This article is part of a regular series of thought leadership pieces from some of the more influential ETF strategists in the money management industry. Today's article features Wesley Gray, chief executive officer and chief investment officer of Alpha Architect based in Broomall, Pennsylvania.
Factor investing, an approach that systematically tilts a portfolio based on the characteristics of the underlying stocks, is a hot topic. Common factor approaches include value, momentum, quality, yield and low-volatility tilts.
These concepts lay the foundation for much of the innovation in the ETF space, which have generically been deemed “smart beta.”
What belies the belief in factor investing? In short, the evidence. But what if all this so-called evidence was bunk? We address in this piece why investors should be skeptics when it comes to the performance of evidence-based investing approaches, which are often not the result of a sustainable investment process, but merely a result of data-mining.
A Short History On Factor Investing
The evidence for the different investment factors extends across many decades and has generated a healthy debate among academic researchers. But while the ivory tower and sophisticated institutional investors spent much of their time chatting among themselves, factor investing finally made it to the mainstream via a 1992 article titled, “The Cross-Section of Expected Returns,” by Eugene Fama and Kenneth French.
The article formalized the anecdotal stories from stock-pickers that value stocks and small-cap stocks paved a way to earn higher excess returns. Of course, the flip side of the higher expected returns was presumed to be higher expected risk. Fama and French’s work has become the foundation for Dimensional Fund Advisors, which formed portfolios focused on cheap small-cap stocks that were accessible for retail investors via the financial advisor channel.
The 1992 Fama and French article was literally one paper among a sea of academic publications that have proclaimed victory for a variety of investing factors. In fact, professors at Duke, Texas A&M and Oklahoma published a recent paper in the Review of Financial Studies that investigates 313 studies that identify potential “factors” that can generate benefits for a stock portfolio. The researchers sum up their work as follows:
“Hundreds of papers and factors attempt to explain the cross-section of expected returns ... given this extensive data mining … we argue that most claimed research findings in financial economics are likely false.”
That’s a pretty strong statement from the professors, as well as a potential warning signal for investors who blindly follow the so-called evidence, which justifies many factor investing approaches might not be advisable.
But it gets worse …