Study for Urals Oil Price Based on ARIMA Model

Meixuan Lou

2023

Abstract

In time series forecasting, oil price forecasting is one of the most famous studies. That is because oil price forecast is essential, for the price of oil is related to transportation cost, stock market, and consumer purchasing power. Under the Russian-Ukrainian conflict and COVID-19 pandemic circumstances, the oil of Russia has been influenced a lot. However, nowadays, there is research on the oil price combined with the Russia-Ukraine conflict and the COVID-19 pandemic. In this paper, both the Autoregressive Integrated Moving Average Model (ARIMA) (p, d, q) model and the auto_ARIMA model are used to analyze the time series. The short-term estimate for the ural oil price is based on the ARIMA (0, 1, 1) model, which is clarified in detail. The findings demonstrated that in the short-term prediction area, the ARIMA (0, 1, 1)model has a strong and reliable potential. In addition, the price of Urals oil is expected to increase shortly. Besides this model can also be used in different situations.

Paper Citation

in Harvard Style

Lou M. (2023). Study for Urals Oil Price Based on ARIMA Model. In Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-705-4, SciTePress, pages 10-13. DOI: 10.5220/0012808900003885

in Bibtex Style

@conference{daml23,
author={Meixuan Lou},
title={Study for Urals Oil Price Based on ARIMA Model},
booktitle={Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2023},
pages={10-13},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012808900003885},
isbn={978-989-758-705-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Study for Urals Oil Price Based on ARIMA Model
SN - 978-989-758-705-4
AU - Lou M.
PY - 2023
SP - 10
EP - 13
DO - 10.5220/0012808900003885
PB - SciTePress