Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/97207
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dc.contributorDepartment of Applied Mathematicsen_US
dc.creatorXu, ZQen_US
dc.date.accessioned2023-02-17T00:58:47Z-
dc.date.available2023-02-17T00:58:47Z-
dc.identifier.issn0346-1238en_US
dc.identifier.urihttp://hdl.handle.net/10397/97207-
dc.language.isoenen_US
dc.publisherTaylor & Francis Scandinaviaen_US
dc.rights© 2022 Informa UK Limited, trading as Taylor & Francis Groupen_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in Scandinavian Actuarial Journal on 08 Jul 2022 (published online), available at: http://www.tandfonline.com/10.1080/03461238.2022.2092892.en_US
dc.subjectMean-variance premium principleen_US
dc.subjectMoral-hazard-free insuranceen_US
dc.subjectOptimal insuranceen_US
dc.subjectQuantile optimizationen_US
dc.subjectRank-dependent utility theoryen_US
dc.titleMoral-hazard-free insurance : mean-variance premium principle and rank-dependent utility theoryen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage269en_US
dc.identifier.epage289en_US
dc.identifier.volume2023en_US
dc.identifier.issue3en_US
dc.identifier.doi10.1080/03461238.2022.2092892en_US
dcterms.abstractThis paper investigates a Pareto-optimal insurance problem, where the insured maximizes her rank-dependent utility preference and the insurer is risk-neutral and employs the mean-variance premium principle. To eliminate potential moral hazard issues, we only consider the so-called moral-hazard-free insurance contracts that obey the incentive compatibility constraint. The insurance problem is first formulated as a non-concave maximization problem involving Choquet expectation, then turned into a concave quantile optimization problem and finally solved by the calculus of variations method. The optimal contract is expressed by a semi-linear second-order double-obstacle ordinary differential equation with nonlocal operator. An effective numerical method is proposed to compute the optimal contract assuming the probability weighting function has a density. Also, we provide an example that is analytically solved.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationScandinavian actuarial journal, 2023, v. 2023, no. 3, p. 269-289en_US
dcterms.isPartOfScandinavian actuarial journalen_US
dcterms.issued2022-
dc.identifier.scopus2-s2.0-85133568774-
dc.identifier.eissn1651-2030en_US
dc.description.validate202302 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera1917, a2099; a3419b-
dc.identifier.SubFormID46128, 46596, 46598; 50096-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNSFC; PolyU-SDU Joint Research Center on Financial Mathematics; CAS AMSS-POLYU Joint Laboratory of Applied Mathematics, The Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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