Smart beta: Will it sink or swim?


Smart beta draws mixed feelings. Many see it as delivering a much-needed kick for the active fund management industry, finally arbitraging away those expensive closet trackers. Others, including luminaries such as Vanguard founder Jack Bogle, have suggested that its uses are limited. At the moment, investors believe it has a place and fund flows are strong, but can its popularity endure?

There has been a proliferation of smart beta launches in recent years, including from a number of active managers. Invesco Perpetual, for example, recently launched four enhanced index funds, focusing on UK, European, US and global equities. At the time, the group said that it was aiming to appeal to advisers and fund selectors who are already using passive funds, but wanted something extra.

While most wouldn’t admit it, the move into smart beta from active managers appears to be a response to the challenge issued by this emerging sector. The most recent data from ETFGI reports that global smart beta equity ETF assets increased by 7.1 per cent from $400bn to $429bn for the year to 30 June 2016. This caps a five-year compound annual growth rate of 31.3 per cent.

Europe has been later to the smart beta party, but is catching up. Wisdom Tree data shows that at the halfway mark in 2016, 40 per cent of total flows into European ETFs have gone into smart beta products. Equally, smart beta products have proved more resilient in turbulent markets. While market capitalisation-weighted ETFs suffered outflows of $9.1bn in the first half of this year, smart beta and alternatively weighted strategies had net inflows of $5.7bn. This continues a strong trend in 2015 and suggests that the industry is on course to push past $500bn by the end of 2016, and reach nearly $800bn by 2020.

Of course, it has not all been plain sailing. There have been a number of high profile closures. For example the db X-trackers SCM Multi Asset ETF closed last year after the funds under management dropped below £500,000. Nevertheless, new launches are abundant and the sector appears in robust health.

This popularity has a number of drivers. First, and most obviously, is the long-term shift to passive investing. Driving this is an increasing preoccupation with costs. Although the costs of smart beta do not compete with the few basis points charged by market capitalisation passive funds, they are still lower than those of active funds. A Morningstar report in February of this year found that average fees in the European strategic beta ETF space had declined in recent years, falling from 0.43 per cent to 0.39 per cent over the previous five years.

Charles Aram, head of EMEA at Research Affiliates, says that low costs are key: “If it costs more than an active strategy, what’s the point? The litmus test is cost. It needs to sit at the lower end, far closer to passive.” He suggests that in a lower return environment, this cost will become increasingly important.

There is also an increasing disillusionment with active management, while at the same time a realisation of the limitations of passive. Howie Li, executive director at ETF Securities, says: “Smart beta as a concept is nothing new. Active management has long applied these criteria when picking stocks. But there has been more scrutiny around active investment – are the returns justifying the fees? Is there good value? Passive has benefits, but short-comings. It is lower cost, it is predictable, but to outperform the market investors need to find a way to search to do things differently.”

Antoine Moreau, deputy chief executive at Ossiam, says: “When active managers were expected to protect portfolios on the downside, it didn’t happen. Investors also started to realise the limitations of market capitalisation indices. On the other side, they also realized the limitations of hedge funds. Absolute return did not prove that absolute. On a three to five-year cycle, few outperformed.”

Smart beta also plays to a new approach to diversification. In a recent white paper, Pimco wrote: “Asset class correlations are less stable than many investors realize, and long-term trends such as globalisation are driving correlations higher. In addition, correlations typically increase during periods of market turbulence. As a result, seemingly distinct asset classes are likely to behave more similarly than many people expect. In other words, even portfolios that are well diversified across asset classes may not be positioned to adequately diversify and cushion market volatility.”

Pimco’s conclusion is that by targeting exposure to underlying risk factors, investors can select a mix of asset classes and styles that provide more diversified portfolio risk. Smart beta investing offers a way to do this in a way that conventional active and passive managers do not.

Chanchal Samadder, ‎head of UK and Ireland institutional ETF sales at Lyxor, suggests there are three main uses for smart beta: to reduce risk, through minimum variance indices or low volatility strategies; to enhance certain risk factors –growth, value and so on; or to enhance income.

To date, it is the low volatility/minimum variance strategies that have found most resonance with investors. This has played neatly into the current trend for volatility targeting within portfolios, rather than more conventional blending of asset classes. Samadder says: “We have seen a lot of money going into low volatility options. This is part of the move to outcome-orientated portfolio solutions, which in turn requires a move away from market weighted passive products.”

None of these factors – cost, changing diversification approaches, the move to passive or the desire to reduce volatility – look likely to fade in the near-term, suggesting smart beta should be able to ride a wave of structural growth for some time, but there are risks: The problem is, as Aram points out, if something has been ‘hot’ recently, it risks performing badly. “London property, for example, has been fantastic, but this doesn’t mean it will perform as well in future. If you overpay, no matter what the quality of the asset, you get a poor investment result. Investors need to look before they leap.”

In particular, this could spell problems for the same minimum and low variance ETFs that have been among the most popular smart beta options. Although these have been top-performers, the assumption on which most of these ETFs are based is that low volatility stocks remain low volatility, and high volatility stocks remain high volatility. In general, that has been true. Companies such as Unilever and British American Tobacco have proved to be lower volatility over a long period of time.

But monetary policy has created an odd investment environment. Assets with predictable cashflows have been highly prized by investors and now look very expensive. Their popularity could be disrupted by shifts in interest rates, rising inflation or simply a change in market mood. This could see performance from these strategies wane.

Aram says: “These are strange times. Quality stocks have been very popular, and have become very expensive. Investors are being asked to pay a lot more. This is not something that is sustainable over time.”

He also believes there is a problem of proliferation: “There are now something like 400 factors. Can they all really offer a source of outperformance?” He suggests that in some cases the data set may not be as robust as it should be.

There is also a danger that some of the factors are arbitraged away. Chris Riley, investment research manager at RSMR, points out that the back-testing in smart beta often looks good over the very long term, but less so over the short term. This may be because the factors used in smart beta have become a lot more well-known in recent years. He adds: “This is a long-term risk for smart beta and could spell danger in the future.”

Nevertheless, active managers cannot rest easy. Riley suggests that smart beta does issue a challenge in certain areas: “Certainly smart beta replicates some of the decisions taken by active managers. For example, in high-yield investments, there are certain criteria that can be codified into a set of values. It will often correlate with the availability of data. For a large cap fund, data is usually quite accurate and quite plentiful.

“However, small cap managers may have a more esoteric process: the quality of data isn’t as good and it is difficult to codify it into a quantitative process.” He points out that quantitative process may not be subject to the same inherent behavioural biases as qualitative processes, which may favour smart beta in the longer-term.”

Investors need to look at whether a manager is genuinely generating alpha, or merely has a tilt to a certain market cap. For many years active managers with a tilt to mid and small cap have fared better, but it is difficult to claim this as ‘skill’ exactly and this tilt is replicable by smart beta.

Samadder says: “Historically certain things have been sold as high alpha that can be explained by risk premia and risk factors.” This suggests that, while smart beta doesn’t negate active management, it could generate some creative destruction.

There is the challenge of how to use and blend smart beta strategies. One of Bogle’s chief criticisms of the approach is that factor-based investing would deliver no more than index returns over time, because – for example – sometimes growth wins and sometimes value wins. Over time, investors get the market.

Riley says: “In the short-term factor outperformance is caused by behavioural biases. Value premium is caused by investor preference for glamour stocks and so on. We believe this is the reason for the pay-offs in individual stocks. It is not a reason that blending lots of factors would cancel each other out.

“That said, Bogle might have been correct that if some factors become very popular, you get a lot of capital flows and it could erode that capital over time. It is not an argument against mixing factors, but the danger of individual factors. It applies to any asset class.”

Nevertheless, there is a question of the extent to which investors should employ market timing when selecting factors. Do investors need to make a judgement on when is the right time to use a growth ETF or a value ETF?

The question is whether the strategies are properly uncorrelated. Does a multi-factor approach see each cancel the other out? Aram believes not: “Momentum stocks don’t display the same correlation as minimum variance stocks and so on.”

Brian Whimmer, senior investment strategist at Vanguard Europe, says that the group’s investors use their smart beta products in a variety of ways: “Some investors prefer to use single factor products to tailor their exposure. They may believe value should outperform the broader market over the long-term, while others want minimum variance products to reduce their overall risk profile. That said, many of our clients are looking for combined solutions, using products with multiple factors.”

Li says: “For lots of our clients, it is the first or second venture into smart beta. They tend to be reallocated a portion of their market cap weighted allocation to smart beta.”

Samadder says that some large institutions will use smart beta to generate, say, a 30 per cent allocation to quality stocks. A second use is much more tactical and dynamic.

Aram believes that it all comes down to the type of investor you are: “If you are a defensive investor; one who likes to avoid serious drawdowns and mistakes, but also wants to minimize effort, work and frequent decision-making, smart beta is a reasonable option. It fits most investors.” He points out that even those very enterprising investors, prepared to do lots of work, still fail to beat the market in 70-80 per cent of cases. On the whole, he doesn’t believe that cherry-picking factors works well in many cases.

In the meantime innovation in the sector continues apace. There has been growth in risk parity products, including those based on Shiller indices. Li believes that there is likely to be more innovation in the fixed income area, where market capitalisation-weighted indices present more problems, giving a higher weight to the most indebted corporates or governments: “Piling money into the most indebted issuers doesn’t make sense. There are indices based on the ability to repay, or credit default risk, or other quality measures,” he adds.

Smart beta is more than a fad and issues a real challenge to active managers in certain areas. Nevertheless, it is not without its risks – there is a danger that factors are arbitraged away as they become more widely recognised by the market, or that previously top-performing strategies do not remain so. Nevertheless, these problems are certainly not unique to smart beta.

Smart beta strategies explained

Alternative indexation: This takes a standard index and re-weights it in a new way. Rather than market capitalisation being the determinant of portfolio weight, weightings may be rebalanced according to a company’s yield, earnings or other metric. In geographical-based indices, a country may be weighted on its economic contribution rather than its GDP weight.

Equal-weight strategies: These strategies assign an equal weight to every stock in an index. This can have a dramatic impact. For example, Apple has near 4 per cent weight in the S&P 500, but just 0.2 per cent in the equal-weighted version. This may be better or worse, but it gets round one of the major criticisms of market capitalisation-weighted benchmarks – that they are always skewed to yesterday’s winners.

Single-factor strategies: These funds aim to isolate a single factor, which might be size, growth or value stocks, momentum or whether a stock has historically shown high or low volatility. Some also focus on stocks that pay dividends. The difficulty is deciding which strategy is right at which time in the market.

Multi-factor strategies: Some smart-beta strategies combine multiple factors together. Research Affiliates, for example, has a set of indices combining four “fundamental” factors to reweight the market: book value, cashflow, sales and dividends.

Proprietary strategies: There are also a wide variety of idiosyncratic strategies, based on proprietary indices.

Expert view: Assessing smart beta

It has been a little more than 10 years since the launch of the RAF Fundamental Index opened the door to an innovative range of strategies now known as smart beta. Since then, “smart beta” has grown increasingly popular among investors seeking systematic sources of returns at low cost.

The original principle is simple enough: unlike traditional market capitalisation-based indices, smart beta approaches can help achieve individual investment objectives by avoiding chasing what is popular and expensive.

Yet, increasingly the smart beta moniker is being applied to strategies that are no long just systematic contrarian investing. Indeed, the term is now used to refer to just about any automated strategy or factor.

But can these ideas all work and are they all truly “smart” beta?

One of the major problems within the asset management world (be investors, managers, consultants or even academics) is that past performance is used to gauge the work of a (smart beta) investment thesis. This itself is fine if past performance comes from the strategy systematically generating structural alpha as the likelihood is that the strategy can replicate and reproduce these results.

Problems arise, however, if strong past performance is situational, that is to say a result of the strategy’s popularity pushing valuations higher. Popularity or performance chasing can really hurt investors – rising valuation levels inflate past performance; reduce the future return prospects of the stock/sector/asset class/strategy (even if the new valuation level holds); and creates a risk of mean reversion to historical valuation norms and an abrupt retraction of past performance.

In this context, our analysis of the smart beta market and the most common equity factors on offer today reveals an alarming picture, with most having produced the majority of their historical performance as a result of becoming more expensive.

Put more simply – many smart betas are popular today purely because of rising valuations, increasing the danger of reversion to the norm and accompanying underperformance.

Analysis of the past 10 years’ of four equity “factors” – value, small cap, low beta, gross profitability – bears this out. At first glance, it may appear that value investing has proved something of a fool’s errand, but if one takes into consideration the returns resulting from changes in valuations it quickly becomes clear that value stocks have underperformed only because they have become cheaper and cheaper, now trading at a discount relative to growth. In contrast, gross profitability in particular has been successful primarily as a result of becoming expensive. An longer term analysis over 30 years makes this trend even clearer, with profitability showing much more modest returns (all earned in the past 10 years and arising from rising valuations), while value has delivered positive returns despite falling valuations and an appalling last decade.

What, then, should we take from this? Quite simply – valuations matter. They cannot expand indefinitely and today’s high valuations will likely be mean-reverting valuations tomorrow, leading to negative future performance. As investors look to allocate into smart beta strategies, it is therefore vital they take valuations into consideration and look before they leap.

Rob Arnott is chairman and founder of Research Affiliates

Smart beta in numbers

$5.7bn Smart beta inflows in June 2016

$2.2bn Inflows into volatility factors in June 2016

$1.7bn Inflows into dividend factor-based products in June 2016

$16.2bn Smart beta inflows for the year to date

$14.3bn Inflows into volatility factors for the year to date

$4.1bn Inflows into iShares, which saw the largest inflows in June 2016