1. Arnott et al. (2016) and Arnott, Beck, and Kalesnik (2016a, 2016b).
2. The Morningstar Direct Mutual Fund Database includes liquidated or merged funds. We focus on institutional, no-load, and A-share classes because they are the most relevant to retail and institutional investors. These three classes differ in fee structures and represent investment returns to different types of investors. Inclusion of all three share classes enriches the sample. Also, the inclusion of multiple share classes should not bias the slope of the second-stage regression coefficients (the methodology is described in the Appendix) nor therefore our conclusions based on our findings.
3. John Cochrane coined this marvelous expression “factor zoo.” Harvey et al. (2015) shows that over 316 factors were published by the end of 2012, with over 90% published since 2000. In conversations with Cam, he suggests that all 316 factors exhibited positive alpha; almost all showed statistical significance, net of the size and value factors; and none—zero—were tested to determine if the factor had enjoyed a tailwind of rising relative valuations, which may have driven part or all of its historical efficacy.
4. Of course, if the factors did not have positive performance, they would not have become popular!
5. Shumway and Warther (1999) show that delisted stocks’ returns recorded in the regular databases are much larger than what an investor would be able to earn when transacting in the over-the-counter market, where the stocks are traded after being delisted.
6. A long-lasting debate in the academic literature is whether the better driver of expected returns is risk exposure or stock characteristics. Fama and French (1993) argue that returns are driven by risk exposures, whereas Lakonishok, Shleifer, and Vishny (1994) argue that mispricing and characteristics may be the stronger driver. Daniel and Titman (1997) conduct a test to compare the two hypotheses and conclude that stock characteristics may be the better driver. More recent research Berk (2000) and Davis, Fama, and French (2000) find support that risk exposures are more important, while Daniel, Titman, and Wei (2001) and Chaves et al. (2013) find evidence in support of stock characteristics.
7. In the early 1970s, researchers such as Haugen and Heins (1975) and Black, Jensen, and Scholes (1972) found empirical evidence that variation in market beta risk is not matched with compensation for risk; this is known as a flat or sometimes inverted security market line.
8. The value effect was first documented by Basu (1977). The two most accepted explanations for the value effect are risk based, as proposed by Fama and French (1992), and behavioral, as proposed by Lakonishok, Shleifer, and Vishny (1994).
9. The apparent 0.1 percentage-point difference is due to rounding.
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———. 2016b. “Timing ‘Smart Beta’ Strategies? Of Course! Buy Low, Sell High!” Research Affiliates (September).
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