Equity smart beta indices are often described as portfolios which tilt toward various (combinations of) equity factors. Thus, one cannot make intelligent choices regarding smart betas without first forming a view on which factors are “for real” and which are data-mined or data-snooped. The academic literature provides useful guidance on decision heuristics that investors can lean on to ascertain whether a factor truly contains a return premium. Summarizing from the studies cited above, the following set of characteristics would constitute evidence of an actual factor:
- The factor was discovered many decades ago; it has survived numerous database revisions as well as extensive out-of-sample data.
- The factor has been vetted, replicated, and debated in top academic journals over decades.
- The factor works in non-U.S. countries and regions.
- The factor premium does not change materially due to minor variations in the factor definition/construction.
- The factor has a credible reason to offer a persistent premium
- It is related to a macro risk exposure, or
- It is related to a deep-rooted behavioral bias that is present in a meaningful fraction of investors, or
- It is related to an institutional feature that cannot be easily changed.
- The factor exceeds a more stringent t-stat threshold of 3.5 (preferably 4.0) instead of 2.0 to adjust for data-snooping and other biases evidenced by the recent explosion in factor proliferation.
Once investors have determined which factors they actually believe in, they then need to figure out how best to capture the factor premia in their equity portfolios. For example, which factor premia can be accessed in low cost, transparent, and formulaic smart beta indices and which are better accessed through high-fee actively managed products? It is generally believed that the momentum premium is best accessed through skilled active managers, who can trade carefully and get ahead of the crowd in buying and selling, given the short holding horizon and liquidity-taking nature of the strategy. If that hypothesis is true, a smart beta index chassis may fail to effectively capture the momentum premium.
Similarly, an illiquidity premium requires active managers with either market making capabilities or sophisticated trading skill, so an index replication approach is unlikely to be successful in capturing this premium. High-fee active management may be necessary. On the other hand, value and low beta strategies require no more than 10% and 20% annual turnover, respectively, and have very slow signal decay. These two premia are well-suited to be captured in low cost smart beta index products.
In determining an appropriate core equity portfolio, investors need to consider their measure of risk. For example, is tracking error to a cap-weighted policy benchmark the measure of risk? And, relatedly, is the value-added return relative to a benchmark the primary measurement of success? Or is portfolio volatility the dominant risk measure with absolute return the key success criterion?
Once investors define their portfolio “bull’s-eye,” it is relatively straightforward to determine which mix of smart beta index products and active products would lead to the desired equity holdings.
We have become what we hated when we were in graduate school. We are now the curmudgeonly party poopers who scoff at the latest and greatest new factors discovered by enthusiastic financial engineers. We like to think we have become wiser and have thus developed a healthy skepticism, not merely grown more cynical of academia and the industry. Fortunately, we seem to be in good company: The titans of academia have similarly grown weary of the factor proliferation, which has created a dizzying zoo of factors. The sheer variety seems to serve the purposes of publication for tenure and product creation more than better investor outcomes. We will gladly bet a simple blend of market, value, low beta, and momentum exposures against anyone’s optimized 81-factor portfolio.