Let’s Talk About Smart Beta

I’m Matthew Bartolini, Head of SPDR? Americas Research, and my affinity for charts has earned me the nickname “Chartolini”. Charts and data are my passion. I dream in bar charts and scream “show me the data” as if I’m Jerry Maguire looking to see some money. 

This edition of #ChartswithChartolini is a little different. Instead of debunking an ETF myth, I’d like to take a look at a growing ETF trend that requires more in-depth due diligence. Let’s talk about smart beta…specifically, how smart beta ETFs are defined and classified. There’s a lot to cover, so stay with me.

Over the last 10 years, smart beta ETFs have been among the most popular strategies to launch as investors have become more familiar with the idea of factor investing. Or rather, investors have become more familiar with the notion of harnessing well-documented premia (such as value and momentum) in search of returns in excess of broad-market beta. During this time, smart beta assets have ballooned by 2,371%, growing from $14 billion to $357 billion.1 Moreover, the asset mix has moved away from traditional dividend strategies toward more factor-based approaches, with the share of smart beta ETF assets held by dividend funds falling from 59% to 44%.2

This shift in buying behavior indicates investors are increasingly viewing their portfolios through a factor lens. They are choosing among smart beta funds that provide specific exposure to a range of factors, including minimum volatility and size, or opting for multi-factor funds that offer exposure to multiple factors. Lately, fund launches have become more sophisticated, with many multi-factor blends and quantitatively-driven (e.g., optimized) products coming to market. The chart below illustrates these trends.

Defining Smart Beta

As smart beta ETFs garner more attention and become more sophisticated, more in-depth due diligence is required. In our view, this begins with defining the selection universe. It is commonly held that:

• There is a core set of factors which are the most persistent in driving equity returns: value, size, volatility, quality, and momentum;
• These factors are well documented in academic literature and have persisted through time because they capture systematic risk, behavioral biases and market structure issues;
• While factors outperform over time, individual factor performance can vary by economic environment;
• Due to the cyclical nature of individual factor performance, a diversified mix of factors provides the best opportunity to outperform a cap-weighted benchmark over time;
• Dividend-based strategies should be recognized as smart beta as they are used to target specific portfolio outcomes.

Still with me? Good. Let’s move onto classification.

The Smart Beta Classification Conundrum

Most smart beta classifications adopt either a selective “I’ll know it when I see it” or a throw it all in there “kitchen-sink” approach. As a result, unlike traditional size and style strategies, there is no clear and concise definition for smart beta. The lack of consensus around what constitutes smart beta results in strategies with seemingly similar names—but in reality, very different construction methodologies.

For example, let’s consider “value” funds as identified by FactSet. At year-end 2018, there were 29 value funds focused on large- or broad-market US equities. The return dispersion between those 29 strategies in 2018 was 12.5%! The best-returning fund was down 4.05% while the worst declined 16.54%. From a risk perspective, the volatility of these strategies ranged from 10% to more than 15%. The chart below illustrates this risk and return dispersion among strategies sharing the same “value” moniker. The dispersion looks like someone just broke the rack in pool, not a breakdown of similar strategies.

Furthermore, the average number of holdings in the funds was 302, ranging from as few as 21 holdings to as many as 1,322.3  The vastness of this range can catch investors off guard unless they carefully conduct in-depth due diligence, much like they would when choosing an actively managed fund. A checklist—such as the one we recently created —can help investors look beyond the label and ensure they’re asking the right questions. All due diligence, however, starts with identifying the applicable universe, and therefore starts with classifications.  The old adage of “know what you own” definitely applies here.

Step-by-step: How We Approach Smart Beta Classification

Creating classification schemas is a difficult task. There is no right or wrong answer, and therein lies the main problem with smart beta investing. If major data providers—and for that matter, fund providers—cannot agree on what constitutes a smart beta strategy, how will investors be able to fully implement it as part of their investment process?  

The chart below depicts the central issue of seemingly random walk down smart beta street. It illustrates the total number of smart beta ETFs and their assets as identified by three major data providers and according to the SPDR Americas Research definition. Given that each data provider has a different definition, we see different figures for assets and number of funds. Traditional style exposures are included by data providers, which we exclude. But that is not the only wrinkle we apply. 

On the SPDR Americas Research team, we take 5 steps to identify and classify smart beta strategies:

• Step 1: As a starting place, take everything Morningstar deems to be “Strategic Beta”
• Step 2: Determine which ETFs are sector-based strategies
• Step 3: Remove any Morningstar-identified smart beta strategies that are market-cap weighted
• Step 4: Add back in market-cap weighted dividend strategies
• Step 5: Tally up what is left, then manually classify by strategy type to ascertain the targeted factor exposure(s)

Our Aim: Provide Clarity in a Nebulous Field

The last chart, placed below, is a recreation of the earlier chart, but with the sub-asset classes (sector, dividend) broken out. By creating different classification tiers for smart beta and being transparent about our process, we aim to provide clarity in a nebulous field that features an abundance of different strategy types—all carrying the same name. As more smart beta strategies come to market, our classification schema and other resources can be valuable tools in the due diligence process, helping investors go from identification to implementation.

For our latest smart beta insights, you can follow SPDR Blog or visit the smart beta section of our website.

1 Bloomberg Finance L.P., Morningstar, as of 12/31/2018. Calculations by SPDR Americas Research.

2 Bloomberg Finance L.P., Morningstar, as of 12/31/2018. Calculations by SPDR Americas Research.

3 Bloomberg Finance L.P., FactSet, as of 12/31/2018. Calculations by SPDR Americas Research. 

Definitions

Beta Measures the volatility of a security or portfolio in relation to the market, usually as measured by the S&P 500 Index. A beta of 1 indicates the security will move with the market. A beta of 1.3 means the security is expected to be 30% more volatile than the market, while a beta of 0.8 means the security is expected to be 20% less volatile than the market.

Important Risk Information

State Street Global Advisors One Iron Street, Boston MA 02210. T: +1 866 787 2257.

The views expressed in this material are the views of Matthew Bartolini through the period ended January 29, 2019 and are subject to change based on market and other conditions. This document contains certain statements that may be deemed forward looking statements. Please note that any such statements are not guarantees of any future performance and actual results or developments may differ materially from those projected. Investing involves risk including the risk of loss of principal. Past performance is no guarantee of future results.

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1/31/2020