An article in the May issue of the Chicago Booth Review discusses the ongoing discovery of investable factors, which it says are “being discovered almost as quickly as they can be packaged and sold to the waiting public.”
But findings from a recent study beg the question: “Are there really 300 separate characteristics associated with higher asset returns, or only a handful of things really driving stock prices?” The study– conducted by Guanhao Feng and Dacheng Xiu (both of Booth) and Yale’s Stefano Giglio—involved collecting and analyzing over 100 of them, and the results suggest that perhaps the hunt for factors has gone too far.
The article provides a brief chronology of factor investing (beginning with the capital asset pricing model developed in the early 1990s, followed by the three-factor model published by the Fama-French team in 1992) noting that the rush to develop new factors continues. It quotes Eugene Fama: “You have thousands of academics in this area, all of whom need to come up with papers to publish, so the door is wide open.”
But it may be time to “partially close this door, or at least make sure researchers test new factors vigorously,” the article argues, adding that many of the newer factor discoveries may be subsets of already-discovered factors. While the study researchers are not suggesting that there are “fake” factors being used, they argue that many of the new ones are “redundant and are the result of somewhat arbitrary choices of existing factors as controls—one form of abusive data mining.”