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Style Investing with Machine Learning

Author

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  • Philipp Kallerhoff

Abstract

This paper applies machine learning techniques to style investing. Support Vector Regression is applied to multi-factor investing based on momentum, dividend, quality, volatility and growth. The results show that Support Vector Regression selects stocks consistently with a higher efficiency ratio than a broad market investment and outperforms linear regression methods. The methods are applied to global stocks in the MSCI World index between 1996 and 2016. The behavior of both models is analyzed for economic sectors and over time. Interestingly, factors like low-volatility and momentum contribute both positively and negatively in some economic sectors and certain time periods.

Suggested Citation

  • Philipp Kallerhoff, 2016. "Style Investing with Machine Learning," International Business Research, Canadian Center of Science and Education, vol. 9(12), pages 13-22, December.
    • Handle: RePEc:ibn:ibrjnl:v:9:y:2016:i:12:p:13-22
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    References listed on IDEAS

    as
    1. 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.
    2. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    3. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    4. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    hedge funds; machine learning; factor models; style investing;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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