A Note On Smart Beta ETFs

by: Marius Bausys


Smart Beta ETFs have grown in popularity over the recent years.

Investors should investigate how a specific factor affects their portfolio.

With broadly comparable risk metrics, Smart Beta ETFs achieve a varying degree of success in different economic cycles.

I had recently attended a Smart Beta ETF conference in the City of London, United Kingdom. The event was buzzing with investors, ETF providers and other market participants. The significant interest in this gathering was probably not as a big surprise given that assets invested in Smart Beta ETFs globally stand around $400 billion according to ETFGI. However, the rapid development of this space also means that it has become increasingly difficult for an average investor to identify funds that are best suitable for their portfolio. To keep this task manageable, using practical examples I would like to demonstrate how different factor tilted investments affect a traditional portfolio.


To keep things simple, I use a classical 60/40 portfolio as a starting point. Such a portfolio is 60% invested in stocks and 40% in bonds with the SPDR S&P 500 Trust ETF (NYSEARCA:SPY) serving as a proxy for equities and the Vanguard Total Bond Market ETF (NYSEARCA:BND) for fixed income. Smart beta factors are represented by iShares range of ETFs:

  • Low volatility - iShares MSCI USA Minimum Volatility ETF (NYSEARCA:USMV)
  • Value - iShares MSCI USA Value Factor ETF (NYSEARCA:VLUE)
  • Size - iShares MSCI USA Size Factor ETF (NYSEARCA:SIZE)
  • Momentum - iShares MSCI USA Momentum Factor ETF (NYSEARCA:MTUM)
  • Quality - iShares MSCI USA Quality Factor ETF (NYSEARCA:QUAL)

In order to measure the impact of an investment in one of the Smart Beta ETFs, I replace 20% of portfolio invested in SPY with an allocation to a smart beta factor. I then put such a portfolio through the analysis mechanism on a freely available investor tool InvestSpy.com. The tables below illustrate results utilizing 2 years of historical data.



Low volatility






As can be seen from the results tables, different smart beta factors had distinctively different performance in terms of returns over the last couple of years. Whilst MTUM leads the pack with a gain of 26.3%, VLUE grew only 4.2%. USMV and QUAL also meaningfully outperformed SPY, whereas SIZE trailed the market cap S&P 500 by a couple of percentage points. However, as returns are strongly dependent on the economic cycle and tend to fluctuate widely from year to year, I would like to focus more attention on risk parameters.

Beta measures security's sensitivity to the benchmark index, which in this case is SPY. MTUM and QUAL had beta coefficients almost identical to the SPY itself, whilst the remaining three smart beta ETFs were less exposed to the broad market cap index. This is due to the fact that by default USMV, VLUE and SIZE all invest in lower risk stocks that typically have reduced beta and volatility. Comparing betas at the portfolio level, they all fall in a range between 0.53 and 0.58, thus the dispersion is not large.

In terms of annualized volatility, only USMV had a lower volatility than SPY. This once again proves how difficult it is to achieve a more efficient diversification than the all-encompassing market cap fund. However, it has to be noted that the exceptionally high volatility reading in SIZE was due to an outlier in the Yahoo! Finance database on July 6, 2015, where on a thinly traded day the fund lost 28% of its value but bounced all the way back the following day.

Maximum drawdown readings for all five portfolios is also comparable, ranging between 6.4% and 7.9%. The portfolio with USMV was the top performer in this category, proving that this specific ETF achieves "what it says on the tin". The portfolio containing VLUE had the deepest maximum drawdown as value stocks struggled in a recent bull market.


From the risk perspective, smart beta factor ETFs do not appear to affect a standard portfolio in a much different way that an investment in S&P 500 fund would. The only exception would be USMV, which clearly helps reduce the overall risk. But it is obvious that even with broadly similar risk parameters, Smart Beta ETFs do deliver different returns. This is what investors want and expect. The million (or even billion for some) dollar question though is how to time exposures right.

Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.