Ang: Factors As An Evolution

December 11, 2017

Andre AngAndrew Ang heads up BlackRock’s factor-based strategies group. He recently posted a blog, “The Five W’s Of Style Factors,” about the key questions to consider when looking at factors. In it, he discusses how factor analysis represents an evolution beyond the Morningstar style boxes that dominated the investment conversation for so many years. He spoke with in more depth about some of the points he made. There’s so much talk about the factor zoo, where there's hundreds of factors, but BlackRock has it narrowed down to just five—value, momentum, quality, size and minimum volatility. How that list was reached?

Andrew Ang: The first, most important, criterion is there has to be a compelling economic rationale. Are these [factors] generating returns through a reward for bearing risk? Do they arise from structural impediments, or investors' behavioral bias? This also gives us confidence that these factors, even though they've been around for a long time—that's our second checklist item—are going to be there for a long time to come.

The third checklist point is there has to be a differentiating source of returns, in particular, especially to plain-vanilla stocks and bonds, and ideally, the factors should have low correlations relative to each other.

The final one is a particular choice we've taken at BlackRock but that is not universal: We want to provide low cost to our investors. Therefore, these factors have to be scalable.

Once you take these four criteria and you pass potentially dozens or sometimes hundreds of factors through them, there is only a handful left, and they're the ones you mentioned. One of the big arguments I've seen against multifactor ETFs is that they're a less efficient way to get broad-market exposure, because once you add in all the different factors, it just becomes a muddle. How can investors avoid this outcome?

Ang: As of the end of September, there are 198 multifactor ETFs, and they're not all created the same.

There are some for which I think your critique is extremely valid, where if you're not careful in adding together these factors, you’re going to come out with the market. That's the outcome you don't want.

If you want to design an intelligent multifactor smart-beta offering, what you need is stocks that are cheap, trending and high quality. An inferior approach would cause some of these factor exposures to cancel each other out.

A bottom-up approach assesses each different stock on these criteria—is it cheap, is it trending, does it have quality earnings, is the stock small and more nimble—and you assess all of those individually.

One way to look at this is if you were to construct a fantasy sports team. In baseball, you really want people who are all-rounders, the utility player. To do that, you have to look at each individual stock and build up the portfolio from there. If you've got talent at hitting the ball out of the ballpark, that could be value, and that would be really great.

And you might have another skill like being able to catch a ball; that might be momentum. But what you really want is the guy who can hit, catch, run and field. You want the all-rounder. To make sure you collect all of those skills, you should be looking at a bottom-up approach and assessing each individual player.


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