Today’s rules-based investing models were supposed to take the guesswork out of Ben Graham’s age-old principle of using “established standards of value” in deciding what to own. In practice, some argue, they’ve made things more confusing.
Take three well-known products that aim to replicate that tried-and-true strategy of buying low. Depending on the one you look at, U.S. value stocks are either up 1 percent in 2018, down 6 percent, or down 8 percent. That’s great, if you happen to own the one that’s rising, which is an index from Deutsche Bank. But if you owned an ETF tracking the Russell 1000 Value Index? Not so much.
It’s not just an academic exercise. With the rise of low-cost passive investing, billions of dollars have poured into so-called factor funds and ETFs, which use sophisticated, math-based formulas to pick stocks with predefined characteristics. Whether value, growth, momentum or size, they’re designed to provide steady exposure and remain immune to subjective (and often faulty) human judgments. But as the disparities show, small tweaks in how you define a strategy can make a big difference in how it performs.
“You’re telling yourself that what you’re actually doing is passive, but you’re actually doing something active, and potentially doing it in a poorly informed way,” said Eddie Perkin, chief equity investment officer at Eaton Vance. “You’re relying on someone else’s definition.”
Those definitions aren’t secrets -- they’re in prospectuses for all to see. And nobody’s saying these funds and indexes aren’t behaving exactly as they’re designed, usually with a variety of risk profiles. The issue is their proliferation: so many funds track so many different styles nowadays that some critics see a return to the same random walk of unpredictable outcomes that passive was supposed to address.
Others just see an industry providing clients with lots of options.
“We’re not here to be a universal cohesive marketplace. We’re here to offer choice, and choice requires research and thinking,” said Simon Mott, head of marketing at HANetf, a European ETF provider, and former global head of ETF and wealth management marketing for FTSE Russell. “Things can be pretty similar, but they offer a different flavor. It’s up to the investor to look at that.”
In theory, any investment that tries to mimic the performance of an index can be considered rules-based. In that way, the entire $5 trillion industry of index funds and ETFs is just one grand exercise in quantitative finance.
But as competition shrinks profits on plain-vanilla passive funds, money managers have made a small fortune selling costlier quant versions, marketed to individuals as smart-beta or factor ETFs. These funds, built to track indexes that use quantitative analysis to precisely target distinct styles like value and momentum, have in a few short years amassed over $1 trillion.
It’s within these strategies, which often carry the stamp of scientific certitude, where the gaps in returns often open up.
Take growth for example. Among 81 ETFs in that admittedly broad category, the best and worst of these funds this year are separated by 26 percentage points, data compiled by Bloomberg show. Among 67 value ETFs, the gap is 13 percentage points. Sure, the definitions incorporate a host of methodologies and sizes, but all of them share elements of the value credo of buying cheap.
It might seem odd to see returns on lookalike quant-driven products diverge so sharply. But according to Meb Faber, chief investment officer at Cambria Investment Management, the phenomenon is “totally normal” as fund managers try to differentiate themselves in an increasingly crowded market.