No need to choose between active or smart beta to beat the benchmark when both are on the menu

Key Takeaways:

  • A fixed income strategy combining active management and smart beta, and aiming at generating high returns over the long run with a risk level similar to the benchmark.
  • A 3-step investment process: 1) choice of an alternative or smart sovereign bond benchmark, 2) systematic approach where portfolio construction follows up an optimisation, 3) active management views are incorporated into the optimisation process.
  • A hybrid "enhanced beta" strategy new to the fixed income space and that can fit into the "core" fixed income bucket of an allocation.
Institutional investors relying on bonds as the core component of their portfolios must now be weary of their seemingly never-ending dilemma. On the one hand, they require higher yields than those currently available on “riskfree”, sovereign debt. On the other, they are reluctant to allocate to riskier assets in order to increase overall yields for fear of suffering substantial drawdown.

For many, the search for higher yield is a straight choice between active portfolio management and smart beta approaches. The trouble with employing active management alone is - like allocating to riskier assets - the possibility of drawdown. And in a very uncertain macro-economic environment, smart beta may not be able to respond to significant shifts in market sentiment.

The solution could be to combine active management and smart beta. This “best of both worlds” approachholds out the possibility of strong, long-term returns with an acceptable level of risk.

A freshly-prepared benchmark

So how might we build an alternative bond strategy that combines smart beta and active management? It can be broken down into three main processes which, combined, are unique in the bond fund management space.

The first is to choose an alternative benchmark. Standard fixed income indices are based on the outstanding amount of bonds. While this provides a highly liquid universe, this construction method has clear limitations, including over-exposure to countries or companies with overvalued bonds, high exposure to the most indebted issuers and not being representative of the global economy.

As weights are based on prices, issuers with a high level of debt are overweighted - for instance, in the Barclays Global Treasury index, 11 of the 37 countries represent 90% of the index. In addition, if a country’s debt is overvalued, investors are exposed to potential bubbles. Over-concentration can also occur in corporate fixed income: banks’ weighting in the Barclays US Corporate Investment Grade index, for instance, peaked at 35% of in the middle of 2008.

One way to diversify portfolios and reduce concentration risk is to adopt a more global approach that is representative of the shifting sands of the world economy. Among global indices, emerging markets with higher growth perspectives are currently hugely under-represented, with emerging market bonds representing only 5.5% of the Barclays Global Treasury index. This despite the fact that emerging economies produce around half of global GDP.1

In addition to adopting a global bonds universe, it is beneficial to replace the traditional bond benchmark construction with constructs that are based on factors other than outstanding bonds.These include equally-weighted and GDP-weighted indices, capitalisation-weighted, quality or agency rating and risk-based. It should be noted that constructing alternative indices for bonds is far more complicated than for equities and requires considerable human and technology resource.

A liquid accompaniment

The next step to building our alternative bond strategy is security selection and portfolio construction. Portfolio construction using systematic selection and implementation maximise expected return and minimise absolute risk in the portfolio. The fundamental idea is to input the manager’s best active views about the macro environment, regulation, investment flows, country analysis and so on into an “optimiser” – a computer program – which then creates the appropriate asset allocation. The optimiser always respects the wishes of the active management process so the portfolio stays within a pre-defined tracking error limit.

As well as external factors, the optimiser defines portfolio allocation using data that are endogenous to the security itself – such as volatility, correlations and liquidity. Liquidity is important to the strategy because the optimisation alone could lead to a relatively high turnover of securities.

Adding active management to the mix

In the final step, active interest rate, country and currency views within the optimisation aims to enhance return. We impose our views on the portfolio regularly seeking to anticipate changes in the marketplace. Only long experience of managing active strategies allows us to do this. Introducing active management to the portfolio adds further alpha, and reduces portfolio risk compared with a pure optimisation process. By adding our views to the optimisation, we expect not only to increase the excess return but to smooth performance and to limit the turnover of bonds which a pure optimisation framework would naturally lead to. That is, active management increases performance while decreasing risk and decreasing trading and liquidity costs.

The proof of the pudding

The result of this unique three-step process is increased overall returns, excess returns that are considerably smoother than those using an optimiser alone, and lower maximum draw-down. Portfolio management skills are critical to this process in order not to destroy the value created by the optimiser alone. In this sense, the strategy requires deep expertise both of quant methods and of actively-managed portfolios.

The benefit for investors is a viable alternative to a traditional bond strategy. The strategy does not necessarily produce the highest alpha, but provides the best returns on offer considering relative or absolute risk.

In addition, the strategy is calibrated to a benchmark and the tracking error constraints of the optimiser mean the strategy never strays too far from this benchmark. In this respect, it can be regarded as an “enhanced beta” strategy and is a natural fit for investors’ core bond allocations.

New recipe, new result

Not all investors will be familiar with the concept of smart beta within the bond universe. While smart beta has become well-known and is maturing fast in the equity world, its adaptation to fixed income markets is less familiar. This is possibly due to the relative difficulty of constructing smart beta bond indices. However, using simple approaches such as optimisation under tracking error constraint provides stable returns. Adding active management skills to this quantitative approach delivers an improved and more “intelligent” asset management process.

Bon appetit!
1 World Economic Outlook - IMF

Published in February 2016

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