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Discussion Paper Details
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Title: Forecast Combinations
Author(s): Allan Timmermann
Publication Date: November 2005
Keyword(s): diversification gains, forecast combinations, model misspecification, pooling and trimming and shrinkage methods
Programme Area(s): Financial Economics
Abstract: Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the degree of correlation between forecast errors and the relative size of the individual models? forecast error variances). Although the reasons for the success of simple combination schemes are poorly understood, we discuss several possibilities related to model misspecification, instability (non-stationarities) and estimation error in situations where the numbers of models is large relative to the available sample size. We discuss the role of combinations under asymmetric loss and consider combinations of point, interval and probability forecasts.
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Bibliographic Reference
Timmermann, A. 2005. 'Forecast Combinations'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=5361