Do iShares Smart Beta ETFs Outperform? (Part II)
September 12, 2016
Do iShares Smart Beta ETFs Outperform? (Part I)
In the first part of this post, we analyzed a couple of iShares smart beta ETFs, the iShares Edge MSCI USA Size Factor ETF (SIZE) and the iShares Edge MSCI USA Value Factor ETF (VLUE).
Let’s start the second part with the evaluation of the iShares Edge MSCI USA Momentum Factor ETF (MTUM). Its issuer states that this ETF generates
Exposure to large- and mid-cap U.S. stocks exhibiting relatively higher price momentum
As before, the analysis will start in the first full month of the ETF’s existence and end in July 2016. Here is the cumulative RealAlpha™ chart with related statistics for the ETF:
The ETF produced a return comparable to that of its reference portfolio, which had a lower volatility. The RealBeta™ of the ETF was considerably below than that of a broad-based equity market ETF.
The following chart and associated statistics show the constant composition of the reference ETF portfolio for the iShares Edge MSCI USA Momentum Factor ETF:
The ETF had major equivalent positions in the Consumer Staples Select Sector SPDR® Fund (XLP), First Trust Large Cap Growth AlphaDEX® Fund (FTC), Health Care Select Sector SPDR® Fund (XLV), PowerShares Dynamic Large Cap Growth Portfolio (PWB), First Trust Dow Jones Internet Index Fund (FDN), and PowerShares NASDAQ Internet Portfolio (PNQI). (The Other component in the chart collectively represents additional two ETFs with smaller weights.)
Not surpringly, the ETF had a strong tilt toward large-cap growth stocks, especially in the consumer staples and healthcare sectors, as well as the Internet industry. Unlike with the previous iShares smart beta ETFs, no single position was clearly dominant in its reference portfolio. It can also be reasonably expected that in the future, the ETF’s exposure to specific sectors and industries will change along with price momentum shifts. Therefore, for a further performance comparison, a similar smart beta equivalent position should be chosen.
Over the same analysis period, MTUM outperformed FTC and PWB in terms of the annualized return and Sortino ratio, and had an equal or higher Sharpe ratio:
At 0.15%, the expense ratio of MTUM was much lower than the 0.62% of FTC and 0.57% of PWB, which improved relative returns of MTUM. The average correlation between rolling 24-month returns was 0.95 and 0.96 for MTUM with FTC and MTUM with PWB, respectively.
Finally, we will evaluate the iShares Edge MSCI USA Quality Factor ETF (QUAL). According to the issuer, this ETF produces
Exposure to large- and mid-cap U.S. stocks exhibiting positive fundamentals (high return on equity, stable year-over-year earnings growth and low financial leverage)
Since QUAL’s inception date was in July 2013, the analysis begins in August 2013. Here is a chart with accompanying statistics of the cumulative RealAlpha™ for the ETF:
The ETF moderately outperformed its reference portfolio, which had a slightly higher volatility. The ETF’s RealBeta™ was lower than that of a broad-based equity market ETF.
The following chart with accompanying statistics depicts the composition of the reference portfolio for the iShares Edge MSCI USA Quality Factor ETF:
The ETF had major equivalent positions in the iShares Russell Top 200 Growth ETF (IWY), SPDR® Dow Jones® Industrial Average ETF (DIA), PowerShares S&P 500 Quality Portfolio (SPHQ), Vanguard Dividend Appreciation ETF (VIG), PowerShares NASDAQ Internet Portfolio (PNQI), and iShares U.S. Energy ETF (IYE). Clearly, this ETF had a strong tilt toward mega-cap stocks, especially of the growth classification.
Over the same analysis period, QUAL had a significantly lower return as well as slightly smaller Sharpe and Sortino ratios than those of IWY:
The average correlation between rolling 24-month returns of the two ETFs was 0.98.
The above analyses uncovered reference portfolios for select iShares smart beta ETFs. While a wholesale substitution of an ETF with its multi-member reference portfolio may not always be practical, each of these portfolios
- Built a foundation for assessment of the true risk-adjusted performance of a smart beta ETF.
- Captured exposures of a smart beta ETF to various stock market styles, sectors and industries (paradoxically, these are exposures of the analyzed factor ETF to various other factors). This may help investors avoid an undesirable overlap with other positions in their overall investment portfolios.
- Identified a predominant exposure of a smart beta ETF to a single factor. This may help investors substitute a smart beta ETF with another product that implements a traditional market-cap index or with a similar strategic beta strategy.
If you would like to use the ETP Analysis Service to examine other smart beta products, please register on our website.
September 10, 2016
Correlations of Factor ETFs
To better demonstrate the new Alpholio™ ETP Analysis Service in action, let’s analyze several of the iShares smart beta ETFs. The oldest of these products were introduced in mid-April 2013, so by now more than three years of performance data are available. According to their issuer
Smart beta ETFs can help investors achieve goals like reducing risk, generating income, or potentially enhancing returns. These funds primarily focus on factors – broad, persistent drivers of returns across equities and other asset classes. New technologies have made it easier to target factor exposures, which investors can access with iShares Edge ETFs.
Due to the scope of analysis, this post will be divided into two parts. We will start with the iShares Edge MSCI USA Size Factor ETF (SIZE). According to its issuer, this ETF provides
Exposure to large- and mid-cap U.S. stocks with a tilt towards the smaller, lower risk stocks within that universe
Here is a chart with related statistics of the cumulative RealAlpha™ for this ETF from May 2013 (the first full month of returns since its inception) through July 2016:
The ETF returned effectively as much as its reference ETF portfolio that had a slightly lower volatility. The ETF’s RealBeta™, measured against a broad-based US equity index ETF, was close to one.
The following chart shows the constant composition of the reference ETF portfolio for the iShares Edge MSCI USA Size Factor ETF:
The ETF had equivalent positions in the SPDR Russell 3000® ETF (THRK), SPDR® Dow Jones® REIT ETF (RWR), SPDR® S&P® Insurance ETF (KIE), iShares U.S. Medical Devices ETF (IHI), IQ Hedge Multi-Strategy Tracker ETF (QAI), and Utilities Select Sector SPDR® Fund (XLU).
Over the same analysis period, SIZE outperformed THRK, the dominant position in its reference portfolio, in terms of a slightly larger annualized return, as well as higher Sharpe and Sortino ratios:
The average correlation between rolling 24-month returns of the two ETFs was 0.96.
The second smart beta ETF we will evaluate is the iShares Edge MSCI USA Value Factor ETF (VLUE). According to the issuer, this ETF supplies
Exposure to large- and mid-cap U.S. stocks with lower valuations based on fundamentals
Here is a chart with related statistics of the cumulative RealAlpha™ for this ETF:
Since late 2014, the ETF failed to add value over its reference portfolio that had a slightly lower volatility. The ETF’s RealBeta™ was higher than that of a broad-based stock market ETF.
The following chart shows the fixed reference ETF portfolio for the iShares Edge MSCI USA Value Factor ETF:
The ETF had major equivalent positions in the SPDR® S&P® 500 Value ETF (SPYV), SPDR® Morgan Stanley Technology ETF (MTK), iShares U.S. Broker-Dealers & Securities Exchanges ETF (IAI), First Trust Large Cap Value AlphaDEX® Fund (FTA), iShares U.S. Healthcare Providers ETF (IHF), and iShares Transportation Average ETF (IYT). The Other component in the chart collectively represents two additional ETFs with smaller weights.
Although VLUE had a slightly higher annualized return than SPYV (the prevailing ETF in its reference portfolio), it underperformed SPYV in terms of both Sharpe and Sortino ratios:
The average correlation between rolling 24-month returns of the two ETFs was 0.98.
The second part of this post will cover two other iShares smart beta ETFs, the iShares Edge MSCI USA Momentum Factor ETF (MTUM) and iShares Edge MSCI USA Quality Factor ETF (QUAL).
August 28, 2013
Factor ETFs from iShares
BlackRock has recently introduced a set of four iShares ETFs that follow factor indices. They are:
The first three of these ETFs debuted on April 16, 2013, while the fourth one three months later. Therefore, as of this writing, there are only 91 and 28 trading day data available for these ETFs, respectively. Traditionally, at least three years worth of data (a minimum of 36 monthly data points) are required to calculate a return correlation between two investments. However, it may be helpful to take an early look on how the return correlations among these ETFs and the iShares Core S&P 500 ETF (IVV) are shaping up so far:
Since daily returns are assumed to contain a substantial amount of “noise,” and the observation period is very limited, the above figures certainly cannot be considered very reliable. However, there is an early indication that the majority of correlations are lower than 0.6, which should aid in portfolio diversification. A research paper from BlackRock shows that idealized zero-net-investment factor portfolios constructed using Fama-French approach* can have much lower long-term correlations:
*MktRf = market, SMB = size, HML = value, CME = quality.
Only time will tell whether these new factor ETFs provide low inter-correlations and sufficient returns to truly benefit an investment portfolio. However, early signs are encouraging.
July 25, 2013
iShares (owned by BlackRock), in conjunction with the Arizona State Retirement System, just introduced three new “factor” ETFs:
- iShares MSCI USA Momentum Factor Index Fund (ticker MTUM)
- iShares MSCI USA Size Factor ETF (ticker SIZE)
- iShares MSCI USA Value Factor ETF (ticker VLUE).
Why does this matter? The Fama-French three factor model, using the SMB and HML factors, explains over 90% of returns of diversified portfolios, instead of the average 70% explained by the CAPM. The model was further improved by Carhart with an addition of the fourth factor, momentum.
While time will tell how close (and for how long) the above ETFs track their underlying indices and theoretical factors, the introduction of these ETFs is yet another major industry trend in support of the Alpholio™ methodology.