Connors Research Traders Journal (Volume 61): “Stacking” Historical Edges Improves Performance
In this Connors Research Traders Journal issue, we will present a few of the factors we utilize in building our Quantamental models and will be teaching in our upcoming course, Quantamentals – The Next Forefront of Trading and Investing.
The test results show that “stacking” multiple factors results in improved performance. Depending on how you combine these factors, this can lead to higher returns, lower volatility, and smaller drawdowns.
We will teach you how to incorporate these factors into complete and higher performing strategies, stacking the odds in your favor!
Let’s begin with known fundamental drivers of higher, risk-adjusted returns.
Fundamental Factors
Value – Value is the observation that “cheap” companies tend to outperform “expensive” companies over time.
Value is one of the oldest and most well established investing styles in history, used by such legendary investors as Warren Buffet and Joel Greenblatt – CEO of the highly successful hedge fund Gotham Capital.
These legendary investors realized that identifying and buying cheap companies will tend to lead to higher returns going forward.
One of the best value factors to apply when you’re building your strategies is EBIT/EV (Enterprise Value). Joel Greenblatt has done a brilliant job of statistically showing this both in his books and in his live investment returns.
In our Quanamentals course, we will teach you how to apply EBIT/EV, along with a multitude of additional ways to measure value for you to use that have historically produced the best results.
Quality – Quality is the observation that high-quality companies outperform low-quality companies over time.
We covered the quality factor in detail in our last issue of the Connors Research Traders Journal. We also presented an example of this factor in action in our “Quality Companies in an Uptrend” strategy.
In case you missed it, here are two previous issues that will further your knowledge.
Quantitative Factors
Momentum – Momentum is the observation that securities with strongest recent performance, usually over the last 3-12 months, tend to continue to outperform going forward.
This type of momentum is referred to as “cross-sectional” or “relative strength” momentum.
Look no further than Cliff Asness, the billionaire founder of the second-largest hedge fund in the world – AQR Capital Management. He had this to say in the introduction to his famous paper – Fact, Fiction and Momentum Investing:
“The existence of momentum is a well-established empirical fact. The return premium is evident in 212 years (yes, this is not a typo, two hundred and twelve years of data from 1801 to 2012) of U.S. equity data, dating back to the Victorian age in U.K equity data, in over 20 years of out-of-sample evidence from its original discovery, in 40 other countries, and in more than a dozen other asset classes.”
https://www.aqr.com/Insights/Research/Journal-Article/Fact-Fiction-and-Momentum-Investing
An example of applying momentum principles would be taking the 20 stocks from a 100 stock universe with the strongest 6-month total returns. We will teach you how to apply momentum principles in our upcoming course.
Low Volatility – The low volatility factor is the observation that stocks with lower historical volatility outperform stock with higher volatility, especially when view on a risk-adjusted return basis.
Below is an academic paper written by Andrea Frazzini and Lasse Pedersen (both principles at AQR and professors at NYU) showing this phenomenon.
https://pages.stern.nyu.edu/~lpederse/papers/BettingAgainstBeta.pdf
Technical Factors
Trend Following – Trend following is the observation that securities that have been trending higher tend to continue to do so, and securities that have been trending lower also tend to continue to do so.
This is often called “time series” momentum, “absolute” momentum, or simply trend following.
Many traditional technical analysis techniques can be utilized for trend following including simple or exponential moving averages, rate of change, and the slope of a linear regression line to name a few.
Below is a comprehensive study, again done by AQR, examining the performance of trend following since the year 1880:
Short-Term Mean Reversion – Short-Term Mean Reversion is the observations that securities that have had an outsized move, either up or down, tend to then revert to the mean over the short term.
Several technical indicators can be used to measure this, such as RSI, Stochastics or Bollinger Bands.
Connors Research has been at the forefront of short-term mean reversion research for decades. These results have held up out of sample and across multiple equity markets around the globe.
The edge provided by short-term mean reversion is especially strong on the long side (buying pullbacks) in equity markets in longer-term uptrends.
Conclusion and Next Steps
While each of these factors themselves has produced edges over time, stacking several of these edges together into a complete trading system will often increase the performance of your strategies.
If you’re interested in learning how to combine fundamental analysis with technical and quantitative analysis we invite you to listen to this recording Larry did on Monday. https://tradingmarkets.adobeconnect.com/pimrfsukaw0c/
Also, you’re invited to attend a live webinar we’re holding this Monday (Sold Out) and Thursday at 1 pm ET.
More Knowledge To Improve Your Trading
1. Quantamentals Webinar – Are you looking to learn more on how to apply Quantamentals to your trading and investing?
We’re conducting a 45-minute webinar on Monday, September 23 or Thursday, September 26 at 1 pm ET to teach you more about Quantamental Trading and to introduce you to the course we’ll be holding.
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Larry Connors & Chris Cain, CMT