The effect of nonstationarity on combined forecasts

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...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of forecasting Vol. 7; no. 4; pp. 515 - 529
Main Authors Miller, Christopher M., Clemen, Robert T., Winkler, Robert L.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.03.1992
Elsevier
Elsevier Sequoia S.A
SeriesInternational Journal of Forecasting
Subjects
Business forecasts
Combining forecasts, Nonstationarity
Effects
Mathematical models
Simulation
Statistical analysis
Studies
Combining forecasts, Nonstationarity
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:0169-2070
1872-8200
DOI:10.1016/0169-2070(92)90035-8