- There is a significant positive relationship between alpha predictors and ﬂows; in other words, investors believe the predictors have value.
- There is a negative relationship between alpha predictors and fees. This relationship becomes increasingly negative out-of-sample. If predictors deteriorate, it isn’t because of rising fees.
- Using two different tests, the out-of-sample alphas fell between 78-87%. The out-of-sample performance of mutual fund alpha predictors is, at best, marginal.
- Publication of the paper on which each predictor is based leads to higher levels of arbitrage (as measured by aggregate short interest, aggregate share turnover and aggregate hedge fund asset size), which is then associated with smaller alpha spreads. Learning from a published academic study that a set of securities offers positive alpha induces greater investment (arbitrage) to those securities, which raises their prices and eliminates the alpha.
Another interesting finding was that in the period between the end of the data sample and publication of the finding on predictability (about four years on average), although predictability declined between about 30% and 40%, some predictability still existed. Predictability is no longer reliable after publication. The finding of a gradual decline in predictability allowed the authors to rule out the likelihood that the original findings resulted from data mining.
Jones and Mo noted that “whether academic ﬁnance research is useful or not in practice largely rests on whether or not its ﬁndings continue to hold out of sample.” Unfortunately, they reached the following conclusion: “Performance persistence, at least for equity funds, is mostly a phenomenon of an earlier era. The primary advice that one can give, again for equity funds, is to avoid high fees.”
Importantly, they added: “Poor out-of-sample performance is at least mostly the result of an overall trend towards greater market eﬃciency.” And finally, they offered this: “The obvious implication of our ﬁndings is that investment practitioners, who are known to use at least some of these measures to guide portfolio selection, may be engaging in a now-futile exercise.”