Three multi-asset funds compared 

Baillie Gifford Multi Asset Growth

Key data

  • Fundamental stockpicking multi-asset approach
  • AUM: £450m (€505m)
  • Inception: December 2015
  • Return target: 3.5% over UK base rate, net of fees annualised over rolling five-year periods
  • One-year performance: 8.4%

Baillie Gifford runs €8.3bn in its multi-asset strategies, divided between some 200 clients and split between four funds. All four funds have the same philosophy, use the same processes and are run by the same team, according to James Squires, investment manager within Baillie Gifford’s multi-asset strategy team. 

Two multi-asset funds are marketed to overseas clients – one is a yen-denominated fund while the other is US dollar-denominated.

That overall philosophy can be summarised as taking full advantage of the investment universe. The greater the asset universe, the more levers there are available to pull to both increase returns and reduce risk.

james squires

That universe of assets includes listed equities; property; investment-grade and high-yield credit; some asset-backed securities such as CLOs and RMBS; both developed and emerging market government bonds; infrastructure; absolute return and active currency. These are accessed using a liquid format.

Focusing on the Multi-Asset Growth fund, the team is not compelled to use any particular asset, and an asset will not be included if does not look like it will deliver the right returns or help to reduce risk. This fund will always have at least five different assets in the portfolio and use limits on the maximum weight limits to avoid the portfolio being overly dominated by one asset class.

For example, the portfolio will not have more than 40% invested in listed equities. Squires says allocations higher than this “will result in the overall portfolio’s risk profile being dominated by equities”. A lower equity weighting and genuinely broad range of assets makes a genuinely diversified multi-asset portfolio, which will have a lower risk profile, he adds.

Asset level decisions are achieved through fundamental, long-term research to better understand the nature of each asset classes. The team takes an in-depth assessment of long-term return drivers of the asset classes over the next 10 to 20 years.

Another core part of the investment process is to carry regular and substantial scenario analysis. Squires says: “Instead of trying to make predictions about what will happen, we explore all the possible outcomes and events and think about how each asset class will perform in each situation.” This gives the fund a good view on how the asset classes might behave and their risk profiles as well as which assets will dovetail well together.

“That focus on long-term returns and scenario analysis gives us an in-depth understanding of all the asset classes and gives us a good framework, which allows the investment team to debate and decide how to position the portfolio.”

Assets currently in favour are listed equities, emerging market government bonds and infrastructure. Squires says: “Equities are likely to benefit from the continued broad-based global economic growth while emerging market government bonds are underappreciated.” This asset class has a strong return profile given emerging countries’ investment-grade ratings and low debt levels. The key attraction of infrastructure is its stable, inflation-linked cash flows which offer both a good source of return and diversification benefits.

Winton Absolute Return Futures Fund

Key data

  • Quant multi-asset, multi-strategy
  • Inception: July 2017
  • Net returns: 1.6% from 3 July to end-October 
  • Daily dealing, trading global futures and forwards with an objective of positive returns on a rolling three-year basis
  • No volatility target
  • Winton’s Diversified Program, inception 1997, has overall AUM of $16.4bn (€13.9bn)

The Winton Absolute Return Futures Fund is a UCITS-compliant version of a strategy that the firm has been running for the last 20 years. Sebastian Maciocia, vice president in the client advisory team at Winton Group, describes it as a multi-asset absolute return fund trading around 85 global futures and forwards across commodities, currencies, fixed income and equities.

sebastian maciocia

The fund aims to produce a long-term compound return over three-year periods. Maciocia says that although the fund does not have a strict volatility target, leverage on the fund is managed so that annualised volatility is around 5%. This is around a third of the level of equity volatility over the last 10 years and half of bond volatility over the same period, he says.

The fund reflects the firm’s use of quantitative techniques and employs what it calls “the scientific method”. Like other quant funds, Winton Group forms a hypothesis about why a particular pattern might exist and then evaluates the robustness of this theory. If the hypothesis withstands the rigour of this scientific scrutiny, it is then codified into a set of investment rules.

Maciocia says: “Our approach differs from other quant funds because we recognise investing is a social science. A pattern is not a scientific law: markets and behaviour change over time.”

Through this research process, the firm has identified a number of strategies which have a better than 50% chance of making money over the long term. Over the short term, however, these strategies are only weakly predictive. Maciocia says: “It’s like finding a coin with a 52% chance of it landing on heads.”

In addition, these strategies must have a low correlation to manage risk when used together. Maciocia continues: “The combination of these strategies has the ability to make money over the long term.”

Each day the fund looks at price and volatility market data and then forecasts the returns, volatility, correlations and trading costs. Maciocia says: “That information allows the system to generate a target portfolio which the fund rebalances to every day.”

For example, one of the firm’s longest running strategies is trend following. Maciocia says: “This model predicts where a price is likely to rise or fall based on its past price performance.” If the model predicts the price will rise, the fund goes long and if it will fall, it goes short.

At the moment the fund is long equity indices. Maciocia says: “The stronger the signal that the market will rise, the more we will increase the allocation to that market.” 

Other strategies include ones which observe seasonal trends in futures markets while another seeks to profit from the tendency of futures markets to gravitate towards the spot price. A third is relative value, which seeks to profit from the differences in the term structures of related markets.

Maciocia says: “These strategies might be giving conflicting signals for a particular futures market so we net them off each other in order to determine our overall position.” But not every strategy will be given an equal weight in the return forecasting. Trend following has an approximately 50% allocation while the other strategies make up the other 50%. This reflects the maturity of the trend-following strategy relative to the other strategies.

Nordea Alpha 15 MA

Key data

  • Risk premia-focused, market-neutral approach
  • AUM: €783m
  • Target return: cash plus 7% pa over a full investment cycle 
  • Target volatility around 10% pa in normal market conditions and 15% tail volatility

Nordea’s Alpha 15 MA fund is designed to extract risk premia from global asset classes. Asbjørn Trolle Hansen, head of asset allocation at Nordea Investment Management, says the fund focuses on around 20 to 25 risk premia, which are dynamically managed and combined using both a quantitative and qualitative approach.

Trolle Hansen says: “While quant models identify the different risk premia and suggest how these should be traded, there is also a qualitative risk review of each trade before it is implemented.”

asbjorn trolle hansen

Nordea uses a broad approach to identifying its risk premia. “As well as comparing the relative benefits of different asset classes, we also identify different investment factors like value and carry,” Trolle Hansen says. “We look at where those investment factors can be found and then find ways to gain exposure to them.”

For example, momentum could be present both in an individual stock and an equity index. As the managers prefer fundamental factors, they focus on earnings momentum rather than price momentum. Individual investment factors can be found across different asset classes. For example, quality can be found in equities, currencies and even fixed income.

To ensure this very broad approach does not create unnecessary risk, the fund works in two dimensions. Trolle Hansen says: “The first dimension is the asset class and the second is the type of trade.”

An investment can be allocated to one of six buckets. The first four of these buckets are asset classes – equities, fixed income, currency and multi-asset. Each asset class is made up of different investment strategies like value or quality.

But each of those buckets has a market-neutral position. Trolle Hansen says the aim is for each to have very little beta so it is not exposed to market directionality. 

Knowing that each asset bucket has to have a market-neutral position means risk management is embedded into the research process: it becomes a fundamental part of the investment process, he adds.

The last two buckets are for directional strategies. Trolle Hansen says: “For example, momentum is often a directional trend so it will go into one of those two buckets.” The final bucket is for very short-term trading strategies which are often directional. “These two can be thought of as short- and long-term directionality,” he adds.

The overall fund also has a volatility target of 15% in the tail. Trolle Hansen says: “When volatility rises, we aim for the volatility of the fund to not be more than 15%.” In normal market conditions, they expect the fund to be closer 10%. He says: “When volatility spikes, we do not aim to reduce risk – we aim just to flag what volatility could increase to in those circumstances.”