Providing Alpha In A Smart Beta World by Arne Staal, Standard Life Investments
Smart beta is a blanket term applied to any non-market-capitalization-weighted systematic investment strategy that can be represented by an index, i.e. any fully algorithmic, completely transparent and investable portfolio strategy. Some restrict its use to long-only indices, whereas others include the full gamut of transparent long-short strategies that aim to capture some type of systematic spread within asset classes. It is alternatively referred to as ‘exotic’ beta, ‘alternative’ beta, factor investing, liquid risk premia, style premia or alternative risk premia. There is no upside in arguing the semantics of smart beta though, what matters are the opportunities and challenges it represents to investors and how it changes the investment landscape. Most public discussion on smart beta is focused on the ever-expanding choice of products offered by providers and the challenge that poses to active managers. Smart beta’s perceived virtues have been widely sung by advocates, but less has been said about the pitfalls investors might encounter in seeking out these types of investments. Even less has been said about the changing opportunities that arise to shape investment outcomes and provide alpha in a smart beta world. We aim to shed light on these topics and discuss both the pitfalls in smart beta investing and the opportunities for using alternative passive exposures to generate value through an active investment approach. Smart beta is often loosely applied to a range of passive alternative solutions that is diverse and changing quickly, blurring the old paradigm of alpha versus beta and active versus passive. We believe the changing investment landscape is best framed in a broader context in which the rise of low cost transparent algorithmic investing calls for a focus on individual outcomes rather than one-size-fits-all benchmarking.
The changing nature of alpha and beta
The concept of smart beta is not new, or even recent. In essence, smart beta represents a class of systematic trading strategies that captures well-known return drivers that can be offered in index format with reasonably high capacity and liquidity. Academia has long advocated taking into account systematic strategies to explain equity market returns: Fama and French (1993) told us about ‘Value’ and ‘Size’ factors in their seminal paper, Jegadeesh and Titman (1993) highlighted ‘Momentum’ as a systematic factor, Piotroski (2000) advocated ‘Quality’ in a landmark paper, and low volatility investing
traces back its origins to Haugen and Heines (1975). Similarly, market practitioners in fixed income have long understood the analytical return drivers in their asset class and used them to systematically deviate from market weights; for example, through duration extension and spread overweighting. It would be a mistake though to dismiss smart beta as merely repackaging existing assets based on old ideas in new investment vehicles. Technological advances, widespread data availability and democratisation of investment knowledge have taken smart beta out of the domain of academics and
specialised investors, and made it widely accessible to all types of investors at relatively low cost. Investors in turn have shown strong demand for smart beta products, with assets under management rapidly growing in the last few years. Historically, beta has been delivered through passive management of portfolios that track market-weighted indices. Alpha was delivered as (out) performance by active managers above and beyond appropriate market benchmarks. In this traditional view of asset management, smart beta represents an evolution that aims to capture the domain of active managers through passive rules. It broadens the universe of available benchmarks and seems to shrink the potential for alpha in size and breadth (see Chart 1).
This narrow view of how to think about investment returns ignores that smart beta comes in many shapes and forms and means different things to different people. It mistakenly assumes that smart beta is as clearly defined and agreed upon as traditional benchmark indices. As the number of available passive investment solutions grow, a one-size-fits-all approach to benchmarking becomes increasingly irrelevant. Asset owners are increasingly likely to adopt different alternatively weighted indices to measure outcomes, and indeed become more focused on overall outcomes rather than narrow return attributions to standard market indices.
[drizzle]The rise of smart beta does not represent a single regime shift in the investment landscape. It is a result of advances in technology, data availability and growing investor sophistication that will continue to drive development of passive solutions in different ways. Understanding the implications of this ongoing change requires a return model that recognises that outcomes are generated through different exposures that can be usefully categorised as ‘transparent algorithmic’ approaches and truly active investments. Transparent algorithmic investments include a broad and growing range of ETFs and passive alternative solutions, such as smart beta indices, but also for example certain ‘risk-parity’ or ‘volatility-targeted’ products. Active exposures are defined by their proprietary and/or discretionary nature (see Chart 2).
A focus on the nature of the exposures that drive outcomes rather than pure return-based benchmarking recognises that investors have an increasing ability to tailor their passive exposure beyond standard benchmark indices to fit their individual objectives, which tend to be more complex than ‘x% over benchmark y’. Representing beta with market indices is increasingly meaningless as investors adopt more transparent rules-based investment strategies such as smart beta. At the same time, the interpretation of alpha becomes broader as it should include any (desirable) outcome that cannot be replicated by simple mechanical investment approaches. This includes traditional security selection approaches but also the value created through dynamic allocation to algorithmic exposures (‘allocation alpha’).
The old world of beta versus alpha was straightforward to understand. In the new paradigm of active versus transparent algorithmic exposure, passive no longer equates to ‘straightforward’ and alpha is increasingly evaluated against an increasing set of transparent rules-based exposures. This means investors are faced with a rapidly changing opportunity set, more complex evaluations and choices to make, and a wider range of associated costs to assess. Awareness of pitfalls in utilising these newly available passive tools is increasing but is not yet widely discussed.
Smart beta investing: the missing warning labels
Decreases in costs relating to development and implementation have significantly lowered the barrier to entry for providing passive alternative strategies. This has led to rapid growth in the range of smart beta products on offer – there are now more smart beta ETFs than large-cap stocks available in the US! The number of unique smart beta approaches with both a solid economic grounding and consistent historical track record is very limited though. Unsurprisingly, this means there are considerable pitfalls in evaluating any single smart beta implementation on its ability to deliver on promised outcomes. Lack of clarity in the investment objective, backward-looking biases, implementation inefficiencies and limits to sustainability are pitfalls investors should be aware of when considering smart beta strategies, or indeed other transparent algorithmic solutions. We address each in turn.
Unclear investment objectives and economic exposure
Most smart beta indices are constructed with the intention to outperform the market benchmark index. The source of this outperformance is generally attributed to a risk premium, market structure – investor segmentation, or behavioural phenomena – see Chart 3. Rarely though is there a simple unambiguous explanation for the market factors that smart