Relative strength strategies are compelling for a number of reasons. First, intuitively it make sense that buying and holding winners and selling losers should be an effective way to navigate the markets. Second, relative strength has been shown time and time again by practitioners and academic studies to be a viable method of beating the market over time. Surely, one of the most effective ways to help investors to commit to a relative strength strategy for the long-term is to share with them some of the body of research on relative strength investing.
Among the relative strength factors that we test is a nonproprietary 52-week return model. This model ranks a universe of securities by their trailing 52-week performance and then divides them into percentile ranks. The investment universe for this model is the S&P 900, which consists of U.S. mid and large cap stocks. The testing period is the nearly 14-year period from 12/31/1995 - 9/30/2009. For this test, we defined a target number of holdings for the portfolio, a buy threshold, and a sell threshold. The buy threshold was the minimum percentile score a stock would need to make it eligible for inclusion in the portfolio. If we set this parameter at 90, for example, only stocks in the top declile (or those with a percentile rank above 90) were eligible for inclusion in the portfolio. The sell threshold was the level at which a stock was automatically sold out of the portfolio and replaced with a stronger stock. We used a buy threshold to define a basket of eligible stocks and then picked one stock at random from the basket. Each security was reviewed weekly and not sold unless its rank fell below the predefined sell threshold. We used this methodology to run 100 simulations for the model with the given parameters. These Monte Carlo simulations also demonstrate the robustness of relative strength because they show the returns are not clustered in a small number of stocks.
Results of this test are shown below:
(Click to Enlarge)
The green dot is the return of the S&P 500 in that given year. The red bar is the average return of the 100 simulations of the relative strength model. The range of returns of each of the trials is also shown.
The percentage of trials that resulted in outperformance in any given year is shown in the table below.
The table below shows the results of all of the simulations over the entire test period.
For comparison, the cumulative return of the S&P 500 over this time period was 71.62% while the average relative strength simulation over the same time was 211.16%. Even the single worst trial for the relative strength model generated superior returns over the that period of time.
Conclusions
- The Monte Carlo methodology is evidence of robustness of the process, since all 100 trials led to outperformance over the entire test period.
- Year-to-year there is large dispersion in the performance of this relative strength model compared to the S&P 500.
- With the exception of 2007, the last couple years have not been a good environment for relative strength.
- If you believe, as we do, that winning investment styles move in and out of favor over time then you may wish take advantage of the opportunity to add to a long-term winning strategy while it is out of favor.
