Oil price factors: Forecasting on the base of modified auto-regressive integrated moving average model

Anthony Nyangarika, Alexey Mikhaylov, Ulf Henning Richter

Research output: Contribution to journalArticlepeer-review

Abstract

The paper proposes modification of auto-regressive integrated moving average model for finding the parameters of estimation and forecasts using exponential smoothing. The study use data Brent crude oil price and gas prices in the period from January 1991 to December 2016. The result of the study showed an improvement in the accuracy of the predicted values, while the emissions occurred near the end of the time series. It has minimal or no effect on other emissions of this data series. The study suggests that investors can predict prices analyzing the possible risks in oil futures markets.

Original languageEnglish
Pages (from-to)149-159
Number of pages11
JournalInternational Journal of Energy Economics and Policy
Volume9
Issue number1
DOIs
StatePublished - 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018, Econjournals. All rights reserved.

Keywords

  • Auto-regressive integrated moving average model
  • Econometric model
  • Oil price forecast

ASJC Scopus subject areas

  • General Energy
  • General Economics, Econometrics and Finance

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