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dc.contributor.authorBendera, Christianen
dc.contributor.authorMoseler, Thiloen
dc.date.accessioned2009-09-17-
dc.date.accessioned2010-05-14T12:00:46Z-
dc.date.available2010-05-14T12:00:46Z-
dc.date.issued2008-
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
dc.language.isoengen
dc.publisher|aUniversity of Konstanz, Center of Finance and Econometrics (CoFE) |cKonstanzen
dc.relation.ispartofseries|aCoFE Discussion Paper |x08/11en
dc.subject.ddc330en
dc.subject.keywordBSDEen
dc.subject.keywordNumericsen
dc.subject.keywordMonte Carlo simulationen
dc.subject.keywordVariance reductionen
dc.titleImportance sampling for backward SDEs-
dc.type|aWorking Paperen
dc.identifier.ppn608957798en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:cofedp:0811-

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