IDEAS home Printed from https://ideas.repec.org/a/eee/jocoma/v37y2025ics2405851325000042.html
   My bibliography  Save this article

Media emotion intensity and commodity futures pricing

Author

Listed:
  • Chi, Yeguang
  • El-Jahel, Lina
  • Vu, Thanh

Abstract

This study investigates the impact of media emotion intensity on commodities futures returns. Emotion intensity measures the proportion of emotional content relative to factual content in media news. The media emotion intensity factor generates an annual premium of 13% after transaction cost. This premium is more pronounced for commodities with low media coverage, high momentum, high basis-momentum, high hedging pressure, and backwardation. Emotion intensity significantly predicts the trading tendencies of both commercial and non-commercial traders and the cross-section of commodity futures returns at both portfolio and individual levels. We also find that media emotion intensity predicts future commodities’ sentiment. Further, other commonly considered risk sources cannot subsume the predictability of the media emotion intensity factor.

Suggested Citation

  • Chi, Yeguang & El-Jahel, Lina & Vu, Thanh, 2025. "Media emotion intensity and commodity futures pricing," Journal of Commodity Markets, Elsevier, vol. 37(C).
  • Handle: RePEc:eee:jocoma:v:37:y:2025:i:c:s2405851325000042
    DOI: 10.1016/j.jcomm.2025.100460
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2405851325000042
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jcomm.2025.100460?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

    Commodity futures; Media emotion intensity; Asset return;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G40 - Financial Economics - - Behavioral Finance - - - General

    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:jocoma:v:37:y:2025:i:c:s2405851325000042. 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/jcomm .

    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.