1. At the end of 2017, funds categorized by Morningstar Direct data as strategic beta funds held about US$767 billion in assets under management. This amount represented an annualized increase of about 20% over the previous five years.
2. Barberis and Thaler (2003) and Barber and Odean (2013), among others, survey the literature on investor behavior and discuss the biases and cognitive limitations that hinder investor decision making. Frazzini (2006) shows not only individual investors suffer from these biases, so do mutual fund managers, who have a tendency to ride losses and realize gains in a pattern known as the disposition effect.
3. See, for example, Arnott et al. (2018) and Ehsani and Linnainmaa (2018).
4. The average factor delivers about 60% less alpha after its “discovery” has been written about and published in the academic literature than before that time (Arnott et al., 2016). Thus, we should expect considerably less alpha with considerably less reliability than backtests would suggest. This does not make factor investing a bad idea. After all, what strategies have ever been reliable on live assets, on an institutional scale, to remotely the extent that factor strategy backtests have been? Investors need merely rein in expectations and recognize that the risk of three-year and five-year periods of underperformance should be expected from time to time.
5. We use full-period volatility for the standardization. Because this information is ex ante unknown to an investor, a practical realization targeting 5% volatility and using only past realizations may result in a significant underestimation of risk and may result in even worse drawdown realizations than we present in this article.
6. The risk-based explanation was suggested, among others, by Fama and French (1992). Campbell, Polk, and Vuolteenaho (2010) show that value stocks react more strongly to the so-called cash-flow shocks that affect consumption level and which tend to be more persistent, whereas growth stocks tend to react more strongly to so-called discount-rate shocks which tend to be more transitory. Mispricing is proposed by Lakonishok, Shleifer, and Vishny (1994) as the main explanation for the value effect.
7. Evidence, such as the findings of Barberis, Schleifer, and Vishny (1998), suggests that the slow reaction to news, both positive and negative, could be due to a conservativism bias in human information processing. Such a bias could explain investors’ initial underreaction when surprise announcements are made as well as their overreaction in continuing to push a stock’s price higher or lower following the direction of the momentum.
8. We do not control for multiple testing in our statistical tests. To do so, the cut-off values to reject the null hypotheses would need to be more stringent, but given that the low-beta effect is one of the earliest factor premiums discovered, the multiple testing concerns are probably less severe than for the other factors.
9. Berk (1995) draws a connection between the size and value effects through the same argument. If the measure of fundamental value, such as the book value of equity, positively correlates with differences in expected cash flows, then a valuation ratio such as the book-to-market ratio may predict returns better than size.
10. Kinnel (2005) and Hsu, Myers, and Whitby (2016) demonstrate that investors’ time-weighted returns are significantly lower than their dollar-weighted returns.
11. We assume normal distribution at all frequencies, which would follow from an assumption of normal distribution on the monthly frequency and no serial correlation in the returns.
12. We use a 55-year period because it corresponds with the time period over which we have return characteristics for most factors in the US market. Likewise, it roughly corresponds to the length of period over which an individual may have an investing experience, starting from when they enter the labor force and may begin saving, through the portion of their retirement when they are divesting.
13. The magnitude of drawdowns scales with the level of risk and would be larger if the tracking-error level chosen was higher.
14. Unlike the magnitude of underperformance, the duration of a drawdown does not scale up or down with the active risk.
15. Realized drawdowns for the long-only factor strategies may yield significantly different drawdown characteristics; for some factors, the outcomes may be significantly milder. Unless we have a theory for why the top, middle, and bottom part of the factor may behave differently, using the worst realized outcome may be the most prudent course.
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