IDEAS home Printed from https://ideas.repec.org/a/eee/riibaf/v73y2025ipbs0275531924004318.html
   My bibliography  Save this article

The COVID-19 pandemic and feedback trading dynamics: Unveiling global patterns

Author

Listed:
  • Tang, Chia-Hsien
  • Lee, Yen-Hsien
  • Chen, Chan-Shin
  • Huang, Ya-Ling

Abstract

This study analyzes how the COVID-19 pandemic impacted stock markets worldwide using the COVID-19 Global Fear Index (GFI) devised by Salisu and Akanni (2020). We examine feedback trading behaviors in stock indices across 70 countries, revealing a complex relationship between pandemic-sentiment and feedback trading. Our study finds that GFI primarily motivates negative feedback trading in many developed countries, particularly those in higher latitudes, while the relationship between pandemic-sentiment and feedback trading is complex and varies across regions. Notably, China and India deviate from these patterns, exhibiting no significant feedback trading effects. These results highlight how regional differences shape financial market responses to the COVID-19 crisis. This analysis offers valuable insights into the pandemic's nuanced impact on global financial markets, emphasizing the distinct reactions across diverse geographic regions.

Suggested Citation

  • Tang, Chia-Hsien & Lee, Yen-Hsien & Chen, Chan-Shin & Huang, Ya-Ling, 2025. "The COVID-19 pandemic and feedback trading dynamics: Unveiling global patterns," Research in International Business and Finance, Elsevier, vol. 73(PB).
  • Handle: RePEc:eee:riibaf:v:73:y:2025:i:pb:s0275531924004318
    DOI: 10.1016/j.ribaf.2024.102638
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0275531924004318
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ribaf.2024.102638?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

    COVID-19; Positive (negative) feedback trading; Global and local fear index;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

    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:riibaf:v:73:y:2025:i:pb:s0275531924004318. 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/ribaf .

    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.