Some Theoretical Results on Forecast Combinations
This paper proposes a framework for the analysis of the theoretical properties of forecast combination, with the forecast performance being measured in terms of mean squared forecast errors (MSFE). Such a framework is useful for deriving all existing results with ease. In addition, it also provides...
| Main Authors: | , |
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| Format: | Journal Article |
| Published: |
Elsevier
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/72424 |
| _version_ | 1848762746441564160 |
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| author | Chan, Felix Pauwels, L. |
| author_facet | Chan, Felix Pauwels, L. |
| author_sort | Chan, Felix |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper proposes a framework for the analysis of the theoretical properties of forecast combination, with the forecast performance being measured in terms of mean squared forecast errors (MSFE). Such a framework is useful for deriving all existing results with ease. In addition, it also provides insights into two forecast combination puzzles. Specifically, it investigates why a simple average of forecasts often outperforms forecasts from single models in terms of MSFEs, and why a more complicated weighting scheme does not always perform better than a simple average. In addition, this paper presents two new findings that are particularly relevant in practice. First, the MSFE of a forecast combination decreases as the number of models increases. Second, the conventional approach to the selection of optimal models, based on a simple comparison of MSFEs without further statistical testing, leads to a biased selection. |
| first_indexed | 2025-11-14T10:52:28Z |
| format | Journal Article |
| id | curtin-20.500.11937-72424 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:52:28Z |
| publishDate | 2018 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-724242019-02-08T05:31:17Z Some Theoretical Results on Forecast Combinations Chan, Felix Pauwels, L. This paper proposes a framework for the analysis of the theoretical properties of forecast combination, with the forecast performance being measured in terms of mean squared forecast errors (MSFE). Such a framework is useful for deriving all existing results with ease. In addition, it also provides insights into two forecast combination puzzles. Specifically, it investigates why a simple average of forecasts often outperforms forecasts from single models in terms of MSFEs, and why a more complicated weighting scheme does not always perform better than a simple average. In addition, this paper presents two new findings that are particularly relevant in practice. First, the MSFE of a forecast combination decreases as the number of models increases. Second, the conventional approach to the selection of optimal models, based on a simple comparison of MSFEs without further statistical testing, leads to a biased selection. 2018 Journal Article http://hdl.handle.net/20.500.11937/72424 10.1016/J.IJFORECAST.2017.08.005 Elsevier restricted |
| spellingShingle | Chan, Felix Pauwels, L. Some Theoretical Results on Forecast Combinations |
| title | Some Theoretical Results on Forecast Combinations |
| title_full | Some Theoretical Results on Forecast Combinations |
| title_fullStr | Some Theoretical Results on Forecast Combinations |
| title_full_unstemmed | Some Theoretical Results on Forecast Combinations |
| title_short | Some Theoretical Results on Forecast Combinations |
| title_sort | some theoretical results on forecast combinations |
| url | http://hdl.handle.net/20.500.11937/72424 |