The name smart beta originates from Towers Watson and for Tim Unger head of advisory portfolio management at the firm, its key purpose and use by investors is to side step certain expensive fund management products.
“It’s enabled investors to substantially reduce the costs of accessing strategies that were largely beta like in nature, but managers were able to charge alpha-like fees, because what they were doing was relatively opaque,” he says.
His research indicates that hedge fund managers that have been hurt the most from this revelation, which has given greater familiarity that wherever there is a risk premium it can be broadly replicated relatively cheaply and systematically. “It’s enabled investors to get access to different kinds of risk premia,” says Unger.
Kal Ghayur, head of Active Beta equity at Goldman Sachs Asset Management, has been managing portfolios on a smart beta basis since 2007 and sees most demand coming from large institutional investors, who as they have grown have sought to focus on reducing fees and who are also not able to access capacity constrained active managers.
He describes those that take money away from passive managers as putting it into smart beta strategies with tracking errors in the 0.5-1 per cent range. These are highly diversified factor strategies with a large number of holdings and very low stock specific risk.
“The idea is to generate 50, 60 basis points of return after cost and make the passive piece work harder,” says Ghayur.
By contrast, where investors are moving money away from active managers, they are happy to go with tracking errors of 2-3 per cent.
For Derek Mock, a principal at Mercer, the increased interest can be largely explained by a growing awareness of the alternatives to the market cap index investment process, which has been spread by academic studies, fund managers with new product lines and consultants informing their clients.
He adds that the identification or the use of factors to identify what is true alpha and what can be perhaps replicated fairly cheaply is not only having a governance impact, but also a fee budgeting impact as well.
The investors at the discussion had varying degrees of experience with smart beta. Michael Blayney, head of investment strategy at First State Super, told how his fund used it to get exposure to particular risk factors that were attractive at a point in the investment cycle or to manage exposure to a particular asset class or sector where the fund might want exposure or avoid.
This might particularly be in reaction to a large asset holding such as Australian equities, which might contain a large factor bias that an investor wants to diversify away from, according to Joshua Bloom, portfolio manager for international shares at Sunsuper, who added that it was also done for cost reasons and where the fund had lost faith in active management, but not in a particular factor.
“The group we invest with wouldn’t call themselves smart beta but it’s like a specific factor portfolio,” he says.
Matt Olsen, chief investment officer at Energy Industry Super Scheme, is looking to make his fund’s first explicit step into the space. He is looking at where the fund can gain a better return than a passive market cap exposure and at ways of accessing proven market factors through smart beta in a way that would be less expensive than active management.
He also sees it as a healthy addition to the investment process. “My goal is to challenge the status quo,” he says, adding that it would give the potential to measure and reward true skill above what a smart beta component of a portfolio could generate.
For Bloom this was not as easy as it sounds and could blur the line in measure manager performance.
“You have to be careful around what it is that you’re actually doing it for,” he says. “If it’s because you have lost faith in active management or you really truly believe in a particular premium that’s one thing. But if you have lost faith in the actual premium itself, going into a smart beta is not necessarily going to do it for you.”
Amongst those who had used smart beta there was an awareness of a learning curve in the style and some of the pitfalls.
Blayney drew attention to the skills of combining factors. He gave the example of how a quality portfolio and a value portfolio might probably produce a suboptimal outcome compared to buying the value portfolio with
a quality filter because the factors can combine in “a nonlinear way”.
He says: “There are so many different risk premiums you can extract, extracting just one in a very simplistic way is probably not going to be the optimal way to do it.”
He also raises the issue of timing an entry into a factor style and the flow of assets into a style. “You can look at whether a portfolio of stocks trades at a premium or a discount compared to how it trades relative to the market through history,” he says. “So you can get a feel for whether you are overpaying for something that’s popular or not.”
Ghayur says that another step in the evolution of smart beta was for managers to deliver their strategies as a model portfolio, which the asset owner can implement in-house. Similarly, custom indexes can be created to be replicated by the asset owner or by their passive manager.
In such a model the smart beta manager gets a licensing fee at a fraction of what a separate mandate fees would normally be.
Bloom says investors must be careful not to set and forget and that some of the savings of such a model would have to be reinvested in ongoing research.
Ghayur accepts this, but says such fears were more pertinent for a public index.
“Once the rules and methodologies are set it becomes increasingly hard for the index provider to make methodological changes in the index and to keep evolving it – they can’t do that very often,” he says. By contrast it was much easier to enhance and update a model portfolio for a single client.
On this point, Blayney sought to make a distinction between the times an investor would use a tailored smart beta portfolio and when it would not.
“If you just want a short term tilt on value, then picking an off the shelf index and implementing that makes a lot of sense,” he says. The same applies for an approach used through a derivative contract or a swap.
“If however you are looking to do something which perhaps complements the rest of your portfolio, then it can make a lot more sense depending on what resources you have, either partnering with an asset manager to build it in-house yourself,” he says.
Ghayur agrees with the various roles smart beta can play and sees the evolution towards working with clients using a customized smart beta framework rather than one product fits all, “I’m seeing a lot of investors who initially dipped their toes into smart beta, had concentrated exposures to individual factor strategies, completely moving away from that… into highly diversified strategies across all factors”.
Blayney explained what success would look like in a smart beta portfolio. If a smart beta portfolio gave the same return as the index at a much smoother journey then it would have a superior sharp ratio. However, other factors may naturally come with a higher volatility than the index and here an investor would need higher compensation than what the index gave. Other benchmarks of success might be outperforming in down markets or simply delivering better diversification.
Measuring this outperformance is problematic because a risk premium can take 10 years to manifest itself and be observable. “These things can underperform for a long period of time,” warns Blayney.
The chief concern at the smart beta from consultants was the sense that anything that is this crowded and popular was unlikely to end well for all.
“There is a bit of a conundrum at the moment which is that it is clearly a good idea, but its very popularity is probably going to mean that future returns are not as good,” says Unger. “This could lead to volatility or disappointment.”
Ross Blakers, head of portfolio construction and risk at Whitehelm Capital points out the risks of a massive duplication of smart beta strategies and the over reliance on back testing.
“One of the risks is that it just is over fitted on history,” he says and advises investors to ask fund managers how their strategy evolve in line with an ongoing research plan.
He also raises the spectre of crowded trades around stocks in low-volatility approaches, one of the most popular strategies. Recent research on crowded trades has shown that in times of crisis these stocks can fall as much as 30 per cent compared to falls of 5 per cent in less crowded trades.
“If low vol is a crowded trade, the risk of a huge sell off would be completely counter intuitive to an investor that might be nervous about markets,” warns Blakers.
Furthermore, he says investors would need more years of experience to see how popular smart beta strategies played out over full investment cycles.
“It will be fascinating see how low-volatility plays out through the next downturn, and if there are different flavours of low vol, just like we saw different flavours of quant through the GFC.”
In answer to these concerns Ghayur again emphasised the role of tailoring portfolios, but also paying attention to building slightly different holdings, weightings to the norm and using stock limits to mitigate crowded trades.
Also on the issue of timing risks when entering a factor, he suggested a diversified approach to factors.
For Joshua Bloom this debate emphasises the fundamental approach that choosing the right smart beta strategy, index or fund manager would determine success in the same way it would for any other investment.
“Investors will make the same mistakes they ordinarily do,” he says. “You still need to invest at the right time and if you believe in value you need to invest when a factor is cheap.”
There was an exchange of views on the relative simplicity of understanding of smart beta. Blayney pointed out that it was easier to explain the decision making process of a fundamental equity manager than it was a smart beta manager. “It’s very easy and very intuitive. You can talk about the companies and their earnings,” he says. “But when you go and try to explain a smart beta strategy to somebody, you start talking to them in terms of risk premia and factor exposures. It is actually far more difficult to communicate that.”
For Bloom, this places a large emphasis on the decision of the investor to make the decision to allocate – poor performance could not be blamed on a lack of skill by the manager.
“If you’re the one that’s selected a factor or premium that for whatever reason is not working, it’s not the manager’s fault anymore,” he says. “Whereas now the decision is solely the asset owners or the board or whoever is making the decision.”
Bloom debates whether an investor should time their entry into a factor or strategy just after it had underperformed and therefore be suspicious of providers with results and performance that had done very well recently.
On this theme, Blakers cites a research report he had seen for an emerging markets fund, which he described as having recently witnessed “phenomenal underperformance”, that was positioned on the premise that it was likely to revert to mean.
Tim Unger sees one of the roles of smart beta providers as breaking down manager’s returns and attributing them to various factors, leaving the residual as identifying true skill and alpha, “so you end up paying a fair fee for the residual”. Ghayur agrees this is a key first step in engaging clients so that they understand their existing exposure.
Overall there was agreement by participants that there is value in harvesting factor beta. That allows investors to make a direct and intentional allocation to a set of common factors rather than accept the allocation provided indirectly by an active strategy.