Shapley-value-based forecast combination

IF 3.4 3区经济学 Q1 ECONOMICS

Journal of Forecasting Pub Date : 2024-08-07 DOI:10.1002/for.3178

Philip Hans Franses, Jiahui Zou, Wendun Wang

引用次数: 0

Abstract

This paper puts forward a new and simple method to combine forecasts, which is particularly useful when the forecasts are strongly correlated. It is based on the Mincer Zarnowitz regression, and a subsequent determination using Shapley values of the weights of the forecasts in a new combination. For a stylized case, it is proved that such a Shapley-value-based combination improves upon an equal-weight combination. Simulation experiments and a detailed illustration show the merits of the Shapley-value-based forecast combination.

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基于形状值的预测组合

本文提出了一种新的、简单的预测组合方法，这种方法在预测高度相关时特别有用。该方法基于 Mincer Zarnowitz 回归，随后使用 Shapley 值确定新组合中预测的权重。在一个典型的案例中，证明了这种基于夏普利值的组合比等权重组合更好。模拟实验和详细说明显示了基于夏普利值的预测组合的优点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Forecasting Multiple-

CiteScore

5.40

自引率

5.90%

发文量

期刊介绍： The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.