Targeted growth rates for long-horizon crude oil price forecasts
International Journal of Forecasting, 2018, vol. 34, issue 1, 1-16
This paper proposes growth rate transformations with targeted lag selection in order to improve the long-horizon forecast accuracy. The method targets lower frequencies of the data that correspond to particular forecast horizons, and is applied to models of the real price of crude oil. Targeted growth rates can improve the forecast precision significantly at horizons of up to five years. For the real price of crude oil, the method can achieve a degree of accuracy up to five years ahead that previously has been achieved only at shorter horizons.
Keywords: Forecasting and prediction methods; Oil prices; Filters; Spectral analysis (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:34:y:2018:i:1:p:1-16
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