understanding smart beta

Understanding Smart Beta July 2013

For several years Towers Watson has been investigating the use of smart beta investing across a range of traditional and alternative asset classes. We are now at a stage where smart beta has moved beyond theory and there are several funds available today across several asset classes.

For something ‘smart’, we believe it is really quite simple. Smart beta gives the investor the opportunity to capture a:

• wider spread of risk premia than conventional systematic strategies, or

• risk premium previously only available through expensive active strategies in a cheaper way.

Smart beta strategies may have one or more of the following features:

• captures existing (or alternative) risk premia (some of which might have been ‘hidden’ in active management)

• improves portfolio diversity

• captures long-term investment themes that some other investors are not well placed to exploit

• improves implementation versus market capitalisation.

In our view, smart beta strategies should be simple, low cost, transparent and systematic.

To believe in the smart beta proposition, one must first accept that there is a wider framework than the narrow definitions of alpha and beta which classic finance theory puts forward. In this framework, somewhere between alpha and beta, lies smart beta.

“Smart beta is simply about trying to identify good investment ideas that can be structured better, whether that is improving existing beta opportunities or creating exposures or themes that are implementable in a low cost, systematic way.”

2 | towerswatson.com

This framework hinges on building an investment strategy as a combination of certain return drivers. We can use the term ‘beta’ for most of these return drivers. The economic rationale behind these return drivers can either be temporal, with a finite term, or secular and largely timeless. A visualisation of this framework is provided in Figure 01.

Why smart beta?

Within traditional markets, interest has arisen partly due to some increasingly undesirable characteristics of market capitalisation weighted index strategies and, in some cases, due to a loss of confidence by some investors in their ability to extract alpha in a cost and tax effective way. Furthermore, several smart beta strategies in traditional markets have recently delivered strong performance over conventional market capitalisation weighted strategies.

Within alternatives, interest has arisen partly from a realisation that some of the things that hedge funds do at great expense can be reproduced with simple, easily accessible strategies at a lower cost. Consequently, access to alternative betas with fundamentally different return drivers to traditional asset classes can potentially be achieved without hedge fund like fees.

We take a holistic approach in considering which smart beta approach(es) would be appropriate for each client; for example, how an existing portfolio is constructed, its overall objectives, risk constraints and beliefs. In other words, we do not adopt a ‘one size fits all’ approach in recommending smart beta strategies.

The rise of smart beta

We believe we are still at the ‘pioneer’ stage in the evolution of smart beta; however, we have now observed several large and prominent investors incorporate smart beta strategies into their portfolios. Growing popularity and increasing allocations into smart beta strategies may remain powerful tailwinds in the foreseeable future; however, as these strategies attract increasing amounts of capital, they may start to reflect diminishing returns over time.

In the following sections of this paper we look at how smart beta can be harvested across the ‘traditional’ asset classes of fixed income and equities. We then go on to examine which smart beta strategies can be implemented across various alternative asset classes.

Equity Term Credit Insurance Illiquidity Currency Inflation ESG Skill

Asset classes Mandates

Real estate EM overweightValue weighted

indices

InfrastructureDemographics

overweightRisk weighted

indices

Choice of smart beta

Classic active management

Skill in alternatives

Tactical asset allocation

Equities

Sovereign bonds

Corporate bonds

Diversifying beta

Thematic beta

Systematic beta

Smart betaBulk beta Alpha

Examples of return drivers

Figure 01. The alpha/beta continuum and example approaches

Smart Beta July 2013 | 3

Equity smart betaThere have been a considerable number of academic papers covering the inefficiencies of equity market capitalisation weighted benchmarks and the existence of systematic factors (value, small cap) which can potentially be exploited by investors. Given many of these papers have been widely distributed, or used for investment management marketing pitches, we do not intend to cover them in this paper. Instead we will look at how Towers Watson sees the equity smart beta universe and the implementation options available within this framework.

Broadly, we split the equity smart beta universe into two high level categories: thematic and systematic. The systematic categories can then be split into four specific definitions: equal weighted, economically weighted, risk weighted and factor tilts.

Below we outline each of these approaches.

Thematic approaches

Thematic smart beta aims to take advantage of secular or temporal mispricing issues (for example, emerging wealth exposure, demographic impacts). The underlying thesis is essentially that many investors are excessively focused on the short term and, therefore, mispricing exists in respect of opportunities that are longer term in nature.

In general, our preference is for simple, transparent strategies with a strong and intuitive economic or investment rationale. While there are currently a limited number of investible equity thematic options that fit this criteria, Towers Watson continues to work with a number of investment managers on potential solutions/products in this space.

We note that because these strategies require beliefs to be held about what the future has in store, the appropriateness of such strategies is particularly specific to an investor’s existing portfolio, beliefs and preferences.

Systematic approaches

Opportunities for systematic smart beta approaches arise from a range of factors; for example, investor heterogeneity and systematic mispricing (such as the value weighted index), and some structural issues associated with market capitalisation approaches (for example, constituent change dates, arbitrary rules for inclusion or exclusion).

We outline the four key systematic approaches below:

Equally weighted approach

This is the most simplistic approach to removing the link between prices and stock weights. No assumptions are used, or needed, for stock returns, volatility or correlations. Implicit in this approach is that stock returns, volatility and correlations are unknown (or are at least expected to be the same on an ex-ante basis).

Although simple, equally weighted approaches have historically been hard to beat both within and across markets, at least before transaction costs. Certainly they have outperformed market capitalisation approaches.

The approach in its purest sense is, however, not practical, particularly for broad market portfolios. The approach gives a large allocation to small and illiquid stocks. This means that a portfolio cannot be implemented with any significant size, so the strategy has low capacity.

Economically weighted approach

This smart beta approach weights stocks by fundamental business metrics such as sales, earnings, book value and so on, rather than market capitalisation. The main aim of this approach is to remove the link between the price and the weighting of stocks in a portfolio, and replace it with weightings based on economic size.

Relative to a market capitalisation portfolio, economically weighted portfolios tend to have a value ‘tilt’, although this varies over time. However, relative to typical value oriented indices, economically weighted strategies include all stocks in a given universe, rather than just the ‘value half’.

There are a number of ways of combining different economic measures to form an economically weighted strategy. In most cases, several measures are used, and the weighting from each is averaged.

The underlying philosophies of the various approaches do differ, and this can lead to some differences in the construction of the indices. However, we believe the effects they capture are broadly similar.


1 Minimum variance: To construct the minimum variance strategy we use the method of Clarke, de Silva and Thorley (2006).

2 Maximum diversification: Portfolio optimised to maximise expected diversification ratio, which is defined as the ratio of weighted average risk to the expected portfolio risk. For details see Choueifaty and Coignard (2008).

3 Risk-efficient (λ=2): Mean-variance optimised portfolio assuming that expected excess returns are proportional to the stocks’ downside semi-deviation, and with stringent constraint to limit portfolio concentration. For details see Amenc et al (2010).

4 Risk cluster equal weight: Applying statistical methods to identify major market risk factors, assumed to be driven by industries and geographies, and then equally weight these uncorrelated risk clusters.

5 Diversity weighting: Weighted based on the market capitalisation weight raised to the power of a constant that is between zero and one to tilt the portfolio towards small cap stocks while limiting tracking error. We used the value of 0.76 in our simulation.

6 Fundamentals weighted: Weighted based on the five year averages of cash flows, dividends, sales and the most recent book value of equity. We introduce a two year delay to avoid forward-looking bias. Following the original method, we select top stocks with the largest fundamental weight. For details see Arnott, Hsu and Moore (2005).

7 Cap-weighted: Weighted based on market capitalisation. The market capitalisation is computed using December values at the close of the year prior to index construction.

StrategyUS 1964-2012

Return Standard deviation

Sharpe ratio

Information ratio

Minimum variance1 11.8% 11.7% 0.56 0.26Maximum diversification2 12.0% 14.0% 0.48 0.35Risk-efficient (λ=2)3 12.5% 16.8% 0.43 0.53Risk cluster equal weight4 11.2% 14.6% 0.41 0.31Diversity weighting5 10.5% 15.5% 0.34 0.47Fundamentals weighted6 11.6% 15.4% 0.41 0.42US cap weighted7 9.7% 15.3% 0.29 0.00

Source: Realindex, Research Affiliates

Risk weighted approaches

These approaches aim to improve portfolio efficiency (return per unit risk) by making assumptions about future volatility, return and/or correlations, generally based on historical observations.

There are three main risk-weighted approaches:

1. Naïve volatility-based weighting — The weight of the stock in the portfolio is related to the inverse of its variance. No assumption is made about return or correlation and, in a similar manner to equal weighting, the implication is these are unknown.

2. Diversification strategies — These strategies assume that correlation is mispriced and that by constructing a portfolio to have low correlations (a high level of diversification), superior risk-adjusted returns can be generated.

3. Volatility minimisation strategies — These strategies combine volatility and correlation through an optimisation framework to produce a portfolio with the lowest volatility or beta, depending on the strategy.

We believe there are issues with many of the strategies in this space, particularly around the implementation of portfolio optimisation that cause us to question the indices available. Consequently, we believe the best way to capture the volatility effect is through a manager that has carefully considered the implementation issues inherent in these strategies.

Factor tilts

These approaches aim to tilt portfolios toward attributes that have been shown in academic literature to add value over time. Typically these are factors that are associated with active management ‘styles’.

There continues to be debate as to whether these phenomena are behavioural, compensation for additional risk, or both.

Three academically recognised factors are:

1. Value — ‘Cheap’ stocks (where the current market price is perceived to be less than the market average as measured by metrics such as Price/Earnings and Price/Book) outperform ‘expensive’ stocks (those where the market price exceeds the market average) as the market reajdusts towards fundamental valuations.

2. Momentum — Stocks that have performed well recently, say over the last 12 months, continue to perform well (and vice-versa).

3. Size — Stocks of smaller companies have higher returns.

It is possible to analyse portfolio performance and attribute returns to sub-groups of stocks with these features. More recently there has been interest in managing these ‘factor exposures’ separately (and more cheaply), in part a recognition that some active returns can be explained by these factor tilts.

PerformanceFigure 02. shows the return, standard deviation and risk-adjusted returns for a number of well-known equity smart beta strategies using US returns between 1964-2012.

Figure 02. Popular smart beta strategies


ImplementationThe availability of investible strategies has improved and is likely to continue to improve as the concept garners greater interest from the investment management community. Pooled strategies exist for a select number of strategies and where there has been client interest, managers have shown a willingness to add appropriate investment vehicles.

In general we prefer smart beta strategies to be implemented over a broad universe. Breadth and depth are instrumental to the successful application of approaches that are systematic in nature, such as smart beta. We do not think a narrow or too concentrated opportunity set is suitable for the use of some smart betas. This might lead to unintended risks, such as over-concentration in certain industries/sectors/countries and/or for stock-specific risk becoming too dominant in the portfolio (a similar argument, however, can be made on market capitalisation approaches in narrow markets). Furthermore, a narrow opportunity set might lead a systematic approach to necessarily ‘force’ a solution to maintain some diversification, due to a lack of alternatives.

There is, however, no hard and fast rule as to which market offers a wide enough opportunity set. Our preferred option is for a developed plus emerging markets universe as it provides the greatest breadth and depth. Developed market only, emerging market only or US market only mandates are also likely to be wide enough to allow for a good application of smart beta approaches. However, in concentrated/skewed markets such as single countries or sub-asset classes (for example, Australian equities or frontier markets), using systematic approaches without considering the market’s specific idiosyncrasies might not be ideal. Similarly illiquidity or high custody costs in some markets create issues in implementing some strategies. In these cases, potential investments should be considered on a case by case basis, taking into account the characteristics of the market and the investor’s underlying objectives.

The assumption for replacing an active allocation is that smart beta captures some of the alpha that active managers can deliver, but at lower costs. Two other advantages of smart beta as an alternative to active management are:

1. Capacity is higher than for most actively managed strategies (lower turnover and less concentrated).

2. Higher levels of portfolio redundancy in traditional active multi-manager configurations can lead to a convergence towards capitalisation weights with some residual style tilts that can be easily and cost effectively replicated using smart beta strategies.

Smart beta strategies are generally not constructed as relative return ‘products’, and typically have high tracking error relative to a market capitalisation portfolio. This means that the strategies will perform very differently to market capitalisation weighted portfolios and can underperform market capitalisation substantially, potentially over a long period of time — typically during strong market rallies and ‘bubbles’. However, there are also more aggressive smart beta strategies that may underperform significantly in bear markets or sharp drawdowns. There is a chance of regret risk and consequent withdrawals from a strategy at the wrong time. Investors should therefore have a long-term approach to the investment — we would suggest a timeframe of at least five to ten years.

How should smart beta approaches be benchmarked? It is important for investors to determine, in advance, their objectives from an investment in equity smart beta strategies. Different approaches to measurement may determine whether such an investment is considered a success or a failure. We believe monitoring versus a benchmark should be focused on the long term.

For some smart beta approaches, the strategic rationale may be to reduce the overall equity beta exposure of the portfolio (that is, de-risking). In this case, we are supportive of the strategy being measured against a market capitalisation index over the long term on an absolute risk-adjusted (Sharpe ratio) basis. We would also support benchmarking against a suitable combination of a market capitalisation index and cash (which would be another way of lowering the beta of the equity portfolio) over the medium term. In cases where a manager is managing their approach against a specific index (for example, an MSCI minimum volatility index) comparing to said index is also appropriate.


Smart beta within fixed interest

Screened fixed interest

Traditional fixed interest indices, which weight issuances according to outstanding debt, have a fundamental flaw in our opinion — the most indebted issuers constitute the greatest portion of the index.

Government bond benchmarks, in particular, have high risk concentrations in the US and Japan. The Barclays Capital Global Treasury Index, for example, had a 54% weight to these two countries at the time of writing.

Similar to many equity smart beta strategies, we believe that any approach which breaks this reliance on issuer size in a sensible manner represents a significant improvement compared to the traditional indices.

Towers Watson has worked extensively with global funds management providers to explore solutions for clients that reduce these concentration risks.

An example of this style of approach (for global sovereign debt) is to establish two simple caps on exposures which significantly alter the characteristics of the index — such as a cap on individual countries, and a collective cap on Eurozone countries.

In the current environment of record-low sovereign bond yields globally, this style of smart beta strategy allows investors to maintain global sovereign bond exposure without assuming the same level of exposure to the US, Japan and heavily indebted Eurozone countries.

Other alternative methods of weighting fixed interest securities in the government bond space could be to weight according to issuer GDP or fiscal sustainability (based on economic fundamentals). These methods do, however, have associated concentration issues which would also need to be managed.

While this outlines some smart beta approaches in fixed interest, we would be generally supportive of any strategy which breaks the reliance upon debt levels and re-weights securities in traditional indices in a systematic and sensible manner.

Figure 03. Barclays Global Treasury Customised versus Market Cap (as at March 2013)

% o

f ben

ckm

ark

35% 30% 25% 20% 15% 10% 5% 0%

RegionBarclays Global Government Index Barclays Customised Sovereign Index

Eurozon

e USJap

an

Great B

ritain

Other Europ

e

Asia (e

x. Jap

an)

Middle Eas

t – Afric

a

Latin

America


Alternative asset classesWe believe there are a number of natural extensions of the theory and philosophy around smart beta which are worthwhile pursuing in asset classes that have historically been expensive, difficult to access and/or illiquid in nature.

Smart beta thinking can provide many of these desired exposures in a simple, low cost, transparent and systematic manner, or provide easier access to diversifying exposures which were previously difficult to access.

Enhanced commodity futures

Commodities provide diversification across the business cycle, with prices being highest at the end of the cycle when capacity is lowest, whereas equity returns tend to peak earlier in the cycle. Additionally, commodities provide reasonably strong inflation-linkages, being part of the consumer basket in most cases.

While this type of exposure is desirable from a strategic perspective, passive investment in commodities has a number of vulnerabilities. We believe that many of these weaknesses can be improved by systematic tweaks to the investment process.

For example, the common commodity futures indices (such as S&P GSCI) are based solely upon the front future contract, which doesn’t seem to fully represent the entire commodity sector anymore and is open to being front-run by active investors.

Investing in longer dated contracts or implementing continuous/daily rolling should theoretically avoid the crowding of passive investors in the shorter dated future contracts, and should also make better use of market liquidity.

Core listed property and infrastructure

Core property and infrastructure investments usually involve the purchase of unlisted, illiquid assets which provide the following desirable characteristics:

• long duration assets

• strong cash flows that are often regulated, contracted or otherwise protected

• inflation linkages

• low correlation with traditional equity markets.

Due to the illiquid nature of unlisted assets, investors often attempt to obtain exposure to these characteristics through listed vehicles. Historically, these vehicles have had an unacceptably high correlation to listed equities, often to the extent

that the desirable characteristics outlined above are compromised. Another problem with investment in listed infrastructure markets specifically is the typically high exposure to energy generation assets (which have relatively high volatility of earnings).

We believe an investment strategy which specifically targets stable, ‘core’, developed assets with predictable earnings throughout the economic cycle and relatively low levels of gearing, mitigates many of these issues while providing access to the desirable characteristics of infrastructure and property assets. We further note that investments in this style of listed vehicle typically have lower correlation with equity markets than their traditional counterparts, given their lower exposure to assets with high leverage and development risk.

Foreign currency carry

Currency carry strategies invest in high yielding currencies using capital from low yielding currencies. The attraction of this strategy is that the real interest rate differential rewards the willing investor over time.

The main risk involved in these strategies is that large, adverse movements in exchange rates have the potential to swamp the carry return over the short term. We note, however, that this can also work in favour of the FX carry investor, and often does, as real exchange rate appreciation tends to follow for countries with rising interest rates.

One way to mitigate the risks of adverse exchange rate movements is to diversify across countries. For example, with 10 liquid developed market currencies, there are 45 currency pairs an investor could potentially take positions in.

A simple smart beta approach would weight each of these pairs equally, with the higher interest rate currency being bought against the currency with lower interest rates using forward contracts. The rationale for such an approach is that higher interest rate currencies tend to outperform lower interest rate currencies over the long term.


Emerging market currencies

Emerging market currency strategies invest in cash and short-dated bonds denominated in emerging market currencies. This provides the investor with an unhedged exposure to emerging market currencies.

We believe that, in general, emerging market currencies will outperform developed market currencies over the longer term and offer protection against low growth in the developed world. We expect emerging market cash to outperform developed market cash for three key reasons:

1. Higher productivity growth in emerging markets should lead to currency appreciation over the long term.

2. Many emerging market central banks have historically suppressed the value of their countries’ exchange rates, however trade imbalances are now stressing this process.

3. There is a heightened risk of devaluation or non-return of assets in emerging market countries, for which a premium typically has to be offered to investors.

We recommend that a semi-passive approach be taken to this asset class, with a largely buy-and-hold approach taken to emerging market currencies subject to the manager’s view on country-specific risks and which countries might relax their currency suppression sooner.

Reinsurance

The insurance risk premium compensates investors for very different risks than the equity or credit risk premia. Traditionally, the impact of natural disasters on financial markets is brief and localised, and financial market movements have no impact on the

frequency or severity of natural disasters, resulting in very low levels of correlation.

There are two key ways in which investors without the substantial scale required to obtain the exposure directly can access this type of investment, namely:

1. insurance companies’ equity

2. catastrophe bonds.

While the first option above is the easiest way to gain access to the reinsurance market, we believe the additional correlation with the equity market this introduces would compromise a key reason for this investment. Additionally, we note that the majority of investors would have exposure to reinsurance companies through their existing equity portfolios.

Catastrophe bonds, which usually have a term of three years, have the same pay-off as a traditional bond, except in the event of the insured risk occurring, when some or the entire principal is used to cover the reinsurance claim. This style of investment gives direct access to a number of different catastrophe-related risks.

The obvious risk to reinsurance investment is the (relatively low) probability of substantial losses due to catastrophic events. We believe that these risks can be largely mitigated through adequate diversification across regions and risk perils.

It is important to adopt a reasonable time horizon for reinsurance investments. Like any type of insurance, a premium is collected to reward the insurer over the longer term for protecting the insured against certain events. Therefore, although a loss will assuredly be incurred at some point, over the longer term (three to five years) a reinsurer with a well-diversified portfolio is expected to have made a profit in aggregate.

Figure 04. Risk and return characteristics of a range of smart beta strategies from February 2002 to December 2012

Return in excess of cash % pa

Volatility % pa Sharpe ratio Max drawdown

Equities AW: fundamental indexation 7.0 19.1 0.37Equities EM: fundamental indexation 0.65Listed infrastructure 6.6 0.61Index: MSCI All World 3.2 0.19Commodities 0.44Volatility premium 1.4 4.5 0.31 17.3Reinsurance 4.3 2.3 4.3Momentum 0.68 17.0Secured loans 2.9 7.2 0.40ABS 3.9 5.9 0.66 23.1FX carry 4.2 8.9 0.47EM currencies 6.6 0.48Index: HFRI 1.1 5.4 0.21

Returns in USD Source: Bloomberg, Barclays Capital, various managers Note: some of the results use back tested data

7.7

16.119.124.810.817.017.6

13.3

13.7

9.11.87

58.461.535.855.853.0

31.5

32.134.325.5


ConclusionIn this paper, we have provided an overview on the smart beta investment thesis and some of the more common and implementable strategies. We continue to observe an increase in both the number of institutional clients allocating to smart beta strategies as well as the diversity of smart beta strategies available.

Towers Watson is deeply entrenched in the smart beta movement and globally our clients added 65 new smart beta mandates to their portfolios in 2012. Our vast experience and broad understanding of the smart beta universe is demonstrated in Figure 05., which shows Towers Watson clients already have $20 billion of assets invested in smart beta strategies.

The intention of this paper is to stimulate thinking on where and whether smart beta strategies could be appropriate for your portfolio.

If you wish to discuss any of the approaches to implementing smart beta in more detail, please contact your Towers Watson consultant.

Figure 05. Total smart beta exposure for Towers Watson clients in 2012 ($US bn)

Bonds

Commodities

Real estate

Equities

Infrastructure

Reinsurance

Hedge funds

11.32.0

2.7

1.61.7

0.3 0.3

towerswatson.com

Copyright © 2013 Towers Watson. All rights reserved.

The information in this publication is general information only and does not take into account your particular objectives, financial circumstances or needs. It is not personal advice. You should consider obtaining professional advice about your particular circumstances before making any financial or investment decisions based on the information contained in this document.

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ContactFor further information please contact your Towers Watson Consultant:

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About Towers WatsonTowers Watson is a leading global professional services company that helps organisations improve performance through effective people, risk and financial management. With 14,000 associates around the world, we offer solutions in the areas of benefits, talent management, rewards, and risk and capital management.

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