Diversify Factor Risk With This Multifactor ETF

While single-factor strategies that target stocks with low valuations, strong momentum, high profitability, and low volatility have each been successful over the long term, they all experience extended stretches of underperformance. But because these factor strategies tend to perform well at different times, investors can reduce risk without sacrificing return by diversifying across them.

The portfolio is divided into four equally weighted sleeves that each tilt toward stocks with a different characteristic of interest. This simple approach is transparent, though a more integrated approach would probably be a bit more efficient. Each sleeve gives over- or underweightings to stocks from the large-cap selection universe based on the degree to which they exhibit the targeted style characteristic. The fund scales these active bets to give each sleeve a 4% target tracking error to its selection universe. Consequently, stocks with factors that introduce greater tracking error, like low volatility, receive lower active weightings. Together, these active bets partially offset one another, allowing the overall portfolio to maintain a 2% tracking-error target.

The resulting portfolio looks a lot like the S&P 500's. It includes more than 420 stocks out of 500 eligible names, with an active share of 26%, as of this writing. These holdings have a smaller average market capitalization than the constituents of the S&P 500. However, they tend to trade at similar valuations. This is because the fund's momentum and quality sleeves pull the portfolio toward pricier names, while its value sleeve leans in the other direction.

This strategy was launched in September 2015, so it has not yet established a meaningful record. From its inception through January 2018, the fund's realized tracking error to the S&P 500 was slightly below 2%, and it lagged that index by 1.56 percentage points annually.

Fundamental View Stocks with low valuations, strong recent performance (momentum), strong profits, and low volatility have historically offered strong performance in most markets studied over the long term. There are reasonable economic explanations behind each effect, ranging from compensation for risk to behavioral mispricing, suggesting they will continue to work over the long run.

While each of these factors has a strong long-term record, they all go through periods of underperformance. Putting them together in a portfolio diversifies risk, reducing the chance of experiencing an extended period of underperformance and making it easier to stick with the factors through their inevitable rough patches.

The fund combines these factors by holding four different portfolio sleeves that each target stocks that score well on a different factor. This approach dilutes the fund's exposure to each factor because most stocks that score well on one dimension (like value) don't score well on the others (like momentum). And because each sleeve only represents 25% of the portfolio, the fund has only modest exposure to each factor. Its low tracking-error target also limits its factor bets and potential outperformance. But it should still benefit from these small tilts over time.

One of the benefits of combining the four factor strategies into a single portfolio is that it helps mitigate turnover, as adjustments across the four sleeves partially offset one another. For example, if a stock in the value sleeve starts to perform well, its weighting in the value sleeve may decrease at the same time it gets a larger weighting in the momentum sleeve. The managers only trade the net change in each security's weighting. To further reduce turnover, each sleeve applies a buffer around the target active weightings for each security, so that the fund doesn't trade until the style characteristics materially change. As a result, turnover was only 20% in fiscal 2017, which is low for a strategy that incorporates momentum.

The fund constructs its value and momentum sleeves differently than many of its peers. Within the value sleeve, the managers limit the fund's industry tilts relative to the selection universe, arguing that such bets are not rewarded. They measure momentum based on returns adjusted for sensitivity to market risk (beta) and stock volatility. This gives the fund a cleaner read on strong performance that is specific to a stock that may be more likely to persist during market reversals.

The profitability (quality) and low-volatility sleeves should point the fund toward defensive names that should help it hold up a little better than the market during downturns. It measures profitability based on gross profits/total assets, which strips out many of the expense items that may be less comparable across firms. The low-volatility sleeve measures volatility over the past 12 months, which should allow the fund to quickly detect changes in volatility.

The bets across the four sleeves aren't sized the same. The fund targets the same active risk (tracking error) from each of the four sleeves. Factors with greater active risk, like low volatility, require lower active weightings to achieve those targets than factors with less active risk, like quality.

Portfolio Construction The fund employs full replication to track the Goldman Sachs ActiveBeta U.S. Large Cap Equity Index. This index applies a transparent methodology that diversifies across four well-vetted factor strategies, supporting the Positive Process Pillar rating. The selection universe for the index includes the largest 500 U.S. stocks. From this pool, the fund tilts toward stocks with strong value, risk-adjusted momentum, quality (gross profits/total assets), and low-volatility characteristics. The portfolio is subdivided into four equal-sized sleeves, each of which has a different factor focus.

Each sleeve sizes its active weightings in order to target a 4% tracking error to its market-cap-weighted selection universe. In contrast to the other sleeves, which start with this market-cap-weighted universe, the low-volatility sleeve applies its active weightings to an equally weighted version of this universe. The managers argue that this is prudent because the low-volatility effect is stronger among smaller stocks. The value sleeve also differs from the others. It rescales its sector weightings to match those of its selection universe, on the premise that value-based sector bets are not rewarded over the long term. The fund casts a wide net, typically including at least 80% of the stocks in the selection universe. It reconstitutes quarterly and applies buffer rules to mitigate unnecessary turnover.

Fees The fund's 0.09% expense ratio is among the lowest in the large-blend Morningstar Category and a fraction of what other multifactor funds charge. Therefore, the fund earns a Positive Price Pillar rating. Goldman initially launched this fund with a 0.24% expense ratio and a 0.15% fee waiver, but it has made the 0.09% fee permanent and removed the waiver.

Alternatives

Bronze-rated

Vanguard U.S. Multifactor ETF VFMF (0.18% expense ratio) also has more-potent factor tilts than GSLC. It starts with the stocks in the Russell 3000 Index and divides that universe into three size buckets (large-, mid-, and small-cap). Vanguard throws out the most volatile 20% of stocks (by count) in each of the three buckets. It then ranks the remaining stocks on their combined value, momentum, and quality characteristics and targets stocks representing the highest ranking third of each size group by market value. While this is a rules-based strategy, VFMF does not track an index, so the managers can decide when to rebalance the portfolio.

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