Simple robust averages of forecasts: Some empirical results
An extensive body of literature has shown that combining forecasts can improve forecast accuracy, and that a simple average of the forecasts (the mean) often does better than more complex combining schemes. The fact that the mean is sensitive to extreme values suggests that deleting such values or reducing their extremity might be worthwhile. We study the performance of two simple robust methods, trimmed and Winsorized means, which are easy to use and understand. For the data sets we consider, they provide forecasts which are slightly more accurate than the mean, and reduce the risk of high errors. Our results suggest that moderate trimming of 10-30% or Winsorizing of 15-45% of the forecasts can provide improved combined forecasts, with more trimming or Winsorizing being indicated when there is more variability among the individual forecasts. There are some differences in the performance of the trimmed and Winsorized means, but overall such differences are not large. © 2007 International Institute of Forecasters.
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Related Subject Headings
- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 1505 Marketing
- 1403 Econometrics
- 0104 Statistics
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 1505 Marketing
- 1403 Econometrics
- 0104 Statistics