Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/25469 
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dc.contributor.authorParpas, Panosen
dc.contributor.authorRustem, Bercen
dc.contributor.authorWieland, Volkeren
dc.contributor.authorZakovic, Stanen
dc.date.accessioned2006-08-07-
dc.date.accessioned2009-07-24T13:47:48Z-
dc.date.available2009-07-24T13:47:48Z-
dc.date.issued2006-
dc.identifier.piurn:nbn:de:hebis:30-25940en
dc.identifier.urihttp://hdl.handle.net/10419/25469-
dc.description.abstractIn this paper, we consider expected value, variance and worst-case optimization of nonlinear models. We present algorithms for computing optimal expected values, and variance, based on iterative Taylor expansions. We establish convergence and consider the relative merits of policies beaded on expected value optimization and worst-case robustness. The latter is a minimax strategy and ensures optimal cover in view of the worst-case scenario(s) while the former is optimal expected performance in a stochastic setting. Both approaches are used with a macroeconomic policy model to illustrate relative performances, robustness and trade-offs between the strategies.en
dc.language.isoengen
dc.publisher|aGoethe University Frankfurt, Center for Financial Studies (CFS) |cFrankfurt a. M.en
dc.relation.ispartofseries|aCFS Working Paper |x2006/03en
dc.subject.jelC61en
dc.subject.jelE43en
dc.subject.ddc330en
dc.titleMean variance optimization of non-linear systems and worst-case analysis-
dc.typeWorking Paperen
dc.identifier.ppn515332216en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:cfswop:200603en

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