Focusing on the long run

05 March 2021

8 minute read

By Gerald Moser, Zurich, Switzerland, Chief Market Strategist and Nikola Vasiljevic, Zurich, Switzerland, Head of Quantitative Strategy

With COVID-19 vaccine rollouts taking place in many countries, hopes of economic normalisation are rising. Expectations of a strong recovery, coupled with ongoing structural changes, call for a review of asset allocation policy.

As investors prepare to position portfolios in a post-pandemic world, we examine the key component of the long-term investment process – strategic asset allocation (SAA). We are in the process of revamping our strategic asset allocation and in this article examine the broad framework of our upcoming SAA.

Strategic asset allocation

SAA is an essential part of our investment process. It is specifically designed to help clients achieve their long-term investment goals, while ensuring a superior risk-adjusted performance over a five-year investment horizon.

The optimal asset mix depends on the investor’s reference currency, ability to take risk, preferences and requirements regarding expected returns, liabilities, foreign currency exposures and investment styles, as well as other objectives. Therefore, investors’ profiles lies at the crux of the investment process.

An SAA review is a comprehensive and highly structured process in which optimal long-term asset allocation policies are defined for each reference currency, investment strategy and risk profile. It consists of two pillars: capital market assumptions and asset allocation policy.

The final set of outputs of the review process comprises expected returns and risks across a wide spectrum of asset classes and optimal asset mixes for various investment profiles. These results constitute a set of performance, risk and allocation benchmarks that are used in the portfolio construction process. Therefore, the SAA represents the backbone of our long-term investments.

Capital market assumptions

Capital market assumptions (CMAs) are forward-looking estimates of expected returns, volatilities and correlations over the next five years for a range of asset classes: cash and short-term bonds, developed government and investment grade bonds, high yield and emerging market bonds, equities, commodities, real estate, hedge funds, foreign exchange and private markets.

Each asset class is carefully selected for inclusion in investment portfolios based on four guiding principles: representativeness, investability, uniqueness of risk-return profile and diversification potential.

Depending on the investment approach (discretionary versus advisory) other criteria such as liquidity are considered as well. This is particularly important for an SAA that includes investments in private markets on top of liquid investments, which represent one of the key additions in our new SAA framework.

CMAs provide a long-term investment compass that helps clients to navigate through shifting landscapes of reward and risk in financial markets. Our future CMA framework will leverage on past information, however it is also conditional on the current stage of the economic cycle and incorporates our views regarding secular trends and possible structural changes. Taking stock of quantitative models and qualitative inputs ensures robust and forward- looking nature of our long-term views.

Expected returns framework

We will construct a five-year outlook to help to decompose expected returns into three components: income, growth and valuation. There are two exceptions to this rule. First, expected returns for hedge funds are estimated using a regression approach. Second, expected returns for private markets are decomposed into expected returns on a public market benchmark and an illiquidity premium.

The starting point in our CMA framework is the observation that all investments are ultimately exposed to the same underlying systematic risks, most notably economic factors. Our forecasts for expected returns and risk parameters are therefore strongly anchored by projected paths of the key macroeconomic variables: short-term interest rates, inflation and real GDP growth.

For example, fixed income and commodities are partially driven by the expected dynamics of short-term interest rates and inflation. On the other hand, expected returns for equities and real estate are closely linked to projected inflation and real GDP growth via the second (growth) pillar of total returns (see table).

Asset class Building blocks of total returns
Income Growth Valuation
Fixed income Treasury yield Credit spread Roll return Treasury yield curve adjustment Credit spread adjustment
Equities and REITs Dividend yield Net buyback yield Real earnings growth Inflation Multiple expansion
Commodities Collateral return Roll return Spot price adjustment
Hedge funds Quantitative approach
Private markets Public market benchmark Illiquidity premium

Source: Barclays Private Bank

The key takeaway is that a building-blocks approach is consistent internally. Expected returns are driven by distinct, clearly identifiable factors which are intuitively combined in a multi-asset class setting. By design, this framework ensures that investors are appropriately compensated for the risks taken. This is usually essential for a robust asset allocation process.

Optimal asset allocation policy

Diversification is the bedrock of any asset allocation and portfolio construction process. In investment circles, it is often said that diversification is the only free lunch.

In a portfolio consisting of core asset classes only (perhaps equities and bonds), diversification across sub-asset classes and implementation through a careful selection of funds and individual securities can help to reduce idiosyncratic risks. Investments into alternatives such as commodities, real estate, hedge funds and private assets can further improve portfolio diversification and stabilise returns.

Building a well-diversified portfolio can substantially reduce risks, however the systematic component cannot be eliminated. As such a structured asset allocation process is crucial for constructing investment strategies that can optimally balance out return and risk.

Optimisation engine

When building an asset allocation optimisation engine, two elements come to the forefront: reward and risk. Given a set of optimisation inputs such as expected returns, risk budgets and investment restrictions, our goal is to determine the asset mix which minimises risk or, alternatively, maximises returns.

The reward is defined as the expected portfolio return. In the SAA world, the aim is to design optimal asset allocation policies over multi-year investment horizons. Therefore, the key assumption in our model is that clients remain invested – and reinvest any interim proceeds they might receive – in their selected strategy over a long period. For this reason, we use expected long-term compound returns as the reward metric.

Understanding risk

In our SAA framework, the risk is defined using a tail risk measure. Although volatility – which measures the standard deviation of return distribution – is the most popular risk metric in the industry, it does not capture the full nature of risk. Indeed, volatility represents a symmetric risk measure that is only well suited to situations where asset returns are normally distributed. This assumption typically does not hold in practice. Extreme market moves are much more frequent than what is expected for normally distributed returns.

It is a well-known fact that – for many asset classes – return distributions are negatively skewed and fat tailed. Moreover, investors may be loss-averse and react differently to down and up markets. To address these concerns, we use expected shortfall as a proxy for risk.

Expected shortfall is a coherent risk measure that can be used to estimate the expected loss in the tail of distribution. Incorporating a tail risk measure into optimisation allows us to extend applications of our model to shorter time horizons and to consider optimal portfolio hedging strategies on tactical basis.

Towards the SAA review

Overall, our new SAA methodology is expected to offer a consistent and portable building-blocks approach for estimating expected long-term returns and risk parameters. It also allows asset allocation optimisation that can be flexibly applied for a broad range of investment strategies and risk profiles.

Over the next few months, as implementation of our new SAA framework approaches, regular deep dives into our thinking when it comes to SAA philosophy will be provided. Some topics covered today, for example risk management, CMA or optimisation, will be addressed in more details as part of this series of articles focusing on our new framework.


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