IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v141y2025ics0140988324008144.html
   My bibliography  Save this article

Energy organization sentiment and oil return forecast

Author

Listed:
  • Jeong, Minhyuk
  • Ahn, Kwangwon

Abstract

This study investigates the role of energy organization sentiments for oil return forecasts. First, we construct organization sentiment indexes using ChatGPT, a large language model, which enables us to extract sentimental information from the oil market reports issued by the International Energy Agency (IEA) and the Organization of the Petroleum Exporting Countries (OPEC). We found that organization sentiment indexes have a significantly negative impact on future oil price changes, and the information in OPEC's sentiment dominates that in the IEA's sentiment. The significance survives in models controlled by well-known oil pricing factors, e.g., oil market fundamentals, financial factors, and consumer and investor sentiments. The organization sentiment indexes Granger cause changes in oil production decisions, where oil production is identified as the channel through which the organization sentiment indexes influence future crude oil returns. We also found that the impact of organization sentiments is time-varying depending on investor sentiments and the market returns but mostly remains significant for both the in-sample fit and out-of-sample forecasts. Oil market participants, e.g., oil consumers, producers, and investors, can refer to the proposed organization sentiment indexes while trading crude oil to improve their utility. The inclusion of OPEC sentiment yields 2.40 % of certainty equivalent return gain, which is increased to 2.56 % with the addition of IEA sentiment. The findings of this study imply that the IEA should review its role and influence to maintain energy security effectively, and OPEC should track the profitability of its production adjustments.

Suggested Citation

  • Jeong, Minhyuk & Ahn, Kwangwon, 2025. "Energy organization sentiment and oil return forecast," Energy Economics, Elsevier, vol. 141(C).
  • Handle: RePEc:eee:eneeco:v:141:y:2025:i:c:s0140988324008144
    DOI: 10.1016/j.eneco.2024.108105
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324008144
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2024.108105?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Organization sentiment; IEA; OPEC; Crude oil return; ChatGPT;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F53 - International Economics - - International Relations, National Security, and International Political Economy - - - International Agreements and Observance; International Organizations
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:141:y:2025:i:c:s0140988324008144. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.