A Simple Recursive Forecasting Model

dc.contributor.authorBranch, William A.
dc.contributor.authorEvans, George W., 1949-
dc.date.accessioned2005-03-22T22:26:23Z
dc.date.available2005-03-22T22:26:23Z
dc.date.issued2005-02-01
dc.description10 p.en
dc.description.abstractWe compare the performance of alternative recursive forecasting models. A simple constant gain algorithm, used widely in the learning literature, both forecasts well out of sample and also provides the best fit to the Survey of Professional Forecasters.en
dc.format.extent252245 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/1794/654
dc.language.isoen_US
dc.publisherUniversity of Oregon, Dept of Economicsen
dc.relation.ispartofseriesUniversity of Oregon Economics Department Working Papers ; 2005-3
dc.subjectConstant gainen
dc.subjectRecursive learningen
dc.subjectExpectationsen
dc.titleA Simple Recursive Forecasting Modelen
dc.typeWorking Paperen

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