Oil Price Factors: Forecasting on the Base of Modified ARIMA Model

Anthony Msafiri Nyangarika; Bao Jun Tang

doi:10.1088/1755-1315/192/1/012058

Oil Price Factors: Forecasting on the Base of Modified ARIMA Model

Anthony Msafiri Nyangarika, Bao Jun Tang

Research output: Contribution to journal › Conference article › peer-review

7 Citations (Scopus)

Abstract

The paper proposes the modification of ARIMA 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 by analyzing the possible risks in oil futures markets.

Original language	English
Article number	012058
Journal	IOP Conference Series: Earth and Environmental Science
Volume	192
Issue number	1
DOIs	https://doi.org/10.1088/1755-1315/192/1/012058
Publication status	Published - 5 Nov 2018
Externally published	Yes
Event	2018 2nd International Conference on Power and Energy Engineering, ICPEE 2018 - Xiamen, China Duration: 3 Sept 2018 → 5 Sept 2018

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10.1088/1755-1315/192/1/012058

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abstract = "The paper proposes the modification of ARIMA 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 by analyzing the possible risks in oil futures markets.",

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PY - 2018/11/5

Y1 - 2018/11/5

N2 - The paper proposes the modification of ARIMA 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 by analyzing the possible risks in oil futures markets.

AB - The paper proposes the modification of ARIMA 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 by analyzing the possible risks in oil futures markets.

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Oil Price Factors: Forecasting on the Base of Modified ARIMA Model

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