Christine Benz: Hi, I'm Christine Benz from Morningstar.com. Multifactor funds have grown in number, and they have also grown in assets. Joining me to discuss the key criteria to bear in mind when evaluating multifactor funds is Alex Bryan. He is director of passive strategies research for Morningstar in North America.
Alex, thank you so much for being here.
Alex Bryan: Thank you for having me.
Benz: Alex, I want to look at multifactor funds. They have grown rapidly, and they have also proliferated in number as I said. But before we get into how to look at a multifactor fund, let's talk about what a multifactor fund is and before we do that, we need to talk about what a factor is.
Bryan: A factor is basically a characteristic that is predictive of future stock returns or future asset returns. If you think about something like market capitalization, so stock size, historically, smaller stocks have tended to offer higher returns than larger stocks. That's an example of a factor that can help explain the returns that we see in the market.
Benz: A multifactor fund bundles together several different factors, and these funds do this in various ways. They try to capitalize on different factors in different ways, correct?
Bryan: That's right. The basic idea behind a multifactor fund is that it's not a bad idea to diversify across these different factor strategies, because although each factor strategy, like targeting stocks with low valuations, small market capitalization, high-quality, good momentum, all those things have tended to work well over the very long term, but they each go through their own cycle of outperformance and underperformance. The basic idea is by putting these different factors together in a portfolio you can diversify your risk reducing the risk of underperforming for an extended period of time, and we think that that would make it easier to stick with a multifactor fund than to try to go it alone with a single factor.
Benz: A big question before we get any further down the multifactor rabbit hole, let's talk about why one might consider a multifactor fund versus just a very inexpensive total market-capitalization weighted-index product?
Bryan: When I start by saying that an inexpensive market-cap-weighted product is actually not a bad place to be; that should be the default unless you have confidence in something else. I think a multifactor fund can make sense for those who are hoping to earn a higher rate of return than the market. I think that multifactor funds, at least low-cost and well-constructed multifactor funds, can deliver that. The basic idea here is that you get an opportunity to earn higher returns while still diversifying your risk in an effective manner.
Benz: You authored a white paper where you developed a framework for evaluating these multifactor funds. I think that can be useful for investors who might be inclined to take a look at these products. Can you, kind of, walk us through the key factors that you think are important to that analytical process?
Bryan: There's a few key questions that I think it's important for investors who are evaluating these products to ask. Number one, you need to understand what factors these funds are targeting. It's important to stick to funds that are focusing on well-vetted factors and defining them in a very simple and transparent manner.
What do I mean by well-vetted factor? There's only a handful of factors that many academics have looked at and independently determined are robust enough that you would expect that they would continue to work. There is good economic rationale for why we would expect these to work and they are not the just product of data mining. These factors include: low valuations, so being a value investor; momentum, so targeting stocks that have recently outperformed because recent performance tends to persist in the short term; quality, companies with high profitability, strong economic moats tend to offer better performance over the long term; small market capitalization, smaller stocks have tended to outperform; and then low volatility, those stocks have tended to do well on a risk-adjusted basis. You want to stick to funds that kind of focus on those things and define them in a very simple and transparent manner to reduce the risk that you might be buying into something that's overly engineered or data-mined to look really good in the back test but may not do as well going forward.
Looking at the factors that you are targeting. Number two, it's important to look at how aggressively these funds are going after those factors. There is a trade-off here. When you invest with a fund that targets those factors more aggressively or tries to target stronger factor tilts, that increases your potential outperformance, but it also increases your risk of underperformance. Some people who really believe in those factors might be comfortable taking stronger factor tilts and going over more aggressive fund. Others might prefer to rein in those factor bets and be cognizant of how well the fund is going to do relative to the broader market, and for them, maybe a more modest factor fund might be the way to go.
Benz: In the case of the more aggressive funds, that might mean that they would end up with very different sector positions, for example, relative to the broad market, is that correct?
Bryan: That could very well happen. But typically, what it means is that if you are, basically you are applying a higher threshold for stock inclusion. If, for example, I am targeting stocks with low valuations, an aggressive way to do that would be to say let's target the cheapest 10% of the market. Then I am going to get a lot of really risky companies in that portfolio. They may well have higher expected returns, but they are a lot more volatile than if I had, for example, just taken the cheaper half of the overall market where I would get better diversification. That's the key trade-off. It's the amount of risk that you are taking versus the amount of expected outperformance you might be getting.
Benz: One key point of differentiation that you made in your paper was on portfolio construction and you really put the funds into one of two key categories. One, are the funds that use an approach called mixing, and the other would be funds that use an integration approach to portfolio construction. Can you discuss the differences and why that is an important distinction?
Bryan: Mixing is a way of combining different factors. It's basically very similar to an approach that you might take as an investor buying several individual factor funds. It's basically taking several different portfolios that each target stocks on a different factor, and then it combines them together in a single portfolio. The benefit of that approach is it's very simple, it's very easy to do performance attribution to understand where your returns are coming from, and you get pretty good diversification out of that. Typically, with a mixing approach you are going to have less aggressive factor tilts because stocks that look really good on value, for example, will tend to maybe not look quite as good on momentum. A lot of times you might overweight a stock in this bucket, but you might underweight it in a different bucket in your multi-factor portfolio. This is conducive to good diversification and modest factor bet. If you are looking to kind of limit your risk of underperformance, a mixing approach might be a good way to go.
Benz: The integration approach then?
Bryan: Now, the integrated approach is taking a more holistic approach. And basically, what it's doing is, instead of targeting the cheapest stocks, for example, or the stocks with the best momentum, it's looking at stocks that have the best overall combination of factor characteristics. The stocks that look cheap and have good momentum together. Now, the benefit of this approach is that you can achieve stronger factor tilts by avoiding stocks that only look good on one factor characteristic and look really bad on another. That can help you use your capital more effectively to get more potent factor exposures.
Now, the downside is, anytime you take stronger factor tilts, you have a bigger risk of underperformance. You also have more complexity with this approach. And so, it's harder to do performance attribution. It's harder to understand where your returns are coming from and how different stocks got into the portfolio because you are combining all these things together. But overall, we think that both of these approaches can work, but it's just important understand which your fund follows and what that trade-off is.
Benz: You bought a couple of favorite multifactor ETFs that you and the team like. Let's start with one that uses the mixing approach, the first approach that you just talked about.
Bryan: One of the funds that we really like that uses the mixing approach is the Goldman Sachs Active Beta U.S. Large Cap Equity ETF, ticker GSLC. And what this fund does is it starts with a universe that looks very similar to the S&P 500 and then it basically targets stocks that have low valuations, high profitability, low volatility, and good momentum. It's doing all of this while explicitly limiting its expected tracking error to its target universe. This is a way that you can get very similar exposure to the S&P 500 with modest factor bets meaning that you have a chance of outperforming the market by a little bit. But you are also reducing your risk of underperforming because the tilts are relative modest. Now the good thing about this fund is it has a low expense ratio.
Benz: Well, that’s what I was going to ask, because if it's taking just modest bets one would hope that it's expenses would be nice and low.
Bryan: That's right. In fact this fund charges 9 basis points which is the same fee that the SPDR S&P 500 ETF charges. So, yes you are not going to shoot the lights out with this fund, but you are paying a very low fee. We think over a full market cycle this has a good chance to slightly outpace the market.
Benz: And then an example of the integrated approach to portfolio construction.
Bryan: One fund that we really like that uses the integrated approach is iShares Edge MSCI USA Multifactor ETF, ticker LRGF. What this fund does is it looks for stocks with the best overall combination of low valuation, momentum, small size, and high-quality characteristics. Again, it's looking at the intersection of all those different characteristics. This fund takes a lot more active risk than the Goldman Sachs fund. What that means is that it has greater potential upside but also greater potential downside risk. It is following a bit more of a complex approach, it uses an optimization framework to basically maximize exposure to all those things while at the same time trying to match the same risk level of the parent index. There is lot of moving parts there. But we think that this is a really good way of getting very potent exposure to factors that we think will pay off over the long term. Now this fund is a little bit more expensive but its still reasonably priced at 20 basis points. So that’s not that much more than cap weighted alternatives.
Benz: If I am looking at one of these multifactor products, obviously expenses are a key thing to focus on. What should be sort of the cut off, what's too expensive in this realm?
Bryan: It depends, but I would say you would want to, at least in the U.S. market, you wouldn't want to pay a lot more than 20 basis points, because the fund that we just talked about that’s a great fund. In order to justify a fee that’s much higher than that the fund would have to be doing something quite a bit different. In our view there isn't lot out on the market that could justify an expense ratio that was a lot higher than 20 basis points when you have a really good option at 20 basis points. That's kind of where the industry has coalesced a lot of multifactor funds that have been launched in the last few years are priced anywhere between the 9 basis points where the Goldman Sachs fund is and about 30 basis points. Now outside the U.S. funds are a little bit more expensive, but if you are looking at a U.S.-centric fund I would be very skeptical paying anything more than 30 basis points.
Benz: Alex interesting research. Thank you so much for being here to discuss it with us.
Bryan: Thank you for having me.
Benz: Thanks for watching. I'm Christine Benz from Morningstar.com.