Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/32189
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dc.contributor.authorBendera, Christianen_US
dc.contributor.authorMoseler, Thiloen_US
dc.date.accessioned2009-09-17en_US
dc.date.accessioned2010-05-14T12:00:46Z-
dc.date.available2010-05-14T12:00:46Z-
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/10419/32189-
dc.description.abstractIn this paper we explain how the importance sampling technique can be generalized from simulating expectations to computing the initial value of backward SDEs with Lipschitz continuous driver. By means of a measure transformation we introduce a variance reduced version of the forward approximation scheme by Bender and Denk [4] for simulating backward SDEs. A fully implementable algorithm using the least-squares Monte Carlo approach is developed and its convergence is proved. The success of the generalized importance sampling is illustrated by numerical examples in the context of Asian option pricing under different interest rates for borrowing and lending.en_US
dc.language.isoengen_US
dc.publisher|aCoFE |cKonstanzen_US
dc.relation.ispartofseries|aDiscussion paper series // Zentrum für Finanzen und Ökonometrie, Universität Konstanz |x2008,11en_US
dc.subject.ddc330en_US
dc.subject.keywordBSDEen_US
dc.subject.keywordNumericsen_US
dc.subject.keywordMonte Carlo simulationen_US
dc.subject.keywordVariance reductionen_US
dc.titleImportance sampling for backward SDEsen_US
dc.type|aWorking Paperen_US
dc.identifier.ppn608957798en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-

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