Our Asset Allocation Approach
Matt Brennan, Head of Asset Allocation & Research, runs through the Scottish Widows asset allocation process. Matt led a recent review that fine-tuned the Asset Allocation Team’s investment philosophy, principles and process.
The Scottish Widows Asset Allocation Team makes the allocation decisions across our multi-asset fund range, including the Managed Growth Funds.
Philosophy
My Team’s Asset Allocation philosophy encompasses a fundamental belief that investment markets are broadly efficient and longer-term realised returns are relatively predictable, tending to revert to long-run averages. However, shorter-term returns are difficult to predict. As such, we believe that by focusing on longer-term customer goals, we’ve the advantage of being able to ride out and look through short-term market gyrations. Other facets of our philosophy, include:
- We look to harness the benefits of diversification as fully as possible.
- A view that growth assets such as equities tend to outperform other major asset classes over the long term, while noting, however, that at different economic and market conditions, the trade off between excess return and excess risk changes, and therefore the split between growth and defensive assets is the most important portfolio decision.
- An asset allocation process should evolve over time and adapt to changes in the global economy. As we do not have an in-house fund management business, the Team can cast its net wide across asset classes, allowing us to adopt new asset classes in a timely fashion.
- In our view, responsible investment can go hand-in-hand with an asset allocation process, as systematic risks impact future growth and can cause volatility through uncertainty. Therefore, incorporating RI can help to build more-resilient portfolios.
Investment principles
Guided by our Philosophy, we’ve introduced five principles that are applied over all our customer funds and incorporated into the asset allocation process:
- There is a customer-first focus because it’s customer money that’s being looked after, and we want to give them the investment outcomes they need. As such, we’ve aligned our portfolio risk bands with those used by intermediaries.
- Our process is data-orientated, with my Team working to harness the power of data to help deliver robust returns. For example, we use long-term economic growth forecasts, market data and historical analysis to help understand potential risks and asset correlations.
- The process is cost-aware, aiming to implement portfolios in a cost-effective way. There’s a focus on, for example, asset-class liquidity and weighing the costs of changing portfolios against the expected benefits.
- It’s also scalable, as we aim to ensure the process works and grows with us. We’ve developed a three-tier asset allocation framework to drive consistency throughout our fund range, and to enable it to be future-ready.
- The process is robust, and adaptable to change as and when new ideas develop, or market conditions change. For example, we’ll look beyond traditional public-market investments for opportunities to improve returns and portfolio diversification.
The asset allocation process
So, what are the key elements of our asset allocation process? The broad direction of the asset allocation remains the same, specifically optimising portfolio asset allocations based on customer requirements – with the aim of maximising expected returns for each portfolio risk requirement level. However, we’ve made a number of adjustments to the process, including calculating our market assumptions in-house, rather than using third parties, and our risk banding scale has been adjusted.
The four stages of the new asset allocation process are:
Capital Market Assumptions
Capital Market Assumptions (CMAs) are our expected return forecasts for a broad range of asset classes. These consider the risks and interactions of asset classes, based on market and economic indicators. Risks analysed include measures of volatility, as well as liquidity, inflation expectations, and country and global risks. As a Team, we’ll challenge our own forecast assumptions by analysing the differences between our assumptions and those of others in the market. For example, comparing if our forecasts are relatively bullish or bearish on certain assets, like international equities or UK bonds.
Modelling
We then input our forecasts into market-leading software to derive an efficient frontier that shows what assets to hold and in what quantities for various levels of risk tolerances.
An efficient frontier is a concept that helps in portfolio construction. It represents the optimal portfolio positioning in each asset, showing the highest expected returns for each level of risk that has been defined.
We’ve developed a ‘building-block’ approach for the modelling of expected returns. For each asset class, the modelling starts with the risk-free rate for the market and then returns are added to this, considering what an investor would expect to receive for taking the risk of holding each specific asset type. This could include bond default risk for fixed income, or currency risk for international assets.
Customer requirements
For each portfolio risk level, an allocation is selected from the efficient frontier. We look to align market exposure as closely as possible to the leading risk profilers in the market, comparing our modelling outputs and methodologies with theirs. This is because we believe that around three-quarters of asset allocation returns are as a result of market exposure levels.
We’ve produced a seven-point sliding-scale risk banding, with the growth assets allocated at broadly equal intervals across a seven-point scale.
Forecasting
We work with third parties to understand forward looking risks, factor exposures, and potential stresses to fine tune our selection and ensure the expected outcomes of the proposed portfolio allocations align with customer expectations at each risk level.
Governance and controls
Overarching all of this, there are robust governance and controls across the process, including committee oversight. Additionally, we will regularly review our capital market assumptions and undertake Strategic Asset Allocation (SAA) to assess and optimise our funds on an annual cycle, or more frequently if market conditions change sufficiently.
Overall, we believe this process is future-fit, so that our asset allocation evolves and adapts to new information and changes in the market to ensure we continue to meet customer requirements.
