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Article: Optimal proportional reinsurance to minimize the probability of drawdown under thinning-dependence structure

TitleOptimal proportional reinsurance to minimize the probability of drawdown under thinning-dependence structure
Authors
KeywordsProportional reinsurance
Stochastic optimal control
Probability of drawdown,
Thinning-dependence structure
Issue Date2018
PublisherTaylor & Francis Scandinavia. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/03461238.asp
Citation
Scandinavian Actuarial Journal, 2018, v. 2018 n. 10, p. 863-889 How to Cite?
AbstractIn this paper, we consider the optimal proportional reinsurance problem in a risk model with the thinning-dependence structure, and the criterion is to minimize the probability that the value of the surplus process drops below some fixed proportion of its maximum value to date which is known as the probability of drawdown. The thinning dependence assumes that stochastic sources related to claim occurrence are classified into different groups, and that each group may cause a claim in each insurance class with a certain probability. By the technique of stochastic control theory and the corresponding Hamilton–Jacobi–Bellman equation, the optimal reinsurance strategy and the corresponding minimum probability of drawdown are derived not only for the expected value principle but also for the variance premium principle. Finally, some numerical examples are presented to show the impact of model parameters on the optimal results.
Persistent Identifierhttp://hdl.handle.net/10722/259509
ISSN
2019 Impact Factor: 1.705
2015 SCImago Journal Rankings: 0.956
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHan, X-
dc.contributor.authorLiang, Z-
dc.contributor.authorYuen, KC-
dc.date.accessioned2018-09-03T04:08:59Z-
dc.date.available2018-09-03T04:08:59Z-
dc.date.issued2018-
dc.identifier.citationScandinavian Actuarial Journal, 2018, v. 2018 n. 10, p. 863-889-
dc.identifier.issn0346-1238-
dc.identifier.urihttp://hdl.handle.net/10722/259509-
dc.description.abstractIn this paper, we consider the optimal proportional reinsurance problem in a risk model with the thinning-dependence structure, and the criterion is to minimize the probability that the value of the surplus process drops below some fixed proportion of its maximum value to date which is known as the probability of drawdown. The thinning dependence assumes that stochastic sources related to claim occurrence are classified into different groups, and that each group may cause a claim in each insurance class with a certain probability. By the technique of stochastic control theory and the corresponding Hamilton–Jacobi–Bellman equation, the optimal reinsurance strategy and the corresponding minimum probability of drawdown are derived not only for the expected value principle but also for the variance premium principle. Finally, some numerical examples are presented to show the impact of model parameters on the optimal results.-
dc.languageeng-
dc.publisherTaylor & Francis Scandinavia. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/03461238.asp-
dc.relation.ispartofScandinavian Actuarial Journal-
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in Scandinavian Actuarial Journal on 30 Oct 2018, available online: http://www.tandfonline.com/10.1080/03461238.2018.1469098-
dc.subjectProportional reinsurance-
dc.subjectStochastic optimal control-
dc.subjectProbability of drawdown,-
dc.subjectThinning-dependence structure-
dc.titleOptimal proportional reinsurance to minimize the probability of drawdown under thinning-dependence structure-
dc.typeArticle-
dc.identifier.emailYuen, KC: kcyuen@hku.hk-
dc.identifier.authorityYuen, KC=rp00836-
dc.description.naturepostprint-
dc.identifier.doi10.1080/03461238.2018.1469098-
dc.identifier.scopuseid_2-s2.0-85056993409-
dc.identifier.hkuros289187-
dc.identifier.volume2018-
dc.identifier.issue10-
dc.identifier.spage863-
dc.identifier.epage889-
dc.identifier.isiWOS:000450512100001-
dc.publisher.placeSweden-

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