Smart Beta

Smart beta is in vogue. The origins of the phrase are a bit vague, but mention it and you're sure to start a conversation with your investment colleagues. Beta, of course, refers to the return on an investment portfolio that is down to overall market performance. Smart beta, on the other hand, is an umbrella term for rules-based investment strategies that do not take as their starting point traditional market capitalization-weighted indexes. Many use alternative weighting systems based on measures, often known as factors, such as volatility, value or dividends. These systems can range from the naïve, as in equal-weighted indexes, to the complex, such as fundamentally weighted indexes.

Investors have been attracted to smart beta because it offers opportunities to better refine their portfolios and protect against the risks associated with volatile financial markets. Yet this remains a new area of the investment landscape and investors are still learning about the best ways to use smart beta strategies in their portfolios. In order to get some answers to investor questions,

Pensions & Investments asked three market professionals to explain what makes beta smart.

Rolf Agather: We define smart beta fairly broadly. It's any number of transparent, rules-based indexes that are providing exposure to systematic factors or strategies. These include different market segments or alternatively weighted strategies. It ranges from beyond cap-weighted, passive but stops short of full stock-picking or active quantitative models.

The key element is the notion that these strategies are transparent. We disclose the various rules that we use to manage the indexes and do not use any discretion in applying these rules. Regardless of market conditions, we follow the rules we stated up front.

Dan Draper: Smart beta is a methodology that can be used to alter a risk-adjusted return profile compared to traditional benchmarks in pursuit of risk-adjusted outperformance. But, as Rolf says, in a transparent, rules-based, formulaic way. The term “factor-based” is important. If an investor takes a performance attribution view, it used to be 20 or 30 years ago that style factors, for example value and growth, were buried inside of some performance outcome. Now, thanks to the work by Fama-French, these factors can be isolated and then carved out of the total risk return profile. Then such factors can be repackaged, as a way to harvest or pursue investment performance in a more systematic manner.

Kal Ghayur: Smart beta really boils down to gaining an efficient exposure to what we call equity common factors. As Dan said, these factors are things like value, momentum, low volatility, quality and size. These are the five common factors used in the practitioner world and mentioned in the academic literature, and we would agree represent what are known as common factors. Smart beta evolved out of the desire of investors to capture common factors in a more direct and risk-controlled manner.

Today in the smart beta space, we see two types of approaches. One is an index-based approach that seeks to provide exposure to common factors through rules-based indices, often packaged in off-the-shelf offerings. The second is a bespoke approach, where clients can customize their exposure to individual or specific combinations of common factors, thus allowing for tracking error (relative to a policy benchmark) specification as well. Both approaches seek to provide exposure to common factors, and both are a potential substitute for market cap-weighted indices. Ultimately, a client's need or desire for customization may drive their preference for one approach over another.

Dan Draper: Invesco PowerShares contracts with providers, like NASDAQ, Morningstar or S&P who design and produce indexes for us. While our ETFs passively track these indexes, we view the process of generating the rules within a smart beta index as extremely active up until the point of actual implementation in trading. As part of the index methodology process, clients provide input on single-risk factors, or a combination of risk factors they are looking to harvest. This demand-driven need, combined with the process of identifying how these factors correlate together, and then transporting that within a portfolio context, is an extremely active process in our view — particularly when wrapped in an ETF. But, when the transparent index is determined and the rules are set, the ETF will be passively managed.

Kal Ghayur: The background to this question is, what is your reference point? You can only talk about active or passive once you have a reference point. So one argument that could be made is that smart beta is active because it chooses weighting schemes that are different than cap weighting, and therefore it represents an active management decision.

Is cap weighting the right reference point? Because you can see a case where an investor says that cap weighting is inefficient, therefore I'm going to view the minimum variance portfolio as my benchmark. It's a better way of gaining exposure to the equity risk premium. Now, the cap-weighted portfolio is active relative to the minimum variance portfolio.

But there are a few arguments that could be made in favor of the cap-weighted market portfolio as being the reference portfolio. One argument is that it is macro-consistent, meaning that everyone can hold that portfolio. Second, it's the cheapest and most transparent way of gaining exposure to the equity risk premium. Third is the argument for performance benchmarking. Market prices reflect consensus expectations about future returns. So it would be fair to say that a cap-weighted market portfolio represents the consensus of what investors think. If someone believes that they can do better than the consensus, their performance should be compared to the cap-weighted portfolio. In that sense, the cap-weighted portfolio does become the performance benchmark for any strategy.

Rolf Agather: That's a good point. I agree that these are active strategies. Though I would say it's becoming increasingly difficult to have this sort of binary categorization, either being active or passive. But if you had to choose one, it would definitely be active.

A truly passive investor is willing to accept whatever the market bears, up or down, with whatever inefficiencies or concentrations that are created. So it's important to recognize with smart beta strategies, you are deviating from the market, so you are either implicitly or explicitly taking a view. There is a chance that you may underperform or outperform the benchmark.

It's important to recognize that as much as we think of smart beta strategies as being active, there are limits. It stops short of true active strategies like stock-picking or quant models. We don't use any sort of discretion in the day-to-day operation of our index. There is a passive component in that the indexes are managed in a very systematic way.

Kal Ghayur: We would argue that smart beta strategies are a hybrid solution, meaning that they are more efficient than cap-weighting. In that sense, they are more efficient, or active, than passive. But at the same time, they are more passive than the traditional active management.

Rolf Agather: In traditional active strategies, you would expect some sort of explicit forecast. That's what you are paying for, presumably — smart people with robust forecasting models who are convinced that they can make the right calls on where the market is going. We aren't doing that with smart beta. We're really not making any sort of forecast. We are leaving that up to you, the investor, and giving you the tools to express a view or take a position on where the market is going.

Dan Draper: In many ways, smart beta deconstructs a lot of factors and performance attributes that were historically just broadly bundled. Today, through a transparent ETF, we can divide these up and price them appropriately. That empowers us to divide up the total risk-return budget into a variety of ETFs that portfolio managers, advisors and even traders to some degree can repackage to pursue a better probability of reaching future wealth goals.

Rolf Agather: While all of us have described a broader picture when it comes to smart beta, different strategies will behave differently depending on the market environment. An example would be a low-volatility strategy that has clearly been designed to help dampen the effect of down or bear markets. So you would expect low-volatility strategies to do better in down markets. The flip side is that they may not do as well in up markets because of the way they are constructed.

An alternative weighting strategy like fundamental or equal weighting has generally been shown to produce an exposure to value and small- to mid-cap stocks. So in cases where value is outperforming, or small- and mid-cap stocks are outperforming, you would expect a fundamental weighting strategy potentially to do better than its cap-weighted counterpart.

Kal Ghayur: If smart beta is defined as being the capture of common factors in the end, then our view is that investors should implement a diversified strategy with respect to common factors. The argument here is that common factors individually experience a lot of cyclicality. So value, for instance, can underperform the market, and that underperformance can be very pronounced and very prolonged. Similar cycles are evident in momentum, low volatility, quality, small cap and so on. The great thing about common factors, which investors may not be focusing on, is that they have low or even negative correlations. So factor diversification strategies dominate individual factors.

Dan Draper: Just to add a bit of nuance here, thinking about correlation or lack of correlation, each investor — short-term trader up to long-term pension fund manager — needs to determine what they are trying to achieve. We want to move investors away from the concept of this one smart beta strategy succeeds or fails vs. the market cap-weighted benchmark over some period of time.

The real key is the portfolio allocation strategy or trading allocation strategy. What we at Invesco PowerShares are trying to do is to build an ETF toolkit that allows investors to express market views within a larger portfolio or trading strategy.

Dan Draper: Recent market conditions, with artificial monetary policy that has raised correlations high across most major asset classes and lowered volatility by historical standards, have been almost nirvana for market cap-weighted investors. When the market is just moving up and down together, that's when you'd expect market cap-weighted benchmarks to perform very well. And they have.

Today, however, many market participants are looking ahead and feel that interest rates and volatility may go up. So there may be more opportunities to tactically adjust portfolios using smart beta to better capture risk premium. There is also a long-term case for individuals, advisors and portfolio managers to use smart beta even if the correlations remain the same over the next five to 10 years.

Kal Ghayur: Traditionally, investors have approached portfolio construction and structuring from an alpha-beta perspective. What investors have realized today is that active management returns are actually comprised of three components, not just two. One is the market itself, beta. The second component is the exposures that a manager has to common factors. And the third is the return that the manager generates beyond the exposures to the market and common factors. For simplicity's sake, let's call it stock selection — how skilled the manager is at selecting individual stocks.

What both practitioners and academics have realized is that when active management returns are decomposed in this way, the number of managers who can actually provide returns that go beyond their common factor exposures is quite limited. The question then arises, if a value manager is only giving me exposure to value and does not possess stock selection skill within value, why am I paying active management fees to capture value when I can capture value directly through smart beta products?

Rolf Agather: I would agree that there is a case for using smart beta to make a relatively fixed long-term allocation based on some particular belief. Low volatility is a good example. An investor may want to participate in equity markets, but not be comfortable with the volatility that they've seen recently. So they might make a strategic and fairly meaningful allocation to a low-volatility strategy for a long period.

It's also possible to have a more dynamic or tactical use. This is one idea that I think investors need to approach with a healthy dose of caution. Factors can change their behavior depending on market cycles. So as markets are moving, different factors can behave very differently.

Anyone thinking of using smart beta strategies more dynamically needs to have the capability to understand their situation. So while we definitely highlight this more dynamic or tactical use as something that's a potential, we stress that it is not for the faint of heart. It requires tremendous capability to manage either specific factor exposures or broader strategies in a very dynamic way.

Kal Ghayur: Historically, if an investor wanted to implement value investing, they had to go to an active manager. If they wanted momentum investing, they had to go to an active manager. But today, there is this additional implementation option that says you don't have to hire active managers to gain exposure to common factors. You have another alternative that you may wish to consider, which is using smart beta strategies.

So we see investors moving toward a more efficient way to structure portfolios. Rather than saying there are two components — alpha and beta — they now see that there are three components. One is market beta, cap-weighted indexes. The second is factor betas or smart betas, which give exposure to the common factors. Then the third is return from active management, which is driven by manager skill, which goes beyond common factor exposures.

The efficiency is gained through two levels of diversification. The first layer is in the common factor capture, because factor diversification strategies dominate individual factors. The second layer comes from hiring active managers that are able to deliver returns that are uncorrelated to common factor returns. These two layers of diversification should, in the end, result in much higher efficiency.

Dan Draper: Right now, we see investors searching for ways to enhance income. Smart beta can be an efficient way to do that. Take, for instance, baby boomers or others that have a shorter investment time horizon. These investors likely can't live with high levels of volatility, but still need some level of capital appreciation and growth, particularly in a low interest-rate environment. Should they need equity exposure but can't live with the volatility of an S&P 500 or comparable index, a low-volatility strategy may provide a higher probability of achieving their goals efficiently. We also see investors with greater risk appetites taking advantage of momentum through smart beta because it provides exposure to the market above the market benchmark.

Rolf Agather: We see investors using smart beta as a way to manage risks that might be created because of other forms of management. In particular at Russell, as we help clients to bring together a wide variety of active managers, we see that this approach will generally have a higher exposure to volatility than many investors want. Active managers tend to like to buy higher-volatility stocks vs. lower-volatility stocks. So you might be overexposed to volatility. One smart beta application would be to use the low-volatility product to offset that.

Dan Draper: Since the development of modern portfolio theory starting in the 1950s, and the introduction of the concept of mean variance, investors have been trying to properly attribute risk. The factors we are describing — low volatility, high momentum, high beta — are parts of the overall risk package. In the past, investors had only one choice — to either buy or not buy the whole package without knowing what the individual parts cost or, crucially, how the correlations between the parts change the overall price.

Now we can unbundle the package, price the individual parts and see the correlations between them through the ETF wrapper. When investors buy the bundled package, frankly, there are probably things in there they don't need or are actually working against them. So smart beta allows investors to refine their performance attribution to help ensure that they are buying the right collection of individual parts at a reasonable cost.

Rolf Agather: Factors are really systematic return drivers. Obviously the most famous is just beta itself. The market effect was identified many years ago as something that does drive equities. There are other factors, too. Knowing what they are helps you more precisely control the exposure in your portfolio to achieve more diversification, or a particular outcome.

It's important to notice that there are actually a number of these return drivers, but just a subset that are generally acknowledged to have some sort of risk premia, meaning that you are rewarded with excess return over time. The four we look at are value, momentum, quality and volatility because they have been shown to provide some excess return over long periods of time.

Kal Ghayur: Factor diversification is powerful, so we suggest using it. There is a cost to holding a philosophical view in favor of one factor or another. Some investors do have philosophical biases, which is perfectly fine, but they should be aware that they are giving up diversification benefits.

Rolf Agather: I think it's important to recognize hat even as we are able to produce a particular performance or risk-return profile based on some exposure, there are implementation issues that can come along. Equal weight is a great example. It's been around a long time and is a relatively naïve strategy that has performed better than some other strategies. But when you equal-weight companies, you are putting the same amount of money into the largest company in the market as the smallest company, so potentially you can introduce liquidity or capacity issues.

In terms of persistence, we do think that markets are generally efficient and therefore, true anomalies will go away over time. But when you talk about risk premia, like value, momentum and quality factors, there is the notion that you are bearing additional risk for which you have a reasonable expectation to benefit. We would expect a risk premia to persist.

But it's important to recognize relative valuation levels. As money flows into certain strategies, they can become overvalued. That doesn't make the potential benefit go away, but it can create an artificial imbalance in a particular factor or strategy.

Kal Ghayur: There are two schools of thought here. One echoes what Rolf is saying, the risk premium explanation, that suggests that these things can persist over time because they are a compensation for bearing extra risk. But the risk premium explanation is a little bit hard to justify when it comes to the low-volatility anomaly. There's a lot of research that shows that low-volatility stocks tend to outperform high-volatility stocks. This is contrary to everything we know in finance, where the most basic argument is that you can only earn higher returns if you take higher risks.

There is another school of thought that argues that things that have worked in the past and continue to persist over time do so because of behavioral or institutional biases. According to this explanation, investors have some behavioral biases when they invest in stocks. They like glamour stocks and stocks with nice stories, so they tend to invest in growth stocks as opposed to the more depressed value stocks. As a result, the prices of these glamour, high-growth stocks tend to bid up and their future returns fall, whereas the prices of the less exciting value stocks are bid down and their future returns tend to be higher.

Low volatility is still a puzzling anomaly here, but it can potentially be explained through an institutional bias. Most managers are measured against a cap-weighted benchmark — passive or active managers. Low-volatility stocks are low beta stocks, so there is little incentive for managers to hold low-volatility stocks. In fact, because the beta of low-volatility stocks is less than one and the market beta is one, it introduces tracking error. So managers shy away from these types of stocks. As a result, the future returns of high beta stocks are low and the future returns of low beta stocks are high, explaining why the low-volatility anomaly persists over time. This would probably only disappear if the focus on benchmarks disappears.

Dan Draper: I think smart beta strategies adapt over time. Some factors — large cap, small cap, value, growth — which were identified back in the 1970s are now construed as to some degree traditional beta, even though they are not the true overall market.

I expect that smart beta strategies that perform well and stand the test of time to become more mainstream. If that happens, we think we're doing our job!