Thanks to lower fees and the never-ending search for noncorrelated sources of alpha, more institutional investors are carving out allocations to factor investing and smart beta strategies. While these strategies are not new, technological advances have allowed managers to crunch more data and develop more robust approaches — at a lower cost than ever. These developments have also improved transparency, which has allowed investors to better understand what makes these strategies tick. In this roundtable discussion Oliver Schupp, Head of Investor Relations, North America at Capital Fund Management (CFM), Bernie Nelson, chief research advisor at Style Analytics, and Phil Tindall, senior director at Willis Towers Watson, discuss what investors need to know, how to allocate to factors and smart beta, how to measure these strategies and what the risks are.
Bernie Nelson: There are probably several drivers behind increased adoption, but I think the elephant in the room is lower fees. Most smart beta and factor products are being positioned between traditional active and very low-cost, nondiscretionary passive, in terms of fees as well as active risk. From a fiduciary perspective, there has to be an obligation to examine whether a lower-fee product could provide an appropriate investment solution.
Oliver Schupp: If you go back 20 years, the strategies that are today called risk premia or alternative beta strategies were the inherent ingredients of a hedge fund. It could be long/short value and momentum investing in equities, it could be merger arb, it could be trend following, or it could be harvesting volatility. Those were hedge fund strategies for which investors happily paid 2 and 20. What I think happened is that these strategies have been researched well and therefore made essentially public. That’s my rationale for why these strategies have been repriced so dramatically, as they have been.
You can assume that no institutional investor pays more than 100 basis points flat without any performance fee for a collection of these risk premia, and I think the real number is lower, 70 or 80 basis points. That’s where the sweet spot is for most of these transactions, and I think it’s been driven by investors who said, “We like the exposure. We don’t want to pay, so if you can do it for that price, great, but otherwise we’ll try it ourselves.” And some do both.
But I think it’s also driven by institutional investors trying to better understand what’s driving their portfolios. They’re saying, “What are the sources of risk and the associated premia that I get rewarded for? If I understand this better, can I control my portfolio in a more meaningful way?”
P&I: How much is the current macro environment contributing?
Phil Tindall: I wouldn’t say so much in the current market environment specifically. However, there is a broader idea of increasing diversification away from traditional market exposures, which has been going on for some time now, perhaps a decade or so. Some of this may be investors who are looking for other sources of return in a low interest rate environment, the so-called reach for yield.
Nelson: Although we are a decade on from the global financial crisis, I think there is still a strong echo from that today in terms of investors’ changed attitude to risk and the demand for more investment transparency. Of course, factor investing was around before the global financial crisis, but the changing environment following the crisis — with low-return expectations, quantitative easing, and a low-yield environment — has encouraged factor-based solutions given their risk-controlled systematic approaches to investing that have evidence-based support. So investors are still trying to seek out extra return above the market return, but now they are more risk averse, more fee conscious and more demanding of transparency into what they are buying than before.
Schupp: One point that sometimes comes up is whether it’s fashionable right now, and will it go away. I think a lot of the interest and demand has been driven not because it’s fashionable, but purely by automation and the growing influence of computing power in investment management. We firmly believe that with ever-growing data and computer power, emotion can be taken out of the process and we can look at just the data. As a quant shop, we believe that robustly analyzing big datasets will allow us to make better decisions going forward. And because we have that computer power and that data, it will lead to a better understanding of what drives all of these portfolios. Many of these themes are inherent in traditional portfolios — value investing, momentum investing, or growth or large cap versus small cap — so it’s not that it’s different from common themes, it’s just implemented in a different way.
P&I: Is a lack of knowledge or understanding on the part of institutional investors hampering the adoption of these strategies? Do you spend a lot of time with clients and potential clients on education?
Nelson: We’ve seen an improvement in understanding over the past few years, which is important because it’s all very well building and proclaiming these strategies, but if the ultimate investor doesn’t understand them then there will be a barrier to usage. Although recent surveys seem to show that investors are getting more confident about these strategies, I think educational challenges remain. We’ve seen many of the largest investment managers investing in education, including headlining at seminars, conferences and webinars, to bring clients and intermediaries up to speed. I don’t see that slowing down.
Schupp: We spend a fair amount of time on education and we find that there are two main streams. The first is investors who try to better understand their factor exposure or the drivers of their returns. And we like to see investors looking at the exposures in their portfolio and the underlying risks that drive those returns, so we’re involved in those conversations and try to help further that education and that dialogue.
The other one is to have realistic expectations. What investors need to understand is that you need to have realistic scenarios of what may happen. So drawdowns of a certain length and a certain size are commensurate with the Sharpe ratio assumption that you have. This is not the same as an innovative alpha-seeking strategy where you aim for a Sharpe of 1.5 or higher and assume that it mostly goes up because that’s the nature of it. Here you need to accept that drawdowns are possible. That is something that we need to focus on because otherwise you set unrealistic expectations.
Tindall: I agree that it’s about understanding the sources of return and risk. The jury is still out on the rationale for a lot of smart beta factors, whether there’s a behavioral effect or compensation for risk or some combination of the both. But either way, it’s better for investors to have an upfront understanding of what they’re getting.
P&I: Are these strategies best suited for larger or smaller institutional investors, or does it matter?
Schupp: For bigger investors, it is typically going into what they often call their diversified strategies bucket. And one of the things that I believe most of these alternative beta products have done pretty well is having relatively low correlation to traditional assets, in particular equities. I think what drives some of the demand is that if you have this bucket in your asset allocation, there is only so much you can actually do. Many of the alpha-seeking, low-correlated managers are capacity constrained, so investors with big portfolios are finding low-correlated strategies and the capacity they need in other areas such as alternative beta.
On the flipside, we do find smaller investors who show interest in this type of product as a replacement for traditional hedge funds. If you are fee sensitive and don’t have the resources to run a bigger program or deal with a vast consulting network then alternative beta products can act a bit like a diversified hedge fund portfolio.
Nelson: We see increasing interest from both large and small institutional investors to analyze these types of strategies alongside more traditional active and passive approaches. Holdings-based portfolio analysis that includes granular factor-based insights is becoming more available and more affordable for smaller, lower-resourced investors. Of course, some asset owners rely on consultants, but we are now seeing smaller asset owners analyzing and comparing these strategies to help satisfy their fiduciary responsibilities more directly.
Our goal is to democratize the analysis of these strategies and to provide factor insights on funds that can be used by all institutional investors, large or small. In fact, we recently launched a new managed-services solution for qualified asset owners, called Factors as a Service, or FaaS, which provides full data management and the creation of factor style reports.
We intend to make it simpler and easier for smaller asset owners to benefit from the deep insights possible through the use of a factor lens.
P&I: How should investors approach the idea of adopting factor and smart beta strategies?
Tindall: Investors should consider factor investing as a strategic decision. By and large, investors own the factor decision, the smart beta decision. Future performance is really with the investor and not with the fund manager, and therefore no different to investing in an asset class such as property or bonds or whatever. So there is upfront work to understand the drivers of performance, the environments when factors may or may not work and the timeframes for performance. Factors can perform reasonably [flatly] or poorly over quite long periods of time. Just as with the equity or bond markets, you’ve got to pre-analyze the outcome, if you like, and be prepared to react to it, but not overreact to it.
In terms of allocation, if you’re going to do all that work you need to make a reasonable allocation to make it worthwhile. It’s hard to say what’s material. I wouldn’t rely on some technical optimization, which is too sensitive to assumptions. I’d say you should allocate at least 10% to 20% of your equity portfolio to smart beta if you’re going to do it at all, but it depends on how much you’ve got in equities and how much traditional active management is used. If you don’t have much in equities, you could allocate proportionately more in smart beta to make a bigger difference at the bottom-line portfolio level.
Nelson: The first thing to do is to make sure you understand what’s in any individual strategy or fund. Not just broad factor themes like value, quality and volatility, but also what type of value, quality or volatility and making sure you are not just confusing sectors or countries with factors. Different choices of underlying measures can give different performance characteristics, such as price-to-book versus free cash flow yield, as distinct value factors can perform quite differently. And sectors can often masquerade as factors. Then of course you have to consider how to allocate to a fund or several funds alongside existing active and passive strategies. In theory, you can use risk models to construct an “optimal” portfolio, but in practice we have found that there’s less of that going on than you might think. Rather than pressing a button to get a single answer from a model, many investors use more heuristic transparent approaches, such as a “what-if” process to check the factor and risk profiles of different fund combinations.
P&I: What are best practices when it comes to due diligence of managers?
Schupp: In our experience, the approach that our investors and allocators are following is very much the same as they do for normal hedge fund investing. You start with presentations, you send them the data, you go into questionnaires both on the investment side and on the operational side. Then they usually send their team over, or their consultant, and you have a deep dive on-site, where you would meet with all relevant teams — from the research portfolio management side all the way to IT and infrastructure — to try and get a sense of who you are dealing with, and how they are working and implementing these portfolios. That’s what we found is the most standard approach. Clients who rely heavily on consultants have their consultant pretty much do all of that. It’s the allocators who are more hands on and involved and make final decisions, who would typically come alongside their consultant, and then the ones who don’t use consultants obviously do it themselves. I find it’s fairly established, and I think the best practices are the same as for traditional hedge fund investing.
Tindall: In terms of our process, it’s no different than traditional active management in a high-level sense, but ultimately there is less dependence on manager alpha skill and more on implementation skill in delivering on factor exposures. The investor is doing much of the upfront work in deciding on factor allocations, so to some extent the manager selection process is less focused on the alpha skill element, but it’s not zero. We always look for managers who are thoughtful about the way they build smart beta portfolios. They’ve got experience in running it, they’ve got good trading capabilities and they’re a stable organization. It’s sort of most of the same success factors that we use across all our managers. It’s just that the context is a little bit different.
P&I: Does factor and smart beta investing require custom benchmarks?
Schupp: There isn’t really a good way to benchmark this today. You have some indices that are put together and based on peer managers so that gives you a sense. However they tend to be rather different in their implementation so it’s questionable how good that is, but it does give you an indication. I continue to think that if someone came out and actually tried to do something that was a bit more objective and presented more of a benchmark concept it would serve the industry quite well. However we’re mostly working with institutional investors, and they have very realistic expectations and good understanding of how these strategies fit into their portfolio.
Nelson: You have to analyze the strategies using a consistent approach regardless of whether a fund is index, active, smart beta or factor based, or whatever it is. Ultimately the choice of benchmark should relate to the investor’s performance objective and not just what the product provider proclaims as the reference index for their particular fund.
We have found that investors will look at different reference benchmarks. Of course, analyzing against the stated performance objective of the fund, often a custom index, can help identify whether active risk is appropriate for the investor, but analysis versus a broad reference index is also helpful to identify clear proof statements of the overall factor intention of a fund, perhaps in relation to the investor’s broader investment objective.
For example, a U.S. large-cap value equity fund may state its benchmark as the Russell 1000 Value index. Analyzed against that index, the factor tilt may show that this fund has a negative tilt on value indicating, correctly, that it might be less value on certain factors compared to the index. But does that mean it’s not exposed to value? Not necessarily. You won’t know for sure unless you analyze the same fund against a broader index such as the Russell 1000 or Russell 3000. Specifically, the fund may have a significantly negative price-to-book tilt versus the Russell 1000 Value index, indicating the fund is more expensive than the index. But the Russell 1000 Value index is narrowly defined with an emphasis on price-to-book, so if a factor or smart beta fund doesn’t emphasize price-to-book in its definition of value, it’s going to look expensive relative to that index. However, other legitimate value measures, such as free cash flow yield or EBITDA to enterprise value, might have positive tilts versus even the Russell 1000 Value index. It can get confusing quickly if you don’t keep one foot on the ground with proof statements against broad-based as well as custom indexes. And being able to do this quickly for thousands of funds is key.
Tindall: In terms of benchmarks, a lot of people link smart beta with index investing, but we don’t think that an index is needed to define smart beta. The underlying principle is capturing a factor or effect in a rules-based way. That said, clients can gain comfort from some reference to an index because it is independent of the specific way they are implementing it.
We tend to have indices that our clients look at next to the actual strategy itself. Again, it’s about confidence in not just the manager’s performance, but also the factor and effect that [the client has] bought into. What we try to avoid is getting hooked on tracking error, because its absolute risk and return at the portfolio level that’s important to an investor, not some benchmark index you put in in the middle of that.
P&I: What are the risks of pursuing these strategies?
Nelson: Even for institutional investors that do understand that factors can underperform for long periods there are still risks in making sure their funds are oriented to the specific factors that they really care about. For example, in a high-quality, low-volatility strategy, do you know what measures have been used to define quality and volatility, and do you understand how deliberately the fund is oriented to those measures? Do you understand the difference in downside protection from low volatility versus quality, and how those factors have performed through market cycles? When you are verifying the obvious factors of interest, often included in the fund’s name, you still have to watch how you are oriented to other factors for unintended bets, as well as check sector, country and stock selection exposures. There is essentially no such thing as a “single factor” strategy. You have to keep your eye on several balls at once, from a risk perspective, for all strategies.
Tindall: First of all, smart beta strategies are not risk-free. Factors can, as we said before, perform either flattish or poorly for quite long periods of time — for many years, in fact. So you’ve got to be prepared for that. The second thing that keeps us thinking is whether these factors become overused and crowded. It’s one of those million-dollar questions really. It might appear that everyone is buying into them, but it’s still rational to expect a return as compensation for risk. In addition, there has been a move from traditional active management, so some of the smart beta assets are likely to have come from that side. ■