01 Mar Learning From "Profitable Momentum Trading Strategies for Individual Investors"

After factoring in transaction costs and risks, the highest returns and monthly alphas are obtained by buying the top five to eight of the top performing stocks of the previous six-month holding period.

In this article, Absolute Momentum will be used interchangeably with trend following or time series momentum. Relative Momentum will be used interchangeably with cross-sectional momentum or relative strength.

The paper explores a simplified momentum trading strategy that only exploits excess returns from topside momentum for a small number of individual stocks. This is suitable for individual investors with a relatively smaller initial investment amount.

The trading methodology is as such:

Each stock would be ranked by its formation period (six-month) performance, from best to worst. After ranking each stock, equally weighted portfolios were formed that contained the best (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50) performing stocks in the formation period. established a 12-month holding period and bought each stock at the closing price on the first trading day of the period. At the end of the 12-month holding period, all stocks were sold at the closing price on the last trading day of the period. For example, the holding period would begin at the closing price on August 1 and all stocks would be held until the closing price on July 31 the following year (given that both are valid trading days). The overall return of each time period was calculated by averaging the performance of all stocks in each portfolio.

The results in “Table 1” of the paper (reproduced below) show that:

All portfolios, on average, outperform the S&P 500 benchmark by 0.52%-2.44% per month. Overall portfolio performance gradually increases until it reaches the highest performance, 3.07% per month, in the top seven stock portfolio. The returns then decrease as the portfolio holds more stocks.  Gross returns were divided into two equal sub-periods, January 1992 to December 2000 and January 2001 to December 2009. Each sub-period appears to consistently outperform the S&P 500 in both categories.

Source: Profitable Momentum Trading Strategies for Individual Investors

The paper then explores the impact of trading frequency on the strategy. In addition to the once per year strategy, the paper explores bi-yearly, tri-yearly, quarterly, bi-monthly, and monthly trading frequencies in order to observe the effects of each trading frequency on their respective portfolios.

For example, for a $50,000 portfolio on a quarterly frequency, hypothetically this investor would initially buy $12,500 ($2,500 of each of the top five performing stocks of the previous six months) on January 1 and hold these stocks until December 31. He would repeat the process on April 1, July 1, and October 1 and hold the respective portfolios for 12 months (thus selling on March 31, June 30, and September 30, respectively). In the following year, he would sell each portfolio at the end of each quarter and use the proceeds to buy the new portfolio. Once the strategy is fully established, this individual will have up to 20 different stocks in his portfolio at any given time.

The paper finds 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.

The paper finds evidence that buying the smaller overlapping portfolios consisting of the top five to eight best performers of the six-month formation period on a bi-yearly to monthly basis results in larger risk-adjusted returns compared to buying a larger portfolio consisting of 20-50 stocks one time per year

Research Paper: Profitable Momentum Trading Strategies for Individual Investors

Authors: Bryan Foltice, Thomas Langer

Organisation: Finance Center Münster, University of Münster