf | es |
dc.format.extent | 20 p. | es |
dc.language.iso | eng | es |
dc.publisher | ELSEVIER SCIENCE INC | es |
dc.relation.ispartof | Applied Mathematics and Computation, 396, 125869-1-125869-20. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Loss modeling | es |
dc.subject | Dependent loss times | es |
dc.subject | Overdispersion | es |
dc.subject | Markov renewal theory | es |
dc.subject | Batch Markovian arrival process | es |
dc.subject | PH distribution | es |
dc.subject | Double-Pareto Lognormal distribution | es |
dc.subject | MLE estimation | es |
dc.subject | Operational risk | es |
dc.subject | Value-at-Risk | es |
dc.title | Analysis of an aggregate loss model in a Markov renewal regime | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Estadística e Investigación Operativa | es |
dc.relation.publisherversion | http://doi.org/10.1016/j.amc.2020.125869 | es |
dc.identifier.doi | 10.1016/j.amc.2020.125869 | es |
dc.contributor.group | Universidad de Sevilla. FQM329: Optimización | es |
dc.journaltitle | Applied Mathematics and Computation | es |
dc.publication.volumen | 396 | es |
dc.publication.initialPage | 125869-1 | es |
dc.publication.endPage | 125869-20 | es |