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John Reese is chief executive officer of Validea.com and Validea Capital, the manager of an actively managed ETF. Globe Investor has a distribution agreement with Validea.ca, a premium Canadian stock screen service.
As investors, we've been taught that success comes from sticking to a few basic ideas: Cheap stocks outperform expensive ones; earnings quality matters; prices move on momentum. Market anomalies can be exploited for profit and have helped make so-called "smart beta" exchange-traded funds a hit in recent years.
But what if the widely followed investment factors underpinning these investments don't really function as expected?
The Wall Street Journal recently wrote about a new academic study that called into question hundreds of factors, including one identified by the Nobel Prize-winning economist Eugene Fama and Kenneth French, a professor of finance at Dartmouth College. Eight in 10 of the 447 factors examined in the study proved insignificant after rigorous testing, according to the study by Kewei Hou and Lu Zhang at Ohio State and Chen Xue at University of Cincinnati.
Thinly traded penny stocks, which make up more than half of publicly traded listings, distorted the significance of many factors, the authors wrote. Their study weighted stocks by market capitalization to eliminate this issue. Another part of the problem, the authors said, was the confirmation bias created by people mining the data in their quest for a new factor that would mint money.
Indeed, many of those who identified factors that produced historic returns were simply wrong, or their factors didn't behave as well as expected or stopped working after they publicized their findings. Following what has worked in the past doesn't always translate into future returns.
After applying their new testing, the Ohio State and University of Cincinnati researchers tossed out as insignificant a whole bunch of factors including a widely followed idea: that companies with high operating returns outperform.
Factor-based ETFs had about $1.34-trillion (U.S.) of assets as of mid-last year, an influential and growing corner of the investing market. The academics noted in their study that as factor investing rises in prominence, the financial press has questioned the reliability of the research underpinning it.
The authors of the study concluded that most claimed research findings in financial economics are likely false, particularly claims about trading friction. Some 93 per cent of anomalies in trading were shown to be insignificant by the study.
Some widely followed factors did pass their test, including value, momentum and corporate quality, but in many cases their effects weren't as big as expected.
Of course, investors chasing an idea all at once will tend to dampen the returns or eliminate them altogether. That is part of the problem with popular, or crowded, trades. Once an opportunity is exposed and investors dive in, the anomaly that made it a profitable trade disappears.
Over the past few years, factor investing, whether through strategic beta or other quantitative methods, have soared in popularity, which is why I think this new body of research is important for investors to think about and digest. More and more strategies are using factors, so knowing what to look for and understanding what you are buying will be important.
For instance, if you are an investor loading up on strategic beta approaches the first question might be, do you understand the factors at hand? Most factor-based approaches are looking at semi-popular valuation, quality, size, profitability and volatility metrics. Having an understanding about the "why" behind what a factor is trying to exploit is important because it will help you decide whether that's a risk you are willing to take with your money.
Any portfolio of stocks weighted to a particular factor also has the potential to show relative underperformance, and possibly for a long period of time. In an article in the AAII Journal from April of this year, Larry Swedroe, director of research at BAM Alliance, showed that almost every persistent investment factor can go through periods of 10, or even 20 years, of underperforming. No factor always works, and all of them have periods of poor relative returns.
At heart, I am a fundamentally based factor-oriented investor – although different than most. Over the past 20 years, I have been modelling and developing strategies based on the methodologies outlined by great investors, including Warren Buffett, Benjamin Graham and Peter Lynch. Their work in fundamental research led them to spectacular returns over time, and our computer-generated investment models track these same fundamental strategies that combine a series of investment criteria, or factors, together with the goal of selecting the very best stocks according to each model.
Over the next few years, I expect more factor-based approaches will come online and investors will be faced with even more investment options. The integrated factor approach, similar to the models I run, may be the next wave of development that takes place in the factor investing landscape.
The key to your success in utilizing factor-based investing won't be by following the latest investment fad or by investing in only one specific type of factor-based approach that has worked in the short term. Find a set of strategies built on sound fundamental factors and ones that don't cost you an arm and a leg. Understand that any time you are weighting one group of stocks, say value stocks or small caps, there is a potential for outperformance but there is also a potential for underperformance. Those investors who grasp the realities of investing alongside factors, even if their effectiveness is less than expected, can still come out very successful in the long term.