Once an investor identifies the desired robust sources of return premium they wish to capture in their portfolio, the logical next step is to select the product(s) that can deliver these premiums. An investor new to the smart beta arena can easily be overwhelmed with the immensity of product offerings.
To address this challenge, we believe investors should be aware of the elements that constitute quality craftsmanship in the design of smart beta strategies, and make their product selection decisions accordingly. These elements can be grouped along the following dimensions: 1) universe coverage and weighting mechanism, 2) signal definition, 3) measurement period, and 4) rebalancing frequency.
A commonality underlying all of these dimensions arises from an overriding lesson we have gleaned from our combined decades of designing investment strategies: thoughtful product design work includes striking a balance between simplicity and effectiveness. Albert Einstein aptly captured this notion: “Everything should be made as simple as possible, but not simpler.” We lean toward simplicity because it tends to lead to more predictable results and easier governance (Brightman, Kalesnik, and Kose, 2015), and we are highly conscientious in our design of preserving the effectiveness of the strategy.
As we explore each of the four craftsmanship dimensions, we will use the example of a strategy—the RAFI™ Fundamental Index—that relies on fundamental measures of company size to systematically rebalance against the market's constantly shifting expectations, and thereby harnessing a value premium (Arnott, 2006). Investors can apply the following framework to evaluate the craftsmanship elements of just about any smart beta strategy.
Dimension #1: Universe coverage and weighting mechanism
Decisions surrounding the universe coverage and weighting mechanisms of strategies can meaningfully impact investor portfolios because they influence the amount of liquidity available, which in turn affects transaction costs. For instance, if we invest in a strategy that allocates equal weights to all stocks with no consideration of the size of a company (an equal-weighted scheme), we inherently have a higher exposure to smaller companies, which tend to be less liquid and more expensive to trade. Unfortunately, most investors ignore liquidity issues because of the difficulty in observing their tangible impact on portfolio returns.
This dimension partially informs why we chose to avoid an equal-weighted approach, even though it is the simplest non-price-weighted weighting mechanism of all! Consider the comparative analysis conducted by Aked et al. (2014). The starting universes of the portfolios in the analysis include all stocks within the largest 85th percentile rank, either by cumulative market capitalization (for the cap-weighted and equal-weighted strategies) or by cumulative fundamental weight (for the fundamental strategy).2 Both essentially cover a fixed portion of the market and are consistent with the practices of the most popular index providers.
A couple of observations: First, both an equal-weighted approach and a fundamental-weighted approach exploit a weakness in the cap-weighted approach—the tendency to overweight overpriced stocks and underweight underpriced stocks. So, as expected, both strategies meaningfully outperform the cap-weighted benchmark over the long run. Second, and more surprising, we observe a substantial difference in the performance of the fundamental approach and of the equal-weighted approach across the G7 countries: Australia, Canada, France, Germany, Italy, Japan, United Kingdom, and United States.