IDEAS home Printed from https://ideas.repec.org/a/eee/beexfi/v49y2026ics2214635026000171.html

Loss aversion in investment: A bibliometric and network visualization analysis

Author

Listed:
  • Soman, Siddhesh S.
  • Chirputkar, Abhijit
  • Punjani, Krunal K.

Abstract

Loss aversion is widely considered one of the most influential behavioral biases among investors and has been studied by several researchers over the years. However, a bibliometric study on the topic of ‘Loss Aversion in Investment’ does not exist. To address this gap, we present the first-ever bibliometric and network visualization analysis based on 427 research articles published from 1996 to October 2025. A comprehensive bibliometric protocol was followed, covering document selection, bibliometric analysis, network analysis, and content analysis. Data extracted from ‘Scopus’ database was analyzed using ‘Bibliometrix’ tool. Key indicators included annual research output, citation patterns, co-authorship, co-citation, bibliographic coupling, thematic trends, and keyword analysis. Network visualization was conducted using ‘VOSviewer’, while thematic analysis utilized Biblioshiny to identify emerging research themes. These analyses reveal key clusters in behavioral finance theories and emerging themes in asset allocation. The findings provide theoretical insights, practical implications, and directions for future research.

Suggested Citation

  • Soman, Siddhesh S. & Chirputkar, Abhijit & Punjani, Krunal K., 2026. "Loss aversion in investment: A bibliometric and network visualization analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 49(C).
    • Handle: RePEc:eee:beexfi:v:49:y:2026:i:c:s2214635026000171
    DOI: 10.1016/j.jbef.2026.101155
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2214635026000171
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jbef.2026.101155?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:beexfi:v:49:y:2026:i:c:s2214635026000171. 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: https://www.journals.elsevier.com/journal-of-behavioral-and-experimental-finance .

    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.