An empirical investigation of the Fama-French five-factor model

  • Received January 21, 2020;
    Accepted February 17, 2020;
    Published March 10, 2020
  • Author(s)
  • DOI
  • Article Info
    Volume 17 2020, Issue #1, pp. 143-155
  • Cited by
    7 articles

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This work is licensed under a Creative Commons Attribution 4.0 International License

The article deals with evaluating the securities portfolios in the process of transition from the one-factor CAPM model to the Fama-French five-factor model (FF5F). It identifies the advantages of the latter and discusses the controversial issues regarding its use by portfolio investors in different countries, given the anomalies inherent in asset pricing. Besides, the peculiarities of the statistical stratification method used in the FF5F model to group stock portfolios are revealed, and attention is drawn to some of the debating points of the five-factor model. The proposals have been formulated, which offer broader avenues for taking advantage of the FF5F model and increase the validity of the portfolio analysis results. The article also gives recommendations on modifying the approaches to analyzing small-size portfolios versus big-size portfolios based on partial changes in RMW and CMA factors, threshold proportions, and the use of STARR for asymmetric portfolios. The study substantiates the use of these approaches in testing the Fama-French five-factor model with portfolios composed of blue chips.

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    • Figure 1. Share allocation across big-size portfolios
    • Figure 2. Share allocation across small-size portfolios
    • Table 1. Changes in approaches when using the FF5F model
    • Table 2. Small-size and big-size portfolios according to the modified approach
    • Table 3. Multiple linear regression results
    • Table 4. Parameter estimates of the FF5F model
    • Table 5. Summary results
    • Table A1. ANOVA results for the BtM group portfolios
    • Table A2. ANOVA results for the RMW group portfolios
    • Table A3. ANOVA results for INV group portfolios
    • Conceptualization
      Oleksandr Paliienko, Svitlana Naumenkova
    • Data curation
      Oleksandr Paliienko
    • Formal Analysis
      Oleksandr Paliienko
    • Funding acquisition
      Oleksandr Paliienko, Svitlana Naumenkova, Svitlana Mishchenko
    • Investigation
      Oleksandr Paliienko, Svitlana Naumenkova
    • Visualization
      Oleksandr Paliienko
    • Project administration
      Svitlana Naumenkova
    • Methodology
      Svitlana Naumenkova, Svitlana Mishchenko
    • Resources
      Svitlana Naumenkova
    • Supervision
      Svitlana Naumenkova
    • Writing – original draft
      Svitlana Naumenkova, Svitlana Mishchenko
    • Writing – review & editing
      Svitlana Naumenkova, Svitlana Mishchenko