A Simple Recursive Forecasting Model

William A. Branch () and George William Evans ()

University of Oregon Economics Department Working Papers from University of Oregon Economics Department

Abstract: We 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.

Keywords: constant gain; recursive learning; expectations (search for similar items in EconPapers)
JEL-codes: E37 D84 D83 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mac
Date: 2005-02-01
View list of references View citations in EconPapers

Downloads: (external link)
http://economics.uor ... mple_Forecasting.pdf (application/pdf)

Related works:
Journal Article: A simple recursive forecasting model (2006)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Access Statistics for this paper

More papers in University of Oregon Economics Department Working Papers from University of Oregon Economics Department
Contact information at EDIRC.
Series data maintained by Bill Harbaugh ().