How to mix and match your multi-asset funds

Different firms take slightly differing approaches.

However, generally, the risk assessment is undertaken based on the underlying asset allocation of the solution and an assessment of how the asset classes will behave in the future, from a risk/volatility perspective.

Capital Market Assumptions

To help with the assessment, capital market assumptions (CMAs) are used.

At Defaqto, we outsource our CMAs to a third-party organisation (Moodys Analytics) and it provides us with an expected level of annualised volatility, together with an expected return, for each asset class within our risk scheme. 

We then apply these to the asset allocations (both strategic and tactical), that we get directly from the fund manager, to get an overall expected level of volatility for the solution.

This expected level of volatility then corresponds to the volatility bands of our 1-10 risk profiles.

There is also some correlation analysis being performed, but as a basic concept, the expected volatilities for the asset classes, represented within the solution, are driving the risk-rating.

CMA’s across our asset class taxonomy may look something like this:

The above numbers are for illustrative purposes only and do not reflect the actual CMA’s provided by Moodys Analytics.

A single asset fund invested in UK equities, for example, would have an expected annualised volatility of 16 per cent, whereas, a diversified multi-asset solution with a 50:50 allocation to Global Fixed Interest (8 per cent annualised volatility) and UK Equity (16 per cent annualised volatility), could project a combined annualised volatility of say, 12 per cent and that would position it at risk profile 6 on the Defaqto scheme.

This is obviously an over-simplified example, but it does provide the basic framework for risk-rating.

However, due to asset diversity, simply doing the numbers is dangerous.

As such, we always interview fund managers to get a good understanding of how they allocate within broad asset classes, which may have an effect on our risk assessment.

For example, data may tell us that they allocate to UK Gilts but we need to understand the actual duration of the bonds they hold to provide a clear prediction of future volatility and the associated risk.

The same would apply to equities and we would seek to understand how a manager may be allocating within, say, UK Equities, to understand if there is a market cap bias to small, medium or large cap, which would, again, influence predicted volatility and the Defaqto risk-rating.

We always interview fund managers to get a good understanding of how they allocate within broad asset classes

Another piece of the jigsaw worth mentioning is the asset class referred to ‘other’.