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The Fama 3 and Fama 5 factor models under a machine learning framework

Author

Listed:
  • Periklis Gogas

    (Department of Economics, Democritus University of Thrace, Greece; Rimini Centre for Economic Analysis)

  • Theofilos Papadimitriou

    (Department of Economics, Democritus University of Thrace, Greece)

  • Dimitrios Karagkiozis

    (Department of Economics, Democritus University of Thrace, Greece)

Abstract

We examine four empirical models which are popular in money and stock markets world. These models are Fama – French 3 & 5 factors model, the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT) model. These tools are intensively used by investors and market professionals as an important part of the investment decision process and for the evaluation of the applied investment strategies. The last years, several surveys and studies have done, and various methodologies were implemented to evaluate the effectiveness of these four models. The methodological approach of the current thesis focuses on the Support Vector Regression (SVR). This method is running in comparison with the Ordinary Least Squares linear regression.

Suggested Citation

  • Periklis Gogas & Theofilos Papadimitriou & Dimitrios Karagkiozis, 2018. "The Fama 3 and Fama 5 factor models under a machine learning framework," Working Paper series 18-05, Rimini Centre for Economic Analysis.
    • Handle: RePEc:rim:rimwps:18-05
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    References listed on IDEAS

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    1. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
    2. Fama, Eugene F & French, Kenneth R, 1996. "The CAPM Is Wanted, Dead or Alive," Journal of Finance, American Finance Association, vol. 51(5), pages 1947-1958, December.
    3. Eugene F. Fama & Kenneth R. French, 2004. "The Capital Asset Pricing Model: Theory and Evidence," Journal of Economic Perspectives, American Economic Association, vol. 18(3), pages 25-46, Summer.
    4. Plakandaras, Vasilios & Papadimitriou, Theophilos & Gogas, Periklis & Diamantaras, Konstantinos, 2015. "Market sentiment and exchange rate directional forecasting," Algorithmic Finance, IOS Press, vol. 4(1-2), pages 69-79.
    5. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    6. Bartholdy, Jan & Peare, Paula, 2005. "Estimation of expected return: CAPM vs. Fama and French," International Review of Financial Analysis, Elsevier, vol. 14(4), pages 407-427.
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    Cited by:

    1. Pedro M. Mirete-Ferrer & Alberto Garcia-Garcia & Juan Samuel Baixauli-Soler & Maria A. Prats, 2022. "A Review on Machine Learning for Asset Management," Risks, MDPI, vol. 10(4), pages 1-46, April.
    2. David Mayer-Foulkes, 2018. "Efficient Urbanization for Mexican Development," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(10), pages 1-1, October.

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    More about this item

    Keywords

    stock markets; stock returns; machine learning; support vector regression;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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