Why do some combinations perform better than others?
The evidence from the literature on forecast combination shows that combinations generally perform well. We discuss here how the accuracy and diversity of the methods being combined and the robustness of the combination rule can influence performance, and illustrate this by showing that a simple, robust combination of a subset of the nine methods used in the M4 competition's best combination performs almost as well as that forecast, and is easier to implement. We screened out methods with low accuracy or highly correlated errors and combined the remaining methods using a trimmed mean. We also investigated the accuracy risk (the risk of a bad forecast), proposing two new accuracy measures for this purpose. Our trimmed mean and the trimmed mean of all nine methods both had lower accuracy risk than either the best combination in the M4 competition or the simple mean of the nine methods.
Duke Scholars
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- 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