The concept behind both smart beta and active management is largely the same: Beat passive indexes.
Market cycles often reward certain investment styles, and for the past several years, U.S. large cap growth funds dominated, particularly growth and technology funds.
Certain actively managed exchange-traded funds benefited from this trend, with ARK Invest the poster child for active management in an ETF wrapper. Meanwhile, compared to the S&P 500 and MSCI USA Large Cap Index, the classic factors of small cap, value and quality all underperformed on a five-year basis, as did smart beta fundamental and equal-weighted indexes.
But as economies reopen globally after the pandemic, there’s been a shift in market leadership for the past six months, with classic smart beta and factors mostly outperforming. That’s given some investors new appreciation for smart beta funds, which generally tend to be synonymous with these two approaches.
But is one approach better than the other, or does it depend on market segment, market environment and investors’ goals? Given that many ETF watchers consider smart beta “rules-based active,” how different are the two approaches?
Hard To Beat Large Cap Indexes
Brandon Rakszawski, director, ETF product development at VanEck, doesn’t think one approach is necessarily better than the other, and he says for some market segments—such as U.S. large cap equities—active management rarely outperforms, noting S&P SPIVA reports show on a five-year basis that 75% of large cap funds underperformed the S&P 500.
To dig into whether smart beta or active management gets better results overall, Elisabeth Kashner, director of global fund analytics at FactSet, ran a performance analysis on nongeared equity ETFs, split into four strategy groups, measured over one year, three years and five years.
She also ran a degree of confidence test to measure whether the alpha is statistically different from zero, using the standard threshold of 95% certainty, and separated positive and negative alpha; that is, outperformance and underperformance.
The four groups were plain vanilla, active, strategic/smart beta, which employs security selection and/or weighting schemes involving fundamental or technical analysis; and idiosyncratic, which uses nonmarket cap, nonfundamental and nontechnical methods to select and/or weight securities. Common idiosyncratic strategies include single-exchange selection, such as the Invesco QQQ Trust (QQQ), equal-weighting and socially responsible funds.
After five years, only 4-5% of funds in these strategies had any alpha, and negative alpha outweighed positive across all strategy groups—most heavily for strategic and active funds. For strategic funds, 5.4% produced alpha, with 4.2% underperforming and 1.1% outperforming. Of the active funds, 4.3% produced alpha, all of it negative.
Most significantly, the total amount of alpha—positive or negative—was slight for the four groups.
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“The vast majority of products neither outperformed nor underperformed the broad-based cap-weighted benchmark,” she said. “So is the story that 2.5% [of plain vanilla funds] had negative alpha, or is the story that 96% had no alpha whatsoever?”
Kashner suggests the data shows overwhelming odds that investors won’t get risk-adjusted outperformance or underperformance compared to a broad-based cap-weighted benchmark, but will take on additional active risk. “These statistics make it plain that additional active risk is not compensated, and if anything, is more likely to be punished,” she said.
She adds that fees are a big drag on a fund’s alpha, and help to explain these results. The reason plain vanilla ETFs may have any alpha at all may come down to a methodology difference as to how an issuer may define the sector or industry and stray a bit from the benchmark.
Smart beta’s performance lag and headline-grabbing by active funds like ARK also caused flows to move from smart beta to active funds, especially in 2020, according to FactSet data.
A flows gap analysis, which is the difference between actual fund flows and proportionally allocated segment flows based on starting market share within the segment, shows active ETFs picked up flows from both smart beta and plain vanilla funds.
Whether that continues remains to be seen, but Sal Bruno, chief investment officer at IndexIQ, says active management benefits from “having a good story,” even if evidence doesn’t necessarily support the message.
Like others, he sees a lot of similarity between smart beta and active, with the main difference being stock selection. Factor-based smart beta tries to diversify the stock-specific risk by including as many stocks as possible, while active often makes concentrated bets, he notes. That’s also why active ETFs have a higher cost than smart beta strategies.
Don Bennyhoff, investment committee chair at Portfolio Solutions, considers any nonmarket-cap-weighted approach as active in some way, and says both active management and smart beta have shortcomings.
“The reason that some of these companies are the largest companies is because investors, in aggregate, put money in them. And that’s what’s being reflected … in market cap. Whereas in these fundamental indexes, and everything that’s really not market cap weighted, someone is making a choice to not go with market participants’ views,” he said, noting both give investors higher active risk.
Sarah Abernathy, senior investment analyst at Envestnet, still believes factors get results, based on academic research. She notes that factors go through cycles, too, which is why diversification is important. Value had its worst performance in history recently, but she points out that data on the value premium goes back almost 100 years, so context is important.
Chris Brightman, chief investment officer at Research Associates, says that some of investors’ disinterest in smart beta may be the fault of issuers, as some oversold opportunities in smart beta, especially with the push to use multifactor strategies.
Combining factors is more complex than simpler smart-beta strategies, and issuers sometimes sold ETFs on the idea that a multifactor rules-based approach would slightly, but consistently, outperform the market.
“[When] you’re dealing with real-world issues of transaction costs, you find that the aggregate realized performance of these multifactor strategies doesn’t quite live up to the wonderful backtests that were sold,” he said.
The momentum-driven market of the past few years also worked against rebalancing, a hallmark of strategies such as equal weight, Brightman observes. Rebalancing works when there’s mean reversion in prices and is inherently a value strategy.
Rather than rebalance, market action rewarded those who doubled down. “In a momentum market, that’s exactly the right strategy. But history teaches us that these things tend not to end well,” he said.
John Ingram, chief investment officer and partner at Crestwood Advisors, uses passive, smart beta and active managers in portfolios. Depending on the goal, any of these strategies work.
The problem for retail investors with active ETFs is performance-chasing, usually leading them to buy high and sell low. Instead, he suggests diversification with smart beta ETFs for investors who want to buy something besides passive market-cap-weighted funds.
One of the smart beta funds he’s used for these clients is the Invesco S&P 500 GARP ETF (SPGP), when Ingram wanted to focus on valuation. Ingram might pair it with a quality fund, while adding a defensive fund, such as the iShares MSCI USA Min Vol Factor ETF (USMV). He also used the iShares MSCI USA Momentum Factor ETF (MTUM) in the past. A mix of funds may keep clients from chasing performance.
“We can’t predict where market sentiment is going go,” he said. “And that’s why I think owning that basket is so important, because hopefully it gives investors a little confidence to sort of stick with the program.”