AMP Super has delivered 12-month investment returns ranging between 10.1 per cent and 12.8 per cent for its MySuper lifecycle funds, and a return of 14.1 per cent for its AMP Future Directions High Growth fund.
AMP head of portfolio management Stuart Eliot says returns for the year were driven by three main factors: the ongoing results of a review of investment strategy undertaken three years ago; an overweight position in US equities that it unwound in the first quarter of 2025; and a low-cost, flexible rebalancing strategy that captured opportunities as markets fluctuated.
AMP’s overweight position in US equities started in 2023 based on “the thesis that the AI theme would run through equity markets for quite some considerable time”.
“We’re still very positive on that,” Eliot tells Investment Magazine.
“But when we came into February of this year, it seemed like the distribution of future outcomes was changing as things were starting to heat up a bit. And so we squared that up early February, which ended up being quite nice timing
“We went back to our benchmark. “Regrettably, we didn’t go underweight. It’s a lot harder to take an underweight position, because basically you’re going short of risk premium when you do that, so you have to have a lot of confidence.”
The third contributor was AMP’s ability to be “nimble and disciplined” through the wild conditions in March and April.
“We have portfolio structures that allow us to rebalance the portfolio with very low cost and quite frequently,” he says.
“As markets were having down days, we would be buying to get back to our targets. If markets were having strong up days, we would be selling to get back to our targets. That adds incremental return, and also you end up buying a little bit more than you sell, so that helps returns.”
Eliot says AMP’s rebalancing strategy blends active and passive exposures.
“Rather than putting money in and out of the active managers, which can be quite expensive, we were simply trading our index building blocks,” he says.
“And the other [aspect] was using derivatives, so, futures to get in and out. We’re at the sweet spot in terms of being able to do those kind of activities; if you’re behemoth then maybe it’s a little bit harder.”
Three years ago AMP made “a really honest assessment of why our returns hadn’t been as good as we’d hoped”. Eliot says that the benefits of that review continue to pay off.
“It was recalibrating how we spent our fee and active risk budget across the portfolio,” he says.
“We basically reduced our exposure to vehicle – in air quotes – ‘skill-based’ sources of return – so, stock selection in public markets and hedge funds,” he says.
“In our strategic allocation, hedge funds went to zero, and [we use] a lot more passive across public markets.
“That allows us to do quite a few things. One is that then frees up the fee and active risk budget to do things where there is a lot more potential for excess returns, and also more consistent returns, things like private credit, what we call diversified credit – that’s securitized loans, high yield, emerging markets, that sort of thing.”
AMP’s passive positions in fixed interest markets opens up additional return opportunities as well, Eliot says.
“That gives us a nice book of business, which is really attractive in the securities lending space, so we can pick up 20 to 25 basis points a year on those assets, with essentially no risk, which is really cool. How hard is it to make 25 basis points otherwise?”
AMP also “selectively and gradually” increased its exposures to direct infrastructure, mainly in Australia and Europe.
“That was not because of any prescience about US tax policy or anything like that, they were just the opportunities that were most attractive to us,” Eliot says.
“And also in direct property, we were able to buy funds that we were already invested in from sort of distressed sellers at pretty meaningful discounts.”
Eliot said AMP’s quantitative dynamic asset allocation model also made a significant contribution over the year. He says the model is governed by a rules-based process that is supported by extensive back-testing and refinement.
“A really important thing that we did [was] to trust the model.”
“Trading the systematic DA, which is all derivatives-based, through the wild times, Q2 this year was one of the best periods ever for our systematic dynamic asset allocation.
“You’ve spent all this time and research and effort and build governance processes around them, and, unless you have reason to distrust the models that you’ve built, you should just be again, following the plan.”
