How Smart Are 'Smart Beta' ETFs? Analysis Of Relative Performance And Factor Timing – ValueWalk Premium
Smart Beta ETFs

How Smart Are 'Smart Beta' ETFs? Analysis Of Relative Performance And Factor Timing

How Smart Are ‘Smart Beta' ETFs? Analysis Of Relative Performance And Factor Timing via SSRN

Denys Glushkov

University of Pennsylvania – Wharton Research Data Services (WRDS)

April 15, 2015


Using a comprehensive sample of 164 domestic equity Smart Beta (SB) ETFs during 2003-2014 period, I analyze whether these funds beat their benchmarks by tilting their portfolios to well-known factors such as size, value, momentum, quality, beta and volatility. I then test the claim that Smart Beta funds harvest factor premiums more efficiently than their traditional cap-weighted counterparts by dynamically exploiting time-variation in factor premiums.

I find no evidence that SB ETFs significantly outperform their risk-adjusted passive benchmarks. Positive returns from intended factor bets are offset by negative returns from unintended factor bets resulting in an overall performance wash. Risk-adjusted performance of SB funds is also insignificant when compared with the performance of the blended benchmark that provides passive cap-weighted exposure to market, size and value factors. After decomposing benchmark-adjusted performance of SB funds into selection, static and dynamic allocation effects, I find that their factor timing ability is neutral at best. Allocation effect contributes, on average, only 20% of the overall index-adjusted return. This is inconsistent with the argument that Smart Beta products augment performance by dynamic factor allocation.

Overall, the results support the hypothesis that, at least among domestic equity, long-term investors can obtain similar or better performance than Smart Beta funds from a simple mix of a risk-free asset and a portfolio which combines passive cap-weighted exposure to market, size and value premiums, while paying a fraction of the cost.

How Smart Are ‘Smart Beta' ETFs? Analysis Of Relative Performance And Factor Timing – Introduction

Exchange Traded Funds (ETFs) have experienced tremendous growth during the last 10-15 years. According to the ICI 2014 Investment Company Fact Book, in the past 10 years, more than $1.2 trillion of net new ETF shares have been issued1. By the end of 2014, assets under management in US-domiciled ETFs grew to nearly $2 trillion, where ETFs focused on the domestic US market constitute nearly 80%, or more than $1.5 trillion. In addition to the exponential growth in overall market value, ETFs as an asset class continues to garner an increasing share of total trades in financial markets, as its fraction of the overall dollar volume in the US stock market grew from 4% at the beginning of 2001 to nearly 30% at the end of 20142.

One of the fastest growing segments of ETF market that has been attracting a lot of attention in recent years are the so-called “Smart Beta” (SB) ETFs. According to Bloomberg Intelligence, as of the end of 2014 there were almost 400 US-domiciled Smart Beta funds managing around $400bil or nearly 20% of all assets in domestic ETFs, a dramatic change from essentially nothing back in May 2000. SB sector continues to attract a steadily increasing share of net flows relative to the rest of the ETF market, particularly since the beginning of 2009, reaching an all-time high of nearly 35% of all net flows into US-domiciled ETFs during 2013. These trends are supported by the overall positive attitude of investors towards “smart beta” investment vehicles as nearly a quarter of surveyed asset owners in North America have adopted these strategies in their portfolios (with adoption in Europe at much higher 40%)3. At the same time, the average cost of SB ETFs measured by the asset-weighted expense ratio was 70% higher (0.41% vs 0.24%) than that of traditional cap-weighted “non-smart-beta” ETFs, implying that smart beta product providers as a whole are charging investors additional $370mil in fees per year4.

This evidence poses a question: do smart beta products deliver on their promise of outsmarting traditional cap-weighted indexes by bringing factor investing to the masses? Do smart beta products justify fees exceeding a third of a billion dollars in fees each year? Answers to these questions are important, knowing that fund expenses and trading costs are among the few reliable predictors of fund performance (Gil-Bazo and Ruiz-Verdu, 2009; Edelen, Evans and Kadlec, 2013), and that recent explosive growth in assets managed and flows received by these funds are primarily due to the keen investor interest associated with factor investing (Ang, 2014). This paper provides a detailed look at the relative performance of smart beta ETFs and their efficiency in capturing documented factor risk-premiums.

According to Morningstar, the common thread among SB ETFs is that “they seek to either improve their return profile or alter their risk profile relative to more-traditional market-capitalization weighted benchmarks” by using alterative weighting methodology to get exposure to a number of factors such as size, value, volatility and others (see “Global Guide to Strategic-Beta Exchange Traded Funds” for more details). While there is no one uniform consensus on the right naming convention, preferred definition of Smart Beta focuses on alternative ways to construct market exposure5. Rob Arnott, one of the advocates of Smart Beta approach to investing and the chairman and co-founder of Research Affiliates, argues that “what smart beta does best is sever the link between the price of a stock and its weight in the index”6.

The benefits of SB products according to its proponents are twofold. First, that SB products provide investors with easily accessible pre-packaged investment tools to systematically harvest return premiums in addition to market returns (bulk beta) by tilting their portfolios to factors with positive long-run risk-premiums such as value and momentum. In other words, SB ETFs are marketed as products that deliver better raw and risk-adjusted returns relative to their purely passive cap-weighted benchmarks as they go beyond providing mere market exposure. Second, SB products are designed to harvest these factor premiums more efficiently by systematic rule-based contrarian rebalancing to non-price linked target weights. Hsu (2014) argues that rebalancing allows some SB strategies to profit from mean reversion in factor premiums by “effectively implementing a dollar cost averaging program”. For example, fundamentally-weighted ETFS might harvest value premium more efficiently, because, unlike traditional cap-weighted style funds, they systematically engage in contra trading by buying what has fallen and selling what has risen in price, betting on return reversion (Arnott et al., 2013; Chow et al., 2011). Critics of Smart Beta, on the other hand, argue that its long-run performance is no better than cap-weighted performance. Malkiel (2014) summarized his skepticism as follows:

“…Many smart beta ETFs have failed to produce reliable excess returns, although a few have beaten the market over the lifetime of the funds. To the extent that some smart beta strategies have generated greater than market returns, those excess returns should be interpreted as a reward for assuming extra risk. In departing from the market portfolio investors are taking on a different set of risks. Smart beta portfolios do not represent a sophisticated better mousetrap for investors. Investors should be wary of getting caught in the riskier mousetrap themselves. Smart beta fails the safety test…”

Smart Beta ETFs

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