Sensitivity of Weights in Combining Forecasts

Robert L. Winkler · Robert T. Clemen

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Forecasting Techniques and Applications Statistical and numerical algorithms Grey System Theory Applications

Abstract

In the combination of forecasts, weighted averages that attempt to take into account the accuracy of the forecasts and any dependence among forecasts tend to perform poorly in practice. An important factor influencing this performance is the sensitivity, or instability, of the estimated weights used to generate the combined forecast. The intent of this paper is to look at this instability via graphs and the sampling distribution of the weights. Results are developed for the combination of two forecasts and extended to the m-forecast case by viewing the m-forecast case as a sequence of two-forecast combinations.

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References

2000Forecasting Economic Time Series 1990Combining forecasts: A review and annotated bibliography 1974Experience with Forecasting Univariate Time Series and the Combination of Forecasts 1986Combining Economic Forecasts 1985Limits for the Precision and Value of Information from Dependent Sources 1975A Bayesian Approach to the Linear Combination of Forecasts 1986Unstable Weights in the Combination of Forecasts 1987Combination of Forecasts: An Extension

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