Predicting crude oil prices using SARIMA-X method: An empirical study

Anshul Agrawal, Sanjeev Kadam (), Pooja A. Kapoor () and Mohammed Rashid ()
Additional contact information
Anshul Agrawal: GNIOT Institute of Management Studies (GIMS), Greated Noida, India
Sanjeev Kadam: ��Symbiosis Institute of Business Management Pune, Symbiosis International (Deemed University) Pune, India
Pooja A. Kapoor: GNIOT Institute of Management Studies (GIMS), Greated Noida, India
Mohammed Rashid: ��School of Management (NIET), Greated Noida, India

International Journal of Financial Engineering (IJFE), 2025, vol. 12, issue 01, 1-12

Abstract: Crude oil prices wield substantial influence over economic stability and sustainability, exerting a profound impact across various sectors and significantly moulding the economic well-being of nations. Thus, precision of predicting crude oil prices is of utmost importance for a wide array of stakeholders, including policymakers, investors, and participants in the energy market. This study offers an empirical exploration of the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMA-X) method, employing RMSE and MAPE values for forecasting crude oil prices during the most volatile periods from 2020 to 2023, including both COVID-19 pandemic and Russia Ukraine war period. The results indicate that the SARIMA-X method is effective for predicting crude oil prices during turbulent market conditions. This model can be a valuable tool for investors, traders, and other market participants, enabling them to make informed decisions when it comes to both intraday trading and long-term forecasting of crude oil prices.

Keywords: Crude oil; energy; forecasting; SDG; sustainability; SARIMA-X (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S2424786324500075
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijfexx:v:12:y:2025:i:01:n:s2424786324500075

Ordering information: This journal article can be ordered from

DOI: 10.1142/S2424786324500075

Access Statistics for this article

International Journal of Financial Engineering (IJFE) is currently edited by George Yuan

More articles in International Journal of Financial Engineering (IJFE) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().