IDEAS home Printed from https://ideas.repec.org/a/spr/jcsosc/v8y2025i1d10.1007_s42001-024-00355-7.html
   My bibliography  Save this article

Impact of information disparity between individual investors on profits of meme stocks using an artificial market simulation approach

Author

Listed:
  • Miyuki Matsumoto

    (The University of Tokyo)

  • Ryuji Hashimoto

    (The University of Tokyo)

  • Masahiro Suzuki

    (The University of Tokyo)

  • Yuri Murayama

    (The University of Tokyo)

  • Kiyoshi Izumi

    (The University of Tokyo)

Abstract

The growth of social media recently has made individual investors more reliant on online media for information. This trend significantly affects investor behavior and information disparity. For instance, social media can lead to the phenomenon of “meme stocks," in which stock prices rapidly rise and fall. Despite increasing interest in meme stocks, few studies have focused on the information disparity. In this study, we model meme stocks focusing on investors who are influenced by social network information, leading to information spread. We combine the Susceptible-Infectious-Recovered (SIR) model with a network model in an artificial market simulation to examine information disparity among individual investors. Our findings show that conventional investors generally profit, whereas social media investors incur losses. Additionally, the profits of social media investors are heavily affected by their network structure and their network distance from the information source. The results highlight the issue of information inequality in financial markets and offer important guidance for policymakers.

Suggested Citation

  • Miyuki Matsumoto & Ryuji Hashimoto & Masahiro Suzuki & Yuri Murayama & Kiyoshi Izumi, 2025. "Impact of information disparity between individual investors on profits of meme stocks using an artificial market simulation approach," Journal of Computational Social Science, Springer, vol. 8(1), pages 1-29, February.
  • Handle: RePEc:spr:jcsosc:v:8:y:2025:i:1:d:10.1007_s42001-024-00355-7
    DOI: 10.1007/s42001-024-00355-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s42001-024-00355-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s42001-024-00355-7?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.

    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:spr:jcsosc:v:8:y:2025:i:1:d:10.1007_s42001-024-00355-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.