Research Article
Crude Oil Price Prediction Based on Multiple Linear Regression Model
@INPROCEEDINGS{10.4108/eai.28-10-2022.2328443, author={Ziding Yuan}, title={Crude Oil Price Prediction Based on Multiple Linear Regression Model}, proceedings={Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China}, publisher={EAI}, proceedings_a={FFIT}, year={2023}, month={4}, keywords={multiple linear regression; price prediction; r-square test}, doi={10.4108/eai.28-10-2022.2328443} }- Ziding Yuan
Year: 2023
Crude Oil Price Prediction Based on Multiple Linear Regression Model
FFIT
EAI
DOI: 10.4108/eai.28-10-2022.2328443
Abstract
The Russian-Ukraine conflict has had a significant impact on the world economy. This effect is mainly reflected in the energy market as the decisive role of Russia in fossil energy export, bringing a massive change to the price of the world energy market. This paper uses data from mainly EIA to build a multiple linear regression model and focuses on predicting the price of crude oil. The five independent variables chosen to create a multiple linear regression model are time supply, demand, CPI, and GDP. From time to time, the price of crude oil changes on account of many other reasons. Among various cause, supply and demand are two main reasons known to affect the price of crude oil. Thus, the paper studies the correlation of the price of selected target with CPI and GDP and also provides information on the possible future crude oil price. The price fluctuation of crude oil can significantly affect the market related to crude oil, for example, transporting sectors and some manufacturing sectors. The profit of these two sectors is closely associated with the price of crude oil. Therefore, the correct prediction of crude oil can help them suffer less loss during these times of the Russian-Ukraine conflict. These results shed light on guiding further exploration of oil price prediction.