Forecast evaluation improving using the simplest methods of individual forecasts’ combination
Ekaterina Astafyeva () and
Marina Turuntseva
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Ekaterina Astafyeva: Russian Presidential Academy of National Economy and Public Administration (RANEPA), Moscow, Russian Federation
Authors registered in the RePEc Author Service: Ekaterina Astafieva
Applied Econometrics, 2024, vol. 74, 78-103
Abstract:
Combining forecasts is considered the easiest way to improve the forecast quality compared to individual models. In this paper, we test the capabilities of the simplest methods of combination, such as simple averages and estimates based on the standard error of previous forecasts, to improve the performance of short-run forecasts of five resource price indicators (oil and metals). The basis of the work is the Gaidar Institute forecasts database, which provides the database of primary forecasts and allows you to calculate their combinations in real time. Based on the obtained results we conclude that even the simplest methods of combination are a way to improve the accuracy of forecasts. In addition, in the case of resource prices, one can even single out a group of methods (namely, combining with weights inversely proportional to the squared errors of individual forecasts) that provide the maximum gain in quality for the most periods.
Keywords: forecast combinations; oil prices; aluminum prices; gold prices; nickel prices; copper prices. (search for similar items in EconPapers)
JEL-codes: C53 E31 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:ris:apltrx:0498
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