That and other questions were posed during a panel discussion, hosted by MarketWatch and sponsored by OppenheimerFunds, that featured some of the nation’s top smart beta/factor investing experts: Todd Rosenbluth, director of ETF and mutual fund research at CFRA; Jack Vogel, the chief investment officer of Alpha Architect; and Erin Gibbs, portfolio manager, equities at SP Investment Advisory Services.
In a world where there are hundreds of smart-beta ETFs, some which focus on single factors such as beta, size, value, momentum or profitability, and some of which focus on multiple factors, is it possible to tell a good smart-beta fund from a less good one?
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“Cheaper often is better”, said Rosenbluth during the discussion. “But when you’re often paying less or you’re paying more you are going to get somewhat different exposure because each of these, at least from the ETF perspective, is tracking an index.”
Cheap is good
So, whether it comes from an SP index, an MCSI index, a Russell index, or a proprietary index, the exposure is going to be quite different, Rosenbluth said.
“We think you need to look not only at the factor”, he said. “But also ‘What is the output of that factor?’ ‘How often is it rebalanced?’ What exposure do you end up getting?’ So, it isn’t as simple as quality is good and momentum is bad. It may very well be the case in certain environments that that is true. But how is quality derived and does make sense in the current environment or not.”
Gibbs said many investors are focused on returns, and whether smart-beta funds are outperforming the benchmark. But that is not the only factor to examine when trying to separate the good from the bad. For instance, a fund may on average outperform the benchmark, but that performance might be the result of two good years of outperformance, and many years of underperformance.
So, the better way to evaluate and select a smart-beta fund would be to examine the risk, the outperformance, the returns, and the “hit rates” — hit rates being, Gibbs said, how many years the smart-beta ETF is “really outperforming” the benchmark.
“Is that average annual return, that one easy number to look at…really just because they had a couple good years and the rest of that period they were really underperforming?” said Gibbs.
Vogel said investors ought to make sure the fund invests according to its stated objective. “Anytime one invests in a fund that is not market-capitalization weighted, that portfolio construction and the characteristics of the portfolio is what, on average, drives returns”, he said. “You want to understand if you’re buying a value fund, a low volatility fund, or a momentum fund, that portfolio should have those types of characteristics.”
Vogel also emphasized that factors don’t outperform each and every year.
“You are going to underperform a lot”, he said. “And there are two ways to deal with that. One is to throw in the towel and become a market-cap weighted investor. Or the other one is to educate your clients. ‘We are allocating some of your funds to a value fund, because over the long term value investing is at a premium relative to growth stocks.’ Factors will go in and out of favor. And trying to time factors is next to near impossible.”
Consider multifactor ETFs
To be fair, that is the risk one runs with single-factor ETFs. There are, however, multifactor ETFs, which combine three or four factors and don’t carry the same risk of underperformance for years on end, said Rosenbluth.
One such fund is the Goldman Sachs ActiveBeta U.S. Large Cap Equity ETF GSLC, +0.16% which has a low expense ratio, 0.9%, and invests in stocks with low valuations, strong momentum, high profitability, and low volatility. “In theory you can smooth out the ride” with this kind of fund, he said.
Consider tilting too
Rosenbluth also suggested that one way to get around the risk of investing in single-factor funds alone is to consider a core-and-satellite approach to your portfolio. Invest in a market-capitalization weighted tied to the Russell 1000 or SP 500, for instance, and then tilt the portfolio “based on a couple factors of your choosing.”
So, for instance, you can reduce risk by investing in a low-volatility factor ETF or amp up your exposure by investing in a momentum factor ETF.
“So you’re taking a bit of a factor bet, but you’re not putting all of your eggs in that factor or two factor basket because something is going to underperform at all times”, he said.
Persistence, information ratio and risk-adjusted returns are key
According Andrew Berkin’s 2016 book “Your Complete Guide to Factor-Based Investing”, an adviser should look at five factors when considering a smart-beta fund:
- Persistence (does the factor historically deliver reasonably reliable returns);
- Pervasiveness (does it, on average, deliver these returns in a variety of locales and asset classes if such tests apply?);
- Robustness (it shouldn’t be dependent on one very specific formulation or fail to work if other related versions are tested);
- Intuitiveness (does it make sense or is it just going by historical performance); and
Gibbs said persistence is a “big one” for SP Investment Advisory Services. She noted that much can be hidden, so advisers should examine whether they can consistently outperform versus having one or two years of outperformance — just as they might with an active manager.
Gibbs said advisers should also examine the information ratio, which Investopedia defines as “a ratio of portfolio returns above the returns of a benchmark — usually an index — to the volatility of those returns. The information ratio measures a portfolio manager’s ability to generate excess returns relative to a benchmark but also attempts to identify the consistency of the investor.”
According to Gibbs, it will be important for advisers to explain to their clients who want to get in and out of smart-beta ETFs very quickly, that these products have the potential to be more volatile than the benchmark.
Gibbs also said risk-adjusted returns are another big component to consider when evaluating the “worthiness” of any factor/smart-beta funds.
Vogel noted that an academic study identified hundreds of factors, with value, momentum and size among the most persistent.
A smart way to add smart-beta funds to an existing portfolio
If you are using style boxes — large value, large growth, small value, small growth — to allocate assets in a client’s portfolio, Rosenbluth suggested adding or tilting your portfolio with ETFs in those boxes.
Of course it depends on the goals of the client, he said. So, for instance, if you have a client nearing retirement who wants to reduce the risk profile, adding a low-volatility ETF may be a way of doing that. On the other hand, if you have a younger client, adding a momentum or revenue factor ETF might be a way of increasing the potential for growth.
He said adding smart-beta ETFs in a thoughtful way, instead of “throwing everything out the window and starting over”, is the more prudent and less taxing way to add such funds to a portfolio.
Given that such funds can increase “concentration risk”, Gibbs urged advisers to be cautious when adding smart-beta funds to a client’s portfolio. She noted that there’s more risk, in particular, when trading small-caps and that many ETFs have a small cap bias.
Further, Gibbs stated it’s important understand the client, how the styles work, and the fees when adding smart-beta ETFs to an existing portfolio.
Vogel, for his part, said there are two things to consider if you’ve decided to move from market-cap weighted investments to smart-beta products:
- Know and understand your client. “Because if your client is going to come in and track you to the SP 500, deviating away from that may not make sense”, he said. “Or, if you would still like to deviate, you should probably make it a smaller portion of the portfolio.”
- Understand how different factors and styles interact with one another. Vogel noted, for instance, that pairing low volatility and momentum ETFs, which aren’t highly correlated, could help boost a portfolio’s overall risk-adjusted performance.
Worth the effort?
The experts also addressed whether adding smart-beta funds does in fact improve risk-adjusted performance.
“The more things that you add into a portfolio you, in theory, increase the diversification but you often also just duplicate some of the efforts”, said Rosenbluth. “So, if you have market-cap weighted and you have a factor-based product there’s probably overlap…the more you put into the mix, the more you are diluting some of what it is you are doing.’
He noted, for instance, that Apple AAPL, +2.90% (AAPL) is going to show up in a quality portfolio as well as in many single-factor products.
Given that, Rosenbluth said advisers might consider using multifactor funds as a way to avoid duplicating efforts and potentially reducing performance.
“That way they are working together with the right intent, instead of you trying to build that yourself and adding that into your own secret sauce” he said. “The goal of this is to make the investment process simpler, tilt you where you want to go, and have a more rule-based approach to it. But you can overcomplicate anything in the investment world.”
For a purely quantitative standpoint, Gibbs said SP Investment Advisory Services isn’t a fan of single-factor investing. “It is very hard to get higher risk-adjusted returns and persistence over time”, she said. “We always look at more than one component. We don’t like to put all our eggs in one basket, in just value or just momentum, and certainly not just in small cap.”
Gibb said SP Investment Advisory Services tends to include the best of breeds in their portfolio, “not just taking your highest-weighted value but maybe value with some momentum.” Those combinations, at least in SP Investment Advisory Services’ research, are the type of styles that tend to outperform on a consistent basis and give you better risk-adjusted returns, she said.
Vogel said the notion of working hard to add smart-beta funds to get very little in return is worth contemplating.
He said one tool worth using, active share, measures how different a portfolio is relative to the market-cap weighted index. A fund with an active share of 0 is a 100% market-cap weighted index while something with a score 100 which is 100% different from the market-cap weighted index. “It is important for the adviser to understand that if I buy one sample fund it’s 70% the market, 30% active and if I buy another it’s 90% active, 10% passive”, he said.
A second tool worth using is visual active share, which plots the holdings of the ETF along certain dimensions such as book-to-market, market capitalization, and the like, compare it to other benchmarks such as the SP 500. “Those tools help advisers ascertain what they are actually buying”, Vogel said.
Another resource to consider for smart-beta ETFs is www.ETF.com, said Rosenbluth.
The biggest risks associated with smart-beta funds? Understanding the product
The experts suggested that investors not knowing what they are buying is among the biggest risks associated smart-beta funds.
“People don’t know what they are really getting inside the portfolio”, said Rosenbluth. “The name of the fund doesn’t tell you what’s inside the portfolio. You could think two things are similar and you buy the cheaper one” but the two funds aren’t similar at all.
Gibbs agreed. “A lot of people don’t really understand what they are investing in”, she said. “They may think that they are buying a smart-beta fund as a proxy for something else. They get the names mixed up.” They may think they are buying a midcap proxy but that is not what they are getting.
Vogel meanwhile suggested that “tracking error” — the risk that the smart-beta ETFs underperform the benchmark — is the biggest risk associated with smart-beta funds.