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http://hdl.handle.net/10419/25469
  

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dc.contributor.authorParpas, Panosen_US
dc.contributor.authorRustem, Bercen_US
dc.contributor.authorWieland, Volkeren_US
dc.contributor.authorZakovic, Stanen_US
dc.date.accessioned2006-08-07en_US
dc.date.accessioned2009-07-24T13:47:48Z-
dc.date.available2009-07-24T13:47:48Z-
dc.date.issued2006en_US
dc.identifier.piurn:nbn:de:hebis:30-25940-
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_US
dc.language.isoengen_US
dc.publisherCenter for Financial Studies Frankfurt, Mainen_US
dc.relation.ispartofseriesCFS Working Paper 2006/03en_US
dc.subject.jelC61en_US
dc.subject.jelE43en_US
dc.subject.ddc330en_US
dc.titleMean variance optimization of non-linear systems and worst-case analysisen_US
dc.typeWorking Paperen_US
dc.identifier.ppn515332216en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:cfswop:200603-
Appears in Collections:CFS Working Paper Series, Universität Frankfurt a. M.

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