Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22720
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dc.contributor.authorSennewald, Kenen_US
dc.date.accessioned2009-01-29T15:07:49Z-
dc.date.available2009-01-29T15:07:49Z-
dc.date.issued2005en_US
dc.identifier.urihttp://hdl.handle.net/10419/22720-
dc.description.abstractThe present paper is concerned with the optimal control of stochastic differential equations, where uncertainty stemsfrom one or more independent Poisson processes. Optimal behavior in such a setup (e.g., optimal consumption) isusually determined by employing the Hamilton-Jacobi-Bellman equation. This, however, requires strong assumptionson the model, such as a bounded utility function and bounded coefficients in the controlled differential equation. Thepresent paper relaxes these assumptions. We show that one can still use the Hamilton-Jacobi-Bellman equation as anecessary criterion for optimality if the utility function and the coefficients are linearly bounded. We also derivesufficiency in a verification theorem without imposing any boundedness condition at all. It is finally shown that, undervery mild assumptions, an optimal Markov control is optimal even within the class of general controls.en_US
dc.language.isoengen_US
dc.relation.ispartofseries|aDresden discussion paper in economics |x03/05en_US
dc.subject.jelC61en_US
dc.subject.ddc330en_US
dc.subject.keywordStochastic differential equationen_US
dc.subject.keywordPoisson processen_US
dc.subject.keywordBellman equationen_US
dc.subject.stwKontrolltheorieen_US
dc.subject.stwAnalysisen_US
dc.subject.stwStochastischer Prozessen_US
dc.subject.stwZeitpräferenzen_US
dc.subject.stwTheorieen_US
dc.titleControlled Stochastic Differential Equations under Poisson Uncertainty and with Unbounded Utilityen_US
dc.typeWorking Paperen_US
dc.identifier.ppn498470601en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:tuddps:0305-

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