Investors can improve their investment outcomes by taking two straightforward, but sometimes, challenging steps: 1) truly believe in the ability of the style to deliver return in the long run before investing in the style, and 2) understand that the journey to the end of their investment horizon may be bumpy and may take some unexpected turns along the way, but staying the course will get them—at long last—where they want to be financially.
Step 1. Believing in the Style
If smart beta is solely about investing in a style, the client service conversation, suddenly free from the need to convince a client of outsmarting alpha, shifts to a more constructive starting place. The easiest way to eliminate performance chasing is not to engage in a conversation about performance!!
Instead, focus on the style.
To achieve a better dollar-weighted outcome, we should begin, as our colleague Cam Harvey states, by establishing the economic plausibility of the strategy. In other words, we must encourage philosophical buy-in of the factor or style. If the strategy is expected to win with a systematic and transparent approach, someone must be losing. Who’s on the other side of the trade? What’s their motivation, and why do we expect it to continue? After all, smart beta rules are transparent and easily accessible.
The investment beliefs that Research Affiliates espouses make two assertions consistent with investors who are willing to be long-term losers. First, investor preferences are broader than risk and return. The safety of the herd, a preference for investing in big winners (i.e., positive skew), the psychic benefit of realizing gains, the inclination toward comfortable investing, and other motivations all affect investor choices. Second, lack of conviction and/or governance constraints restrict investors’ ability to exploit long-term value. In other words, some long-term winning strategies simply cannot be implemented due to imposed short-termism.
Establishing and re-establishing the belief in style is critical for client success in smart beta. As we’ll see shortly, smart beta is no silver bullet. It can and will underperform, often for long stretches. Indeed, we find when examining the longer-term histories of the 29 smart beta strategies tracked in our SBI webtool that 14% of the time they are underperforming over rolling 10-year stretches. And this is the case for the strategies with promising backtests!
With a sound and ideally straightforward theory, we can then look at longer-term data to substantiate the robustness of the strategy across regions and factor definitions. We can compare the results to the academic literature for further validation. And we shouldn’t just seek one or two studies, but many. The more independent confirmations from leading sources, the more likely we have a style worth believing in. As Beck et al. (2016, p. 59) stated:
Factors should be grounded in a long and deep academic literature. Taking advantage of academic research that is peer reviewed and generally free from undisclosed conflicts of interest is one of the best strategies for investors. A long literature debating the existence and persistence of a factor strategy, including rigorous attempts to debunk it, is critical to validating a factor. A factor strategy that does not attract follow-on research usually means that the factor has not survived academic scrutiny.
The entirety of the exercise from theory to data to academic support establishes a belief, a Northstar so to speak, that the strategy will deliver.
After we gain conviction for the theoretical underpinning of why a strategy is expected to produce robust results, we need to think practically: Can these results be captured in the real world of trading costs and other frictions? As Yogi Berra’s quip aptly reminds us: “In theory, there is no difference between theory and practice. In practice, there is.” Different and often seemingly small elements of product design, such as portfolio concentration, turnover, liquidity, size, and number of holdings, can lead to substantial differences in expected transaction costs. We therefore must assess how transaction costs will impact the theoretical expected return premium.
Step 2. Understanding the Journey
Most of the return conversation with prospective smart beta clients centers on expected return—not dissimilar to the traditional servicing exhibit that shows trailing 1-, 3-, 5-, and (if available) 10-year annualized manager (time-weighted) returns versus a benchmark. But the expected return is just the midpoint in a range. With shorter periods the range can be massive as the style or risk factor moves from being in favor to out of favor. Underperformance will happen. Investors need to be prepared ahead of time.
A better-outcome client review will spend just as much time on the range of returns as the expected. Here’s where smart beta has another critical advantage. Due to the systematic nature of these strategies, through backtesting across multiple factor definitions and geographies, we can gain substantial insight into not only the expected long-term excess return, but the range of outcomes along the way. Of course, we’ll never be able to estimate the full range of outcomes, but we can at least start with the “known unknowns.”
A focus on how the return range narrows with longer horizons can encourage two mindsets, both equally important for better dollar-weighted returns. First, asset managers can communicate the rather wide range of results, which will inevitably have periods (sometimes sustained) of well-below benchmark performance. All performance over the short term will be noisy relative to the long-term expectations of the smart beta strategy. Second, asset managers can help clients appreciate that by extending their holding period, the impact of underperformance on their overall return will be lessened, thereby establishing a mindset of long-termism rather than short-termism. As Charlie Munger said, “The big money is not in the buying and selling … but in the waiting.”
Thus, periods of exceptionally strong performance can be interpreted as an above-normal windfall, ripe for a rebalancing opportunity, and vice versa. Admittedly, easier said than done. A client viewing wonderful trailing one-, three- and five-year returns will have a hard time pulling the sell trigger. Such look-back performance creates an illusion of consistently earned excess return that’s all too easy to extrapolate into the future. The path of least resistance for all of us in the asset manager food chain is to favor recent winners and de-emphasize recent losers. Old habits, especially those that are hardwired, die hard. Mean reversion, however, makes that path of least resistance a losing strategy.