Are You Ignoring This Predictive Stock Indicator?
Everyone makes money investing by following a trend.
Whether your time horizon is minutes or months, a financial instrument must move in your favor to be profitable. It is that simple.
So finding an indicator to measure trend is critical to your success.
There’s a simple, quantitative indicator I use to determine the power of a trend that find stocks with the propensity for big moves. It’s called relative strength (RS).
Relative strength investing is pretty straightforward. It involves buying the best-performing stocks relative to all other stocks and holding them until their momentum changes course.
To most investors, especially those considered value investors, this strategy probably feels counterintuitive. After all, one of the first things you learn as an investor is to “buy low, sell high.”
But what we feel and what we can prove are two very different things. And there are decades of research that prove the predictive power of this indicator.
In the 1950s, George Chestnutt created one of the first newsletters using RS to rank stocks and industry groups. He also used RS to manage the successful American Investors Fund, which showed a cumulative return of 160% between 1958 and 1964 compared with 83% for the Dow.
In the late 1960s, Robert Levy published a study in the Journal of Finance discussing the direct correlation between the percentile ranking of RS and the performance of a stock over the next six months. He found that, in general, the higher a stock’s RS, the better its performance. It was groundbreaking for the time.
Levy planted a seed, and RS became the topic of numerous studies and papers over the ensuing decades. Once of the most famous academic studies on RS was completed in 1993 by Narasimhan Jegadeesh and Sheridan Titman.
Their oft-cited study, which covered the 24-year period from 1965 to 1989, clearly demonstrated a momentum-based strategy that bought past high-performing stocks and sold low-performing stocks made significantly abnormal positive returns. More specifically, they found that buying stocks based on high past six-month returns and holding them for the next six months beat the market by an average of 12% a year.
In 2013, Christopher Geczy and Mikhail Samonov published “212 Years of Price Momentum — The World’s Longest Backtest: 1801-2012.” It showed there was a positive and statistically significant correlation between momentum and stock performance going back to the start of the 19th century.
A primary reason RS works is that stocks produce skewed, excess positive and negative returns. In other words, they do not follow the standard bell-shaped performance curve, which is strikingly obvious when you overlay the two.
Perhaps the most striking difference is at the ends of each chart. The bar chart representing the 10-year returns for individual S&P 500 companies has “fat tails” — high bars at both ends of the graph — that show there are just as many, if not more, companies with extreme high and low returns as there are companies with average returns.
Based on the normal bell curve, this isn’t supposed to happen. Yet it does because stock returns are not normally distributed.
A stock’s RS can range from 0 (weakest) to 100 (strongest). I only consider buying stocks with a RS above 70 — and typically a good deal higher than that — when I recommend picks in my Alpha Trader service.
The table below contains the 20 best-performing stocks since the inception of the service in October 2013, along with their RS scores at the time we entered the position.
As you can see, these high-RS stocks continued to be winners for a good deal of time after we purchased them.
However, to be transparent, price momentum wasn’t the only thing that led me to these names. My picks are also based on the relative strength of a key fundamental measure. In other words, I look at how this fundamental measure for one company stacks up against every other publicly traded company, and rank it on a scale from 0 to 100.
When this rank is combined with price RS, it yields a score of 0 to 200 for every stock, and the predicative power of this combined indicator is unparalleled with anything I have come across in my trading career.
To this end, I am protective of the indicator, because the fewer people who know about it, the greater the edge. But I’ve agreed to temporarily open up my playbook and reveal exactly how this predictive analytics tool works to a few hundred readers. If you’d like to be one of them, you can gain access here.