Optimal policies for discrete time risk processes with a Markov chain investment model

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dc.contributor.author Diasparra, Maikol
dc.contributor.author Romera, Rosario
dc.date.accessioned 2006-11-09T10:59:39Z
dc.date.available 2006-11-09T10:59:39Z
dc.date.issued 2006-05
dc.identifier.uri http://hdl.handle.net/10016/239
dc.description.abstract We consider a discrete risk process modelled by a Markov Decision Process. The surplus could be invested in stock market assets. We adopt a realistic point of view and we let the investment return process to be statistically dependent over time. We assume that follows a Markov Chain model. To minimize the risk there is a possibility to reinsure a part or the whole reserve. We consider proportional reinsurance. Recursive and integral equations for the ruin probability are given. Generalized Lundberg inequalities for the ruin probabilities are derived. Stochastic optimal control theory is used to determine the optimal stationary policy which minimizes the ruin probability. To illustrate these results numerical examples are included.
dc.format.extent 291360 bytes
dc.format.mimetype application/pdf
dc.language.iso eng
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 2006-08
dc.title Optimal policies for discrete time risk processes with a Markov chain investment model
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws062408
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