A modernized toolkit for resilient
strategic asset allocation

BlackRock |01-Dec-2018

Incorporating uncertainty and moving away from point return estimates are important steps for building resilient portfolios, in our view. Our toolkit allows investors to plan for downside scenarios and adjust their asset allocation around individual needs and objectives – including time horizons.

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To create resilience within portfolios, we need to recognise that return assumptions are uncertain. Point estimates overstate the confidence any investor can have in the outlook for asset returns. Without constraints around the process, this can lead to overly concentrated allocations and leave portfolios vulnerable to potentially sharp drawdowns in those larger allocations. Recognising this inherent uncertainty in the central return expectation allows us to create portfolios that are more aware of the downside risks.

Chart: Emphasizing the downside

Median and other pathways for total returns of our multi-asset allocation on 5- to 20- year horizon

Emphasizing the downside chart

Our prior CMAs expressed return expectations as two point estimates – a five-year and a long-term view. We introduce two important changes. First, for any given time horizon, we generate a range of pathways around a central return expectation. Second, we map out asset class returns along a full spectrum from five years onwards, allowing investors to build time horizon-specific portfolios. Our potential return pathways are the result of a stochastic simulation – a random distribution of future returns informed by a combination of the distribution of historical returns, our central return expectations and our estimates of uncertainty. We anchor the simulation to our expectations of macro factors, such as economic growth and inflation, as well as asset-specific factors, such as earnings growth for equities. The chart above shows how our approach can be used. From the myriad possible outcomes, investors can focus on a specific set most relevant to them.

This goes well beyond traditional portfolio construction approaches. These methods construct asset allocations by balancing return and risk assumptions, yet they assume no uncertainty about central (median) return expectations. Robust optimisation improves on mean variance by directly incorporating the uncertainty inherent within our central return expectations – and helps determine the highest possible potential returns under negative scenarios in a fine-tuned way. We believe our systematic approach mitigates the need for ad-hoc fixes – such as forcing minimal allocations to an asset class – that investors typically use to counter the limitations of methods such as mean variance optimisation. The result? Portfolio allocations are more diverse and less vulnerable to changes in return estimates, as we show in our examples. This approach puts the trade-off between returns, volatility and downside risks at its core.

Our new CMAs give a view of returns over an entire horizon – a term structure. We show returns from five years and beyond. Such a detailed view of potential returns over time allows investors to think about the future in a more realistic way that could not be achieved with a few point estimates. Investors can tailor their asset allocations and see how different scenarios affect specific points in time when cash flow considerations, such as redemptions or liability payments, may be paramount. If an investor has specific needs at a seven- or 15-year horizon, those can now be accommodated. An investor can then easily visualize the different paths a portfolio’s returns might take along the way to these points – especially downside scenarios – by using our potential return pathways.

Chart: Evolving over time

Annualised return profiles of our hypothetical 10—, 20-year and long-term allocations, December 2018.

Evolving over time chart

Investors with different time horizons for maximising returns relative to risk can end up with different portfolios. See the chart above. Multi-asset portfolios with similar risk and volatility objectives can look very different when assessed on 10- or 20-year horizons. Equities play a greater role in the long-term allocation – effectively the portfolio leans towards a broader array of macro factors for the same targeted return and expected volatility. We present here our strategic allocations on these horizons. The long-term equilibrium allocation is our benchmark against which our strategic preferences – as presented earlier – are determined. We can build portfolios purely based on our long-term views, yet we can also adapt them to any investment horizon. Allocations will change more at shorter horizons than longer ones as market conditions change.

These portfolios incorporate a greater aversion to downside risk by having been optimised on the potential return pathways below the median outcome. The bottom-half outcomes figures below show how those returns compare to the annualised expected return based on all outcomes from our return pathways

We believe investors need more than just asset class return assumptions to build resilient portfolios. The widespread adoption of factors has made them an essential component for designing the SAA. Exposure to factors can offer returns that straddle asset class boundaries and both indexing and alpha-seeking strategies. Factors are the broad, persistent drivers of returns that can be captured in a systematic and cost-efficient manner through indexing or factor strategies. Factors clearly need to be integrated into any investment framework, in our view. See our July 2018 paper Blending alpha-seeking, factor and indexing strategies: a new framework.

Chart: Making the most of style factors

Expected 10-year annualised returns from hypothetical equity allocations to style factors

Making the most of style factors chart

We differentiate macro factors – the drivers of returns across asset classes – from style factors, which explain returns within asset classes. Macro factors can often be captured by slow-moving, broad indices. Macro factor views are embedded in our long-term allocations. But to capture style factor returns, investors usually need to hold more dynamic portfolios. We use BlackRock’s style factors defined in the paper above: value, carry, size, momentum, min vol and quality. We have expanded our CMAs to include return expectations for equity style factors, enabling investors to build them into the SAA.

There is no one-size-fits-all answer to these portfolio construction questions: the answers will depend on an investor’s objectives and constraints. Different investors will also target different mixes of beta, style factor and alpha returns. Our CMAs reflect this and can accommodate explicit allocations to style factors as a way of spending the equity risk budget – improving potential returns for a limited increase in active risk, or volatility, relative to the original equity allocation. The chart above shows the return impact we would expect from tilting a portion of our 10-year equity allocation towards style factors while maintaining the original equity beta stance. A view on style factors can result in a material changes to the equity allocation.

Philipp Hildebrand
Philipp Hildebrand
Vice Chairman, BlackRock
Jean Boivin
Jean Boivin
Head of BlackRock Investment Institute
Anthony Chan
Director
Lisa O'Connor
Managing Director
Paul Henderson
Director
Simona Paravani-Mellinghoff
Global Head of Investments, BlackRock Client Portfolio Solutions
Vivek Paul FIA
Vivek Paul FIA
Senior Portfolio Strategist, BlackRock Investment Institute