How Smart are “Smart Beta” ETFs?

How Smart are “Smart Beta” ETFs?

April 28, 2015 Academic Research Recap, Architect Academic Insights, Tactical Asset Allocation Research
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Many consider smart beta to be a revolution in the asset management industry. For example, Bloomberg ran an article, “Funds Run by Robots Now Accounts for $400 Billion,” which caught our attention. According to this article, “Smart beta,” is one of the fastest growing segments of ETFs, accounting for nearly 20% of all assets in domestic ETFs as of the end of 2014.

The “secret sauce” of smart beta is its use of alternative weighting schemes to capture premiums associated with factors such as size, value, momentum, low volatility, and so on.

Unfortunately, academic researchers are having difficulty finding the secret sauce associated with smart beta. For us, this finding is unsurprising, since other researchers have already highlighted that many so-called factors are likely false. Nonetheless, we highlight a new research paper by Denys Glushkov, which dives deep into the data and concludes that the benefits of smart beta are questionable.

A quote from Denys:

Using a comprehensive sample of 164 domestic equity Smart Beta (SB) ETFs during 2003-2014 period…I find no evidence that SB ETFs significantly outperform their risk-adjusted passive benchmarks.

Ouch…

How Smart are “Smart Beta” ETFs?

Denys Glushkov conducts a comprehensive analysis of relative performance and factor timing of “Smart Beta” ETFs. A version of the paper can be found here.

In order to see how smart “Smart Beta” really is, this paper uses 164 domestic equity “Smart Beta” ETFs from 2003 to 2014 as the test sample. It categorizes each ETF into 15 category portfolios based on common factors, and then compares them with passive index benchmarks.

This paper use 3 types of benchmarks:

  1. Self-declared benchmark by the ETF provider;
  2. Risk-adjusted version of the self-declared benchmark;
  3. A blended benchmark constructed as an annually rebalanced combination of passive existing funds representing the broad stock market and various factor exposures (size and value).

Finding 1: Performance isn’t great

  • 60% of “Smart Beta” categories (9 out of 15) outperformed their raw declared benchmarks from 2003 to 2014.
  • Only one category (Value) significantly outperformed its risk-adjusted benchmark as measured by Jensen’s alpha.
  • None of the “Smart Beta” categories significantly outperformed the blended benchmark.
  • One of the most popular categories, dividend-oriented ETFs, significantly underperformed the benchmark by an annualized -3.81% (t=1.73)
How smart are smart beta ETFs
The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Please see disclosures for additional information. Additional information regarding the construction of these results is available upon request.

Finding 2: “Good times” vs “Bad times” 

  • During periods of negative benchmark returns (“bad times”), none of the categories beat their risk-adjusted benchmarks;
  • Even during periods of positive benchmark returns (“good times”), the same categories dramatically underperform the same benchmarks.

Finding 3: Factor Exposures

The author runs multi-factor regressions to test the factor exposure of 15 smart beta categories. The six factors used in the regressions are: size, value and momentum, quality, beta and volatility. The paper finds the following:

  • Most “Smart Beta” portfolios, except dividend-oriented strategies, have significant positive exposure on the size factor, which indicates that “Smart Beta” ETFs tend to hold smaller stocks.
  • Most “Smart Beta” portfolios,  except Fundamentals-weighted ETFs strategies, have either insignificant or significant negative exposures to the value factor.
  • Overall, “Smart Beta” ETFs do exhibit significant factor exposures, but those exposures are not always consistent.

Takeaways:

We agree that “Smart Beta” can be replicated via allocations to passive products. We also find that smart beta is essentially an expensive way to access active management, which we discuss in our post, Smart Beta is more expensive than you think.

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Please remember that past performance is not an indicator of future results. Please read our full disclaimer. The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. This material has been provided to you solely for information and educational purposes and does not constitute an offer or solicitation of an offer or any advice or recommendation to purchase any securities or other financial instruments and may not be construed as such. The factual information set forth herein has been obtained or derived from sources believed by the author and Alpha Architect to be reliable but it is not necessarily all-inclusive and is not guaranteed as to its accuracy and is not to be regarded as a representation or warranty, express or implied, as to the information’s accuracy or completeness, nor should the attached information serve as the basis of any investment decision. No part of this material may be reproduced in any form, or referred to in any other publication, without express written permission from Alpha Architect.

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About the Author

Wesley R. Gray, Ph.D.

After serving as a Captain in the United States Marine Corps, Dr. Gray received a PhD, and was a finance professor at Drexel University. Dr. Gray’s interest in entrepreneurship and behavioral finance led him to found Alpha Architect. Dr. Gray has published three books: EMBEDDED: A Marine Corps Adviser Inside the Iraqi Army, QUANTITATIVE VALUE: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors, and DIY FINANCIAL ADVISOR: A Simple Solution to Build and Protect Your Wealth. His numerous published works has been highlighted on CBNC, CNN, NPR, Motley Fool, WSJ Market Watch, CFA Institute, Institutional Investor, and CBS News. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.


  • Thomas Rinaldi

    Doesnt a dividend strat have to underperform as the dividends are paid out, not reinvested. Did you renivest the dividends into the various ETFs in the analysis?

  • dph

    Is there a curated list of smart etfs compared to the closet indexers? With 200+ so called smart etfs out there, how many are truly active (dozens or so)?

  • That is a good question for Denys. I can’t find an explicit callout in the paper that he is using total returns, but that is typically assumed to be the case in academic research articles.

  • Thomas Rinaldi

    I’d be curious. Had the impression boring and generally cheap dividend payers did better over time.

  • Thomas Rinaldi

    Wes, I forgot my own point. Even if you use total return, it matters a lot whether you invest the dividends back into the fund. You can give credit for the return of the dividend in the total return, but if you dont buy more shares of the dividend etf then over time, you have a cash balance building conceptually whereas companies that dont pay dividends are reinvesting that money in the business.

  • Tom, great point and agree 100%. Typically, the total returns have some assumption about how/when an investor reinvests the dividend. e.g., end of month prices.