The effect of nonstationarity on combined forecasts


Journal Article

Previous research on the combination of forecasts has, for the most part, implicitly assumed a stationary underlying process so that parameters could be estimated from historical data. While some models weight recent data more heavily in the estimation process in an attempt to provide more accurate parameter estimates in a nonstationary environment, no research to date has specifically examined the effects of nonstationarity on the performance of combining methods. This paper reports the results of a simulation study of the effects of nonstationarity (a shift in the process) on a range of forecast combination methods. Special attention is given to the relative performance of the methods in the time periods around the shift. © 1992.

Full Text

Duke Authors

Cited Authors

  • Miller, CM; Clemen, RT; Winkler, RL

Published Date

  • January 1, 1992

Published In

Volume / Issue

  • 7 / 4

Start / End Page

  • 515 - 529

International Standard Serial Number (ISSN)

  • 0169-2070

Digital Object Identifier (DOI)

  • 10.1016/0169-2070(92)90035-8

Citation Source

  • Scopus