IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-748-9_47.html

Empirical Study on the Impact of Liquidity Factor Turnover Rate on Stock Returns: Based on CAPM and Fama-French Models

In: Proceedings of the 2025 International Conference on Financial Risk and Investment Management (ICFRIM 2025)

Author

Listed:
  • Sijie Guo

    (Guangdong University of Finance, School of Finance and Investment)

Abstract

This study aims to investigate whether the inclusion of turnover rate (HSL) as a liquidity factor can enhance the explanatory power of the Capital Asset Pricing Model (CAPM) and the Fama-French three-factor model (FF3) in predicting stock returns. This issue is of critical importance in academic research, as it could reveal the impact of market microstructure on asset pricing and provide a new perspective for investment decisions. The author use regression analysis and stock data from six technology companies (Apple, Microsoft, Amazon, Alphabet, Tesla, Plug Power) between June 2016 and October 2020, including excess returns, market excess returns, company size, book-to-market ratio, and turnover rate. The results show that the inclusion of HSL significantly increases the R-squared value of the models, indicating that turnover rate is an important factor influencing stock returns. This finding has practical implications for investors considering liquidity indicators when evaluating stocks and provides a theoretical basis for regulatory authorities to monitor market manipulation behavior.

Suggested Citation

  • Sijie Guo, 2025. "Empirical Study on the Impact of Liquidity Factor Turnover Rate on Stock Returns: Based on CAPM and Fama-French Models," Advances in Economics, Business and Management Research, in: Maizaitulaidawati Md Husin (ed.), Proceedings of the 2025 International Conference on Financial Risk and Investment Management (ICFRIM 2025), pages 425-433, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-748-9_47
    DOI: 10.2991/978-94-6463-748-9_47
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:advbcp:978-94-6463-748-9_47. 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.