Smart Beta’s $1.5 Trillion Bet – Where’s the Alpha?

Do smart-beta ETFs deliver what they promise?

Smart-beta ETFs have become a formidable force in modern investing, managing over $1.5 trillion – roughly 15% of the ETF market. Promoted as a smarter way to capture returns through exposure to factors like value or momentum, these strategies now stand second only to cap-weighted index funds.

With an average expense ratio of approximately 0.35%, they generate approximately $5.25 billion in annual revenue for the asset management industry.

But the critical question remains: Do they deliver what they promise?

To answer this question, I looked at three academic studies that focused on smart-beta ETFs. I selected only studies that looked at U.S. ETFs, were focused on risk-adjusted performance and were not published by employees of an asset manager.

The consensus, based on the three studies I cite below, is that smart-beta ETFs have failed, on average, to deliver risk-adjusted outperformance.

But the results would be more disappointing if these studies had considered survivorship bias. Each study looked at the performance of a group of smart-beta ETFs over a period of a decade or longer. But we know that asset managers routinely close or merge ETFs that perform poorly. If those non-surviving ETFs were included (which is not easy to do), the resulting average performance would be worse than what was reported.

To illustrate just how pernicious survivorship bias is, consider this article posted on Reddit. The author found that the 19 smart-beta ETFs that had 20-year track records ending in 2022 outperformed the S&P 500 by more than 41% on a cumulative basis. But this is a meaningless conclusion, in that it ignores all those ETFs that were shuttered over that period.

What is a smart-beta ETF?

Smart beta is a quantitative approach to fund or ETF construction. The securities to be included in the ETF are determined based on a screening process. For instance, a value ETF may choose the 30% of stocks with the lowest price-to-earnings or price-to-book ratios.

The fund is constructed based on a weighting algorithm. For example, the fund might be equal weighted, market-cap weighted, or weighted to maximize exposure to the quantitative screening factor (e.g., an ETF that screens for the lowest stocks based on price-to-earnings ratio could give the highest weighting to those stocks with the lowest P/E).

Smart-beta ETFs are rebalanced and reconstituted on a regular basis, as are other ETFs.

Smart beta ETFs are created with the goal of providing exposure to risk factors (or “betas”) other than the overall market. Value and small-cap smart-beta ETFs, for example, provide exposure to the factors identified by Fama and French in their 1993 research.

The use of the term “smart beta” began in 2006 in reference to fundamental indexing, a smart-beta strategy pioneered by Research Affiliates.

Smart-beta ETFs are active strategies in that they deviate from the total-market cap-weighted portfolio by virtue of their selection and weighting algorithms.

Three academic studies

Let’s turn to the three academic papers I reviewed.

The first paper, Performance of smart beta ETFs in the U.S. market: 2009–2019, was by four researchers at the Singapore Management University. They looked at the returns of all types of smart-beta ETFs over the decade from 2009 to 2019, including value, growth, dividend, risk-oriented, multifactor and other types of smart-beta products.

They found that smart-beta products did not generate positive risk-adjusted returns (their returns were not statistically significantly different from the overall market). There was positive alpha from some factors but not from others.

They attributed their results to the efficiency of the stock market, which left “no room for smart-beta strategies to generate excess returns.”

The paper, Do Smart Beta ETFs Deliver Persistent Performance?, was by two researchers at the Aaborg Universitet in Denmark and one affiliated with Nasdaq. They looked at 152 US equity smart beta ETFs over the period June 2000 to May 2017.

They found that only 40% of the ETFs had positive risk-adjusted returns. But they looked at the returns within each of the nine Morningstar style boxes (value, growth, blend and small-, mid- and large-cap). In seven of those nine boxes, they found persistence in the returns. Thus, if someone chose an ETF in one of those seven style boxes, it was statistically likely that their performance (or underperformance) would persist from year-to-year.

The paper, Smart Beta Exchange Traded Funds, was a master’s thesis by a student at the Copenhagen Business School. It looked at smart-beta ETF performance from January 2007 to March 2020, based on value, size, momentum, quality, low volatility, and multi-factor categories.

The author found that there was no evidence of risk-adjusted outperformance by smart-beta ETFs over the period studied. None of the smart-beta strategies generated positive alpha, and quality delivered statistically significant negative alpha. On a non-risk-adjusted basis, four of the six ETF categories outperformed the market.

Poor performance was attributed to expenses and “crowding out.” Over the last five and 10 years in the period studied, value and momentum were the worst performing categories, yet they received the largest asset flows.

This paper also looked at whether ETFs gave investors their intended factor exposures. On this note, the author found “mixed signals.” All ETFs provided some degree of the intended factor exposures, but they also provided unintended exposures that weakened performance.

The takeaways

None of the three papers endorsed smart-beta investing. Indeed, in two of the papers, the authors stated that smart-beta investing is “not so smart.”

As author of the third paper noted, the underwhelming performance is surely attributable to expenses (35 basis points versus three basis points for a market-cap-weighted index fund) and to asset flows.

On the question of asset flows, growth has generally outperformed value since 2000, although there have been periods that favored value. One explanation could be that the publication of the Fama-French research in 1993 led to asset flows into smart-beta value products over the ensuing seven years. This in turn drove up the prices of those stocks, which led to subsequent underperformance. But this is merely a hypothesis, and it is very difficult to measure the effect of asset flows on performance.

Be very skeptical of claims by asset managers about smart-beta strategies. Every smart-beta strategy is introduced following a period of back-tested outperformance. You will hear claims about “evidence-based” investing based on “proven financial theory.” Such claims often rely on selective back-testing rather than forward-looking performance.

Smart-beta ETFs are active strategies dressed in passive clothing. While they may eventually outperform, doing so in an increasingly efficient market is an uphill battle. Investors considering these products should focus on low-cost options – and brace for long stretches of underperformance that could test even the most patient holders.

Robert Huebscher was the founder of Advisor Perspectives and its CEO until the company was acquired by VettaFi in 2022. He was a vice chairman of VettaFi/TMX until April 2024.