A Morningstar article posted last month discusses an “emerging body of research that suggests it is possible to successfully time exposure to factors like value, momentum, small size, quality and low volatility,” but adds that “a healthy dose of skepticism is in order.”
The article explains that while such factors reflect a strong long-term record, an effective timing strategy could help to offset the inevitable stretches of underperformance. However, it notes that much of the research to date is from “practitioners, rather than academia, who work for asset managers with a vested interest in bringing new products to the market.” Data mining is also a risk, the article argues, since there are “many variables researchers could have tested to find a predictive relationship that worked in sample but may not work out of sample.”
The article cites a recent paper from BlackRock that suggests the following four factor-timing signals work well, and perform even better together, offering an in-depth discussion of each:
- Economic regime indictors—the idea that different factors tend to do better at different points in the business cycle. The article reports that both BlackRock and Oppenheimer have found that economic regime indicators were the “strongest standalone predictors of factor performance in their back tests.” According to Morningstar, however, “in hindsight, it’s easy to identify each stage of the business cycles past, but it’s hard to know where we stand in real time.” This is further complicated, the article contends, by the increasing global nature of business that could serve to dilute the strong relationship between U.S. business cycles and factor performance.
- Valuations—The article says, “It is well-established that valuations can predict long-term asset returns…but that does not necessarily mean that valuations are an effective timing signal.”
- Momentum—This factor tends to revert to the mean in the short term, the article states, which could make it “one of the more promising candidates for use as a factor-timing signal. But while BlackRock found evidence that momentum-driven factor-timing works,” the author asserts, “I did not.”
- Dispersion—The concept of dispersion suggests that “the return to each factor should be greater when there is greater separation among stocks in the starting universe on the metrics used to construct the factor portfolio.” Morningstar argues, however, that the relationship only holds true for the value factor, and even then, research shows only a “moderate” correlation, suggesting that “dispersion is at best a weak factor-timing signal.”
The article concludes that the “jury is still out” when it comes to factor-timing given the complexity of the strategies and limited research on the topic, as well as the potential present for data mining. “While it isn’t prudent to write factor-timing off just yet,” it concludes, “it’s important to not lose sight of one of the main goals of multifactor investing: diversification.”
