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dc.contributor.authorCorradi, Valentinaen_US
dc.contributor.authorSwanson, Normanen_US
dc.date.accessioned2011-06-14en_US
dc.date.accessioned2012-06-25T11:57:31Z-
dc.date.available2012-06-25T11:57:31Z-
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/10419/59484-
dc.description.abstractThis paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, we first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models. Then, we construct accuracy assessment tests that are in the spirit of Diebold and Mariano (1995) and White (2000). In order to establish the asymptotic properties of our tests, we also develop a recursive variant of the nonparametric simulated maximum likelihood estimator of Fermanian and Salanié (2004). In an empirical illustration, the predictive densities from several models of the one-month federal funds rates are compared.en_US
dc.language.isoengen_US
dc.publisherDep. of Economics, Rutgers, the State Univ. of New Jersey New Brunswick, NJen_US
dc.relation.ispartofseriesWorking Papers, Department of Economics, Rutgers, the State University of New Jersey 2011,12en_US
dc.subject.jelC22en_US
dc.subject.jelC51en_US
dc.subject.ddc330en_US
dc.subject.keywordblock bootstrapen_US
dc.subject.keyworddiffusion processesen_US
dc.subject.keywordjumpsen_US
dc.subject.keywordnonparametric simulated quasi maximum likelihooden_US
dc.subject.keywordparameter estimation erroren_US
dc.subject.keywordrecursive estimationen_US
dc.subject.keywordstochastic volatilityen_US
dc.subject.stwPrognoseverfahrenen_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwModellierungen_US
dc.subject.stwSchätztheorieen_US
dc.subject.stwTheorieen_US
dc.titlePredictive density construction and accuracy testing with multiple possibly misspecified diffusion modelsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn662033450en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Working Papers, Department of Economics, Rutgers University

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