Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6965
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dc.contributorDepartment of Applied Mathematics-
dc.creatorLiu, J-
dc.creatorYiu, KFC-
dc.creatorLoxton, RC-
dc.creatorTeo, KL-
dc.date.accessioned2014-12-11T08:29:21Z-
dc.date.available2014-12-11T08:29:21Z-
dc.identifier.issn2162-2434 (print)-
dc.identifier.issn2162-2442 (online)-
dc.identifier.urihttp://hdl.handle.net/10397/6965-
dc.language.isoenen_US
dc.publisherScientific Researchen_US
dc.rightsCopyright © 2013 Jingzhen Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.subjectProportional reinsuranceen_US
dc.subjectMartingale transformen_US
dc.subjectValue-at-risken_US
dc.subjectStochastic controlen_US
dc.subjectDeterministic optimal controlen_US
dc.titleOptimal investment and proportional reinsurance with risk constrainten_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationAuthor name used in this publication: Yiu, Ka Fai Cedric.en_US
dc.identifier.spage437-
dc.identifier.epage447-
dc.identifier.volume3-
dc.identifier.issue4-
dc.identifier.doi10.4236/jmf.2013.34046-
dcterms.abstractIn this paper, we investigate the problem of maximizing the expected exponential utility for an insurer. In the problem setting, the insurer can invest his/her wealth into the market and he/she can also purchase the proportional reinsurance. To control the risk exposure, we impose a value-at-risk constraint on the portfolio, which results in a constrained stochastic optimal control problem. It is difficult to solve a constrained stochastic optimal control problem by using traditional dynamic programming or Martingale approach. However, for the frequently used exponential utility function, we show that the problem can be simplified significantly using a decomposition approach. The problem is reduced to a deterministic constrained optimal control problem, and then to a finite dimensional optimization problem. To show the effectiveness of the approach proposed, we consider both complete and incomplete markets; the latter arises when the number of risky assets are fewer than the dimension of uncertainty. We also conduct numerical experiments to demonstrate the effect of the risk constraint on the optimal strategy.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of mathematical finance, Nov. 2013, v. 3, no. 4, p.437-447-
dcterms.isPartOfJournal of mathematical finance-
dcterms.issued2013-11-
dc.identifier.rosgroupidr72370-
dc.description.ros2013-2014 > Academic research: refereed > Publication in refereed journal-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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