Efficient Forecasting in Nearly Non-stationary Processes
Ismael Sanchez
Journal of Forecasting, 2002, vol. 21, issue 1, 1-26
Abstract:
This paper proposes a procedure to make efficient predictions in a nearly non-stationary process. The method is based on the adaptation of the theory of optimal combination of forecasts to nearly non-stationary processes. The proposed combination method is simple to apply and has a better performance than classical combination procedures. It also has better average performance than a differenced predictor, a fractional differenced predictor, or an optimal unit-root pretest predictor. In the case of a process that has a zero mean, only the non-differenced predictor is slightly better than the proposed combination method. In the general case of a non-zero mean, the proposed combination method has a better overall performance than all its competitors. Copyright © 2002 by John Wiley & Sons, Ltd.
Date: 2002
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jof:jforec:v:21:y:2002:i:1:p:1-26
Access Statistics for this article
Journal of Forecasting is currently edited by Derek W. Bunn
More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().