Building an exchange-traded fund can be like baking a layer cake. But when the layers are “factors,” the cake may not be as sweet as it looks.
Factors are ways of describing how stocks behave, and they form the basis for 518 ETFs with $759 billion in assets, according to FactSet Research Systems. Multifactor ETFs combine fundamental elements (like value and growth) with technical stock attributes such as price momentum and volatility.
Value is perhaps the best-known factor, but researchers have identified hundreds of other “positive” factors that appear to produce above-average returns and lower risk, or deliver some combination of superior “risk-adjusted” returns. One might emphasize stocks with positive earnings revisions, for instance, or dividend growth. Value, quality, momentum, and low volatility have some of the strongest academic records. Small market value has also been identified as a positive factor, though the first studies to identify the size factor relied on faulty data that may have overstated the size effect (after adjusting for risk).
The idea behind multifactor ETFs is that it’s better to own several factors than one. Factor performance comes in cycles that may last weeks, months, or years. Combining factors in one basket eliminates the market-timing challenge; when one factor falls behind, another is likely to outperform. Holding too many factors can water down returns, resulting in an expensive index fund that largely tracks the broader market. But get the mix right, and a multifactor ETF should outperform over a full market cycle, says Steve Sachs, head of ETF Capital Markets at Goldman Sachs . “The whole idea of combining factors is that over time they tend to work well together,” he says.
Multifactor ETFs generally aren’t designed to outperform by much, though. Big institutional investors often want ETFs that don’t deviate from the broad-market benchmarks by much. Rather, they’re looking for an inexpensive side bet that can edge out the broad market when a particular factor or group is outperforming.
Yet even by that low bar, multifactor ETFs can be disappointing. The largest one, the $4.8 billion Goldman Sachs ActiveBeta U.S. Large Cap Equity ETF (GSLC), launched in September 2015, comprises four subindexes reflecting stocks that score well for momentum, quality, low volatility, or value. It has an expense ratio of 0.09%, making it competitive with ultralow-cost index funds.
Yet it has returned an annualized 13.5% since inception, trailing the 14.6% return of the S&P 500 index, according to FactSet. The ETF got off to a bad start, trailing the S&P 500 by 3.2 percentage points in 2016. That was a year in which every major factor underperformed, says Sachs, adding that the ETF has done well since then. But its performance has been uneven; it lagged behind the S&P 500 slightly in 2017, outperformed by 0.3 points in 2018, and is running 0.2 points behind this year.
Some ETFs take a dynamic approach to factors; they tactically rotate among them, aiming to avoid the laggards and emphasize market leaders. The recently launched BlackRock U.S. Equity Factor Rotation ETF (DYNF), for instance, adjusts its factor weightings based on variables such as the factor’s relative strength in the market, valuation (whether it looks cheap or expensive), and the business cycle. The ETF has an expense ratio of 0.3%, however, making it three times as pricey as Goldman’s multifactor large-cap ETF.
Whatever the strategy, investors should evaluate how much tracking error the fund is taking in a bid to outperform. The greater the tracking error, the more an ETF may be swinging for the fences—or strike out trying. Investors should also view an ETF’s marketing materials with a generous pinch of salt. Fund sponsors often show strong results for their products, based on “back-tests” of their underlying indexes. But the results are prone to manipulation, or “data mining,” indicating superior returns based on a time frame that the researchers happen to examine.
Some studies suggest that integrating factors at the stock level may be more effective than mixing subindexes. Harindra de Silva, a quantitative portfolio manager with Wells Fargo , says that if you build a portfolio of stocks that individually score well for the major factors, the maximum gain over a market benchmark would be about two percentage points a year, on average. Yet to achieve that two-point edge, investors would need to short sell stocks that score poorly on factor attributes, potentially imposing additional cost and risk. Without that short component, the multifactor edge drops to 1.6%, he says.
Factors may lose even more punch in portfolios based on subindexes (rather than integrating factors at the stock level). The maximum gain with that method is 0.80 percentage points, on average, de Silva says. None of this accounts for fees, transaction costs, or taxes, all of which shave a bit off the top.
Even if multifactor ETFs don’t beat the market consistently, they offer diversification benefits over a standard large-cap index fund, says Joe Smith, deputy chief investment officer of CLS Investments, an advisory firm based in Omaha, Neb. A handful of big tech stocks are powering the market, he says, and valuations overall look stretched. Multifactor ETFs can remove some of that concentration risk by diversifying across sectors with different attributes of value, growth, momentum and volatility. “The more balance between the factors in a portfolio, the better,” he says.
ETFs that he favors include SPDR MSCI USA StrategicFactors (QUS), JPMorgan Diversified Return International Equity (JPIN), John Hancock Multifactor Mid Cap (JHMM), and Xtrackers Russell 1000 US QARP (QARP). He doesn’t expect any of these ETFs to be consistent winners. But he likes them for their risk controls and emphasis on a handful of factors, without going overboard with one ingredient. Ideally, they’ll layer the cake in a way that makes for sweeter returns.
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