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In search of momentum profits: are they illusory?

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  • Ivelina Pavlova
  • A. M. Parhizgari

Abstract

We test whether a Genetic Algorithm (GA) can find profitable investment strategies based on prior stock returns and earnings surprises. We add to the argument whether momentum investing profits are a statistical illusion. The performance of the optimized momentum portfolios is evaluated before and after trading costs, during different time periods, over two market states, and after adjusting for risk. The GA optimization improves the annual returns of the momentum strategies by 2% to 6%. After considering transaction costs, both price and earnings momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely in the 'up' markets for a portfolio long in prior winners only.

Suggested Citation

  • Ivelina Pavlova & A. M. Parhizgari, 2011. "In search of momentum profits: are they illusory?," Applied Financial Economics, Taylor & Francis Journals, vol. 21(21), pages 1617-1639.
    • Handle: RePEc:taf:apfiec:v:21:y:2011:i:21:p:1617-1639
    DOI: 10.1080/09603107.2011.589804
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    Cited by:

    1. Luís Lobato Macedo & Pedro Godinho & Maria João Alves, 2020. "A Comparative Study of Technical Trading Strategies Using a Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 349-381, January.
    2. repec:grz:wpsses:2020-03 is not listed on IDEAS
    3. Fink, Josef, 2021. "A review of the Post-Earnings-Announcement Drift," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    4. repec:grz:wpsses:2021-01 is not listed on IDEAS
    5. Fink, Josef & Palan, Stefan & Theissen, Erik, 2020. "Earnings autocorrelation and the post-earnings-announcement drift: Experimental evidence," CFR Working Papers 20-10, University of Cologne, Centre for Financial Research (CFR).
    6. repec:grz:wpsses:2020-04 is not listed on IDEAS

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