IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-246-0_28.html

Risk-Return Analysis of Equity Portfolios: Comparison Between CAPM and Fama-French Three Factor Model

In: Proceedings of the 3rd International Conference on Economic Development and Business Culture (ICEDBC 2023)

Author

Listed:
  • Ziyan Tang

    (Sorbonne Université, La Faculté des Sciences & Ingénierie)

Abstract

This article presents an empirical study that examines the explanatory power of these two models in asset portfolio management. The study analyzes the daily returns of 16 prominent companies in 11 industries and the SPDR S&P 500 from January 2012 to December 2021, using ordinary least squares regression to estimate model parameters. The descriptive statistics reveal diverse trends and patterns of returns over the ten-year period. The results suggest that the CAPM model explains only a small portion of the variation in stock returns, with low R-squared values, while the beta coefficients are significant. In contrast, the F-F model provides a improved fit for the data, with higher R-squared values and significant SMB and HML factors for several stocks. The article highlights the importance of carefully considering the choice of model for stock return analysis and discusses the trade-off between model complexity and explanatory power. To ensure the robustness of the findings, the study conducts robustness checks using different time periods and portfolio construction methods. In general, the study adds to the literature by providing empirical evidence on the performance of the CAPM and Fama-French three-factor models in explaining the daily returns of selected stocks. The findings suggest that the Fama-French three-factor model is more suitable for explaining the variation in stock returns than the CAPM model, providing valuable insights for asset portfolio management practitioners.

Suggested Citation

  • Ziyan Tang, 2024. "Risk-Return Analysis of Equity Portfolios: Comparison Between CAPM and Fama-French Three Factor Model," Advances in Economics, Business and Management Research, in: Shehnaz Tehseen & Mohd Naseem Niaz Ahmad & Rafia Afroz (ed.), Proceedings of the 3rd International Conference on Economic Development and Business Culture (ICEDBC 2023), pages 227-237, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-246-0_28
    DOI: 10.2991/978-94-6463-246-0_28
    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:978-94-6463-246-0_28. 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.