A growing variety of alternative beta strategies have come to market in recent years. Many of these strategies are purported to be “Smart Betas.” Are they? What makes them smart?
According to Towers Watson (2013), a leading global investment-consulting firm, “Smart beta is simply about trying to identify good investment ideas that can be structured better... smart beta strategies should be simple, low cost, transparent and systematic.” This straightforward definition indicates what investors ought to expect of a “smart beta.” Our research suggests that many alternative beta strategies fall short of this definition. Some are overly complex and opaque in the source of their value added. Others will incur unnecessary implementation costs. Many alternative beta strategies don’t seem so smart.
Sources of Value Added
A growing body of research shows that non-price-weighted strategies add value over their capitalization-weighted benchmarks.1 The results show surprisingly consistent simulated value added for the most popular alternative beta strategies.
In an article published in the Journal of Portfolio Management (JPM), Arnott, Hsu, Kalesnik, and Tindall (2013) extend the research to a set of “sensible investment beliefs.” The authors demonstrate that sensible investment beliefs, when translated into portfolio-weighting strategies, result in outperformance against the cap-weighted benchmark index—and so do the arguably nonsensical inverses2 of those weighting strategies! The authors go on to show that even random weighting, as by Malkiel’s monkey,3 consistently outperforms a cap-weighted index.
How can seemingly sensible weighting strategies, the inverses of those strategies, and Malkiel’s monkey throwing darts all consistently add value? The authors observe that all of these strategies involve rebalancing the securities in the portfolio to target weights calculated without reference to market prices. This rebalancing involves a “contra-trade against the market’s price changes at each rebalancing,” which “necessarily results in value and size tilts, regardless of the weighting method chosen.”
Arnott et al. (2013) conclude that value and size factor exposures arise naturally in non-price-weighted strategies and constitute the main source of their return advantage. Revealingly, the authors find “that the investment beliefs upon which many investment strategies are ostensibly based play little or no role in their outperformance…. This does not mean that these strategies’ outperformance is suspect. Rather, as it turns out, these investment beliefs work because they introduce, often unintentionally, value and small cap tilts into the portfolio.” With these results in mind, some alternative beta strategies appear to fail the first part of the objective: efficient capture of a sound investment idea. These strategies add value, like Malkiel’s monkey, simply because they rebalance to non-price weights.
Small Company Tilts
When assessing whether an alternative beta is smart, investors should examine not just average simulated returns, but also risk. Does an alternative beta strategy subject an investor to greater risk relative to the cap-weighted market portfolio? In many cases, they do because of their small company tilt.
According to Arnott et al. (2013), a simulated monkey portfolio (with annual rebalancing to a randomly selected group of stocks) provided 1.6% annual value added relative to the cap-weighted market portfolio. Before deciding to implement such a monkey portfolio, however, a prudent investor will consider its risk. The average size of the companies in a monkey portfolio is far smaller than the cap-weighted market. Smaller companies are typically riskier than larger companies. A monkey portfolio’s tilt toward smaller, riskier companies increases reported annual volatility to 18.3% from the 15.3% volatility of the cap-weighted market and produces tracking error of nearly 8%. After considering these risks, an investor may conclude that the simulated simians don’t seem so smart.
Some other alternative beta strategies also don’t seem as smart after considering risk. An equal-weighted strategy, for example, produces a pronounced tilt to smaller companies relative to the cap-weighted market portfolio. It also produces higher volatility (17.4% versus 15.3% for the market). Both these characteristics are rather like those of a monkey portfolio. Strategies optimized specifically to reduce volatility also display prominent small size tilts and high tracking error (TE) (8% for the minimum variance strategy).
An investor could have achieved the simulated rebalancing return without a significant tilt to small companies and the resulting increase in volatility and tracking error. By rebalancing to the fundamental size of companies, Research Affiliates’ simple and transparent RAFI™ Fundamental Index™ strategy4 practically eliminates the unnecessary size tilt. This lack of a material size tilt for RAFI Fundamental Index strategies makes perfect sense; by rebalancing to fundamental measures of company size, they steer the large companies to large weights, medium companies to medium weights, and small companies to small weights.
In Arnott et al. (2013), the simulated fundamentals-weighted strategy displays 1.9% average annual value added with no material size tilt. The reported volatility of the fundamentals-weighted strategy of 15.5% is far below those of the monkey and equal-weighting strategies and approximately matches the 15.3% volatility of the cap-weighted market. The reported tracking error for the fundamentals-weighted strategy of 4.6% is far below the monkey portfolio’s TE. It is lower also than the TE of equal weighting, and materially lower than those of low volatility strategies.
Trading Incurs Costs
The surprisingly strong simulated performance reported in the JPM article across many alternative beta strategies, and the often even stronger performance of their inverses, ignores trading costs. Careful consideration of many of these strategies reveals that much of the simulated value added is derived from the assumed costless trading of small and illiquid stocks. Some or all of that outperformance will disappear after trading costs are incurred. For this reason, investors should understand the expected source and magnitude of trading costs associated with implementing various alternative beta strategies.
Trading costs will vary across time, across markets, and with the size of assets invested in a strategy. But most of all, investors should expect trading costs to be a function of portfolio turnover and the size of the companies traded.