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Energy prices forecasting using nonlinear univariate models

Zuzanna Karolak

Bank i Kredyt, 2021, vol. 52, issue 6, 577-598

Abstract: This study analyses whether nonlinear methods are powerful enough to outperform consistently the no-change forecast for prices of key energy commodities, i.e. Brent crude oil, WTI crude oil, natural gas and coal. Six classes of nonlinear models are tested: threshold models (both self-exciting and external threshold variable model approach), smooth transition models (self-exciting and external threshold variable model approach), Markov regime switching models and neural networks. The forecasting competition is designed to simulate a real-time forecasting scheme. The analysis provides some evidence for predictive capabilities of nonlinear methods, but only in short-term horizons.

Keywords: energy commodities; prices forecasting; nonlinear models (search for similar items in EconPapers)
JEL-codes: C24 C34 L71 Q47 (search for similar items in EconPapers)
Date: 2021
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Handle: RePEc:nbp:nbpbik:v:52:y:2021:i:6:p:577-598