Hougan: Are any smart-beta strategies getting crowded? How would you tell if they were?
Mazza: Investors should be cognizant of the potential for crowding in particular factors, but I think we’re a long way away from the point where we’re seeing the underlying anomaly for any particular factor being arbitraged away.
If a factor is highly valued, I may need to dampen my expectations for future returns. But if the underlying driver of the factor still exists, the long-term outcome should be there.
Beyond that, there’s a lot of exciting work being done by academics and practitioners on how different factors perform in different macroeconomic environments. That’s definitely a space worth watching.
Hougan: How would we know if an anomaly was arbitraged away?
Mazza: I’m a big believer in the behavioral drivers of factor returns, and as human beings, I’m skeptical that many of these behavioral drivers are going away. Will we no longer be subject to the lottery effect? Will we no longer chase glory stocks at the expense of more mundane stocks? I doubt it.
We have seen certain factors getting arbitraged away in the past by regulation. We saw this in the 1990s with the estimate revision factor. It was a big focus of investors in the 1990s, but after the passage of Regulation FD in 2000, its performance has been spottier. There’s a good reason for that, because the information underlying that factor is now evenly distributed. Those types of changes are worth monitoring.
Hougan: How should investors evaluate smart-beta strategies?
Mazza: You want to borrow from the techniques people have used to evaluate active managers—the classic “five P’s”: people, philosophy, process, performance and price. But you need to use those P’s differently.
In the case of people, ask: What firm is sponsoring the ETF, and who is the index provider? For philosophy, ask whether there’s credible evidence that some particular premia—value, momentum, etc.—exists, and ask if it’s being measured appropriately. For process, you really want to dig into the index methodology and see if it makes sense. And importantly, you want to do all that before you get to performance or price.
With performance—if it’s real-world performance—ask yourself if it delivers what was intended by the portfolio’s design. With a new product, you can look at the backtest, but you’ll want to take a “trust but verify” approach, and look closely at the underlying methodology.
Finally, with price, you want to look at the total cost of ownership: the bid/ask spread, the expense ratio and the premium/discount variability.
And of course, overall, I’ll focus on how the product fits in a portfolio long term. That way, I can still be happy with it even if the short-term outcome goes against me.
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