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Profitable momentum trading strategies for individual investors

Financial Markets and Portfolio Management volume 29, pages 85–113 (2015)Cite this article

Abstract

For nearly three decades, scientific studies have explored momentum investing strategies and observed stable excess returns in various financial markets. However, the trading strategies typically analyzed in such research are not accessible to individual investors due to short selling constraints, nor are they profitable due to high trading costs. Incorporating these constraints, we explore a simplified momentum trading strategy that only exploits excess returns from topside momentum for a small number of individual stocks. Building on US data from the New York Stock Exchange from July 1991 to December 2010, we analyze whether such a simplified momentum strategy outperforms the benchmark after factoring in realistic transaction costs and risks. We find that the strategy can indeed work for individual investors with initial investment amounts of at least $5,000. In further attempts to improve this practical trading strategy, we analyze an overlapping momentum trading strategy consisting of a more frequent trading of a smaller number of “winner” stocks. We find that increasing the trading frequency initially increases the risk-adjusted returns of these portfolios up to an optimal point, after which excessive transaction costs begin to dominate the scene. In a calibration study, we find that, depending on the initial investment amount of the portfolio, the optimal momentum trading frequency ranges from bi-yearly to monthly.

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Notes

  1. Although it is unclear how many investors have the option to short stocks in their account, Barber and Odean (2009) show that only 0.29 % of all individual investors took short positions in their portfolio.

  2. If a customer has shorted a stock, the clearing firm has to borrow it in order to deliver it to the buyer. When there is a huge demand to short a stock and there is a shortage of shares to borrow, holders of long stock can charge potentially very high rates to borrow stock.

  3. Margin requirements for small and microcap stocks are often much higher than the standard 30–50 % margin requirement.

  4. According to Jegadeesh and Titman (1993) and Grinblatt and Moskowitz (2004) findings, the abnormal performance of momentum trading is mainly due to the winner portfolio rather than the loser portfolio.

  5. As of June 16, 2011 the costs of trading a stock averaged $8.77 per trade at five of the largest US discount brokers (Fidelity $7.95, Schwab $8.95, Scott Trade $7, E-Trade $9.95, TD Ameritrade $9.99).

  6. On the first day of the holding period, investors can place “good ‘til canceled” stop loss or trailing stop orders for an amount or percentage loss that remain open up to 120 days.

  7. When a person or group of persons acquires beneficial ownership of more than 5 % of a voting class of a company’s equity securities registered under Section 12 of the Securities Exchange Act of 1934, they are required to file a Schedule 13D with the SEC. Viewed on 08.04.2014. https://doi.org/www.sec.gov/answers/sched13.htm.

  8. Companies that become delisted during the formation period were assigned a return of 0 %, which is consistent with Agyei-Ampomah (2007) and Siganos (2010). However, no delisted stocks made it into any of the winner portfolios during the analyzed period.

  9. As previously mentioned, investors can opt to fully reinvest dividends when buying each stock. This is a free service at most discount brokers in the United States.

  10. Investors in the United States can set up “buy at the close” and “sell at the close” orders for no additional charge.

  11. SEC website viewed 08.02.2012 https://doi.org/www.sec.gov/rules/final/33-7512f.htm#E12E2.

  12. The S&P 500 was used as the benchmark in this analysis as it the most commonly used benchmark for US stocks. We also ran the risk analysis against the Willshire 5000 Index, arguably a more comparable benchmark, and found similar results.

  13. Daniel and Moskowitz (2013) find that in extreme market environments, the loser portfolio provides a high premium, while the winner portfolio returns are minimal following large market declines.

  14. These assumptions are supported by the available bid/ask spread data from April 2006 to December 2010. During this time span, the average actual small cap stock posted a half bid/ask spread of 0.65 %, which is slightly less than our assumed average. The mid cap and large cap stocks posted significantly lower actual bid/ask half spreads, 0.19 and 0.10 %, respectively. As a robustness check, we ran the analysis with the actual spreads of the relevant stocks for this period and found no systematic difference from the results in our base scenario with fixed spreads for small, mid, and large caps.

  15. Section 31 of the Securities Exchange Act of 1934 states that, “self-regulatory organizations (SROs) such as the Financial Industry Regulatory Authority (FINRA) and all of the national securities exchanges (including the New York Stock Exchange) must pay transaction fees to the SEC based on the volume of securities sold on their markets. These fees recover the costs incurred by the government, including the SEC, for supervising and regulating the securities markets and securities professionals.” Viewed on 05.03.2014 on at https://doi.org/www.sec.gov/answers/sec31.htm.

  16. The top 50 stock portfolio with an initial amount of $5,000 underperformed the S&P 500 by 0.39 % per month.

  17. On the other hand, the investor could theoretically have a minimum of five different stocks in the portfolio at any given time, if the same top performers remain in the “winner portfolio” each quarter.

  18. This strategy would be compared to buying the top 20 performing stocks once a year.

  19. Again, replacing the S&P 500 with the Willshire 5000 as the benchmark makes no qualitative difference in the analysis.

  20. Abnormal Sharpe ratios for all portfolios are displayed in Table 9.

  21. These results are not shown, but are available on request.

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Acknowledgments

We would like to thank the anonymous referee for the valuable comments on an earlier draft of this paper. We are also indebted to the participants of the Finance Center Münster econometrics research seminar at the University of Münster for their helpful comments and insights.

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Authors and Affiliations

  1. Finance Center Münster, University of Münster, 48143, Münster, Germany

    Bryan Foltice & Thomas Langer

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  1. Bryan Foltice
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  2. Thomas Langer
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Correspondence to Bryan Foltice.

Appendix

Appendix

Table 7 Capital asset pricing model—monthly alpha “\(\alpha \)” (in %) by trading frequency
Full size table
Table 8 Fama-French three-factor model—monthly alpha “\(\alpha \)” (in %)
Full size table
Table 9 Abnormal sharpe ratios (compared to the S&P 500) all periods (1992–2010), based on initial portfolio amount and trading frequency
Full size table

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Foltice, B., Langer, T. Profitable momentum trading strategies for individual investors. Financ Mark Portf Manag 29, 85–113 (2015). https://doi.org/10.1007/s11408-015-0246-4

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Keywords

  • Momentum investing
  • Personal finance
  • Portfolio management

JEL Classification

  • G11
  • G12
  • G14