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Detection of momentum effects using an index out-performance strategy

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  • N. Meade
  • J. E. Beasley

Abstract

The literature shows a substantial portion of momentum profits come from illiquid investments and short-selling, entailing abnormal transaction costs. Concentrating on liquid long-only investments, we investigate momentum using index out-performance portfolio selection (via a modified Sortino ratio) from universes defined by 11 S&P international equity indices. The probability a stock out-performed its index for n weeks, conditional on out-performance during the preceding year, successfully predicts momentum effects, allowing partition of the indices into those exhibiting strong, weak or no evidence of momentum. We find evidence of significant momentum profits (including reasonable transaction costs) in seven indices. Comparable conventional momentum analysis found significant profits for one index.

Suggested Citation

  • N. Meade & J. E. Beasley, 2011. "Detection of momentum effects using an index out-performance strategy," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 313-326.
    • Handle: RePEc:taf:quantf:v:11:y:2011:i:2:p:313-326
    DOI: 10.1080/14697680903460135
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    Citations

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    Cited by:

    1. Gianfranco Guastaroba & Renata Mansini & Wlodzimierz Ogryczak & M. Grazia Speranza, 2020. "Enhanced index tracking with CVaR-based ratio measures," Annals of Operations Research, Springer, vol. 292(2), pages 883-931, September.
    2. Renato Bruni & Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2012. "A New Lp Model For Enhanced Indexation," Departmental Working Papers of Economics - University 'Roma Tre' 0168, Department of Economics - University Roma Tre.
    3. Guastaroba, G. & Mansini, R. & Ogryczak, W. & Speranza, M.G., 2016. "Linear programming models based on Omega ratio for the Enhanced Index Tracking Problem," European Journal of Operational Research, Elsevier, vol. 251(3), pages 938-956.
    4. Renato Bruni & Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2013. "No arbitrage and a linear portfolio selection model," Economics Bulletin, AccessEcon, vol. 33(2), pages 1247-1258.
    5. Ruchika Sehgal & Aparna Mehra, 2023. "Quantile Regression Based Enhanced Indexing with Portfolio Rebalancing," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(3), pages 721-742, September.
    6. Li, Helong & Huang, Qin & Wu, Baiyi, 2021. "Improving the naive diversification: An enhanced indexation approach," Finance Research Letters, Elsevier, vol. 39(C).
    7. Ruchika Sehgal & Aparna Mehra, 2019. "Enhanced indexing using weighted conditional value at risk," Annals of Operations Research, Springer, vol. 280(1), pages 211-240, September.
    8. Guastaroba, G. & Speranza, M.G., 2012. "Kernel Search: An application to the index tracking problem," European Journal of Operational Research, Elsevier, vol. 217(1), pages 54-68.
    9. Valle, C.A. & Meade, N. & Beasley, J.E., 2014. "Absolute return portfolios," Omega, Elsevier, vol. 45(C), pages 20-41.
    10. H Mezali & J E Beasley, 2013. "Quantile regression for index tracking and enhanced indexation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(11), pages 1676-1692, November.

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