By: Tom Goodwin, senior research director
Investors’ interest in smart beta has increased significantly in recent years, with a specific focus on factor investing. That interest has helped drive an explosion of research on factors. But there can be too much of a good thing: “We now have a zoo of new factors,” declared Professor John Cochrane from the University of Chicago in 2011. Since this statement, the proliferation of factors purporting to deliver excess returns has only accelerated. In just the years between 2010 and 2012, 59 new factors were “discovered.” By some counts, there are now over 300 factors in academic and practitioner literature. But in a zoo of 300, how can anyone sort through the herd and find a group of factors that will generate reliable, sustainable long run premiums? This post outlines the process at FTSE Russell.
Factors are broad and historically persistent drivers of returns that are present in all stocks. Properly specified, they account for all risk except idiosyncratic risk. It is important to remember that all stocks, indexes and portfolios have embedded factor exposures – whether they’ve been formally identified or not. Researchers at FTSE Russell were determined to filter through all the factors found in academic literature to arrive at a group of only the most reliable factors that can reasonably be expected to persist well into the future. They used three criteria to conduct their analysis, as seen below.
Factors should be grounded in long and deep academic literature that has proven to be robust over a variety of definitions. One or two academic papers do not make the cut. There is a long-standing bias against publishing negative results in journals, so the absence of follow-on research often means the factor has not survived further testing.
We also determined that there are three types of intuitive economic rationale behind a successful factor. The first is rewarded risk. Certain factors have earned higher long-term returns as a reward for bearing greater risk. A second rationale encompasses behavioral biases. Not all investors are perfectly rational all the time, generating opportunities for those who can take a contrarian view. A third rationale embraces structural impediments such as market rules or restrictions that can make some investments off limits to certain investors, creating opportunities for others who can invest.
As I mentioned earlier, academic research is chock-full of the discovery of new factors, most of which are based on ephemeral anomalies that do not survive further scrutiny. Another track is our own empirical research. At FTSE Russell we insist that a proposed factor must be robust across all the major regions.
Additionally, we maintain that the surviving factors should be distinct from one another. This has led us to actually reduce the number of factors from eight to six over the past couple of years by observing that the live return patterns of two of the factors were very similar to two others.
At the end of this rigorous process we have six surviving factors. Our methodology “tilts” a starting set of weights, usually market capitalization or equal weights, toward the characteristics of that factor.
Attempting to data mine 300 potential factors that supposedly affect stock returns would only produce a strange and possibly random assortment of beasts in the zoo. At FTSE Russell, we believe that by applying the three criteria discussed above we have arrived at a manageable grouping of factors that display compelling results consistently over time.
For more information on our approach to factor exposures, read our research, Multi-factor indexes: The power of tilting.
 John Cochrane, “Presidential Address to the American Finance Association,” 2011.
 Campbell Harvey, Yan Liu, and Hequing Zhu, “…and the Cross Section of Expected Returns,” Duke University, 2015.
 The two removed are “Illiquidity,” which turned out to be highly correlated with the Size factor and “Residual Momentum,” which turned out to be highly correlated with the Momentum factor.
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