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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Anshul Agrawal & Sanjeev Kadam & Pooja A. Kapoor & Mohammed Rashid, 2025. "Predicting crude oil prices using SARIMA-X method: An empirical study," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 1-12, March.
    • Handle: RePEc:wsi:ijfexx:v:12:y:2025:i:01:n:s2424786324500075
    DOI: 10.1142/S2424786324500075
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