Ever since the 2008 financial crisis, the active versus passive debate has been in full swing, with investors questioning the cost and ultimate value of active stock selection.
Much focus has been squarely placed on the cheap and the cheerful: exchange-traded funds (ETFs) offering efficient, liquid exposure to just about any asset class, at a fraction of the cost of active management.
In a low growth world where every basis point counts, keeping costs in check is key.
At the end of the day, the active versus passive debate is pretty black and white—but as investors have discovered, there’s a whole lot of grey area in between. Some argue that money flooding into major indices makes them securities more expensive and that active managers are better at uncovering value over time.
Cue the development of products aimed squarely at the grey area: ETFs and index funds with an active twist.
At the head of the pack are so-called smart beta ETFs. With roots in Eugene Fama and Kenneth French’s decades old factor model, smart beta ETFs aim to automatically slice and dice the broad index, going beyond the traditional cap-weighted index and focusing instead on specific factors like value, growth, and momentum.
The big advantage here is cost: factor-based ETFs and index funds offer investors a cheap way to go beyond cap-weighting and cut into different areas of the market.
It’s an intriguing proposition for investors. Institutions in particular are taking a close look at how smart beta ETFs could fit in their portfolios. One recent survey showed that smart beta ETFs captured more than 17% of total U.S. ETF equity inflows in 2014, despite representing only 11% of institutional ETF assets. And 36% of institutional investors used smart beta ETFs, up from 24% in 2013, while the mean allocation rose to 13% from 7%.
But smart beta has its critics, Buron Malkiel among them. And most recently a paper from a Wharton University research director crunches the numbers to see if smart beta can really beat their benchmarks. The paper, by Denys Glushkov, is called, “How Smart are “Smart Beta” ETFs? Analysis of Relative Performance and Factor Timing.”
Glushkov looks at 164 U.S. smart beta ETFs from 2003 to 2014 to see whether they beat their benchmarks by tilting to key factors like size, value, momentum, quality, beta, and volatility. His focus is to see whether smart beta ETFs live up to their promise to “harvest factor premiums more efficiently than their traditional cap-weighted counterparts by dynamically exploiting time-variation in factor premiums.”
Although it’s a working paper, Glushkov does not find any evidence of smart beta ETFs significantly outperforming their risk-adjust passive benchmarks. In fact, the final result is a wash, with any positive returns being offset by negative returns from unintended factor bets. At the same time, he finds that risk-adjusted performance isn’t great compared with that of the overall benchmark with passive cap-weighted exposure to market, size, and value factors.
Whether or not you support Glushkov’s conclusion, smart beta has provided a compelling enough approach for many big pension plans to at least start kicking the tires.
And the growing popularity of products like smart beta ETFs shows that investors are still unwilling to take sides in the active versus passive debate. Anything that seeks to address the space in between will continue to grab attention. Which ones can ultimately address that struggle between cost and value, however, is still the big question.