Faced with potential headwinds for traditional equity/bond portfolios, asset owners have been on the hunt for alternative, uncorrelated sources of return, which could potentially generate much-needed returns, while diversifying away from equity risk.
Multi-Asset Class Strategies (“MACS”) is one of the ways to diversify.
MACS investing involves navigating across and within a number of heterogeneous asset classes. Some basic approaches address this challenge by repackaging existing standalone single-asset-class capabilities (in equity, fixed income, currency, etc.) into a combined framework. These types of approaches start with separate portfolios for each asset class, then combine them from the top down.
The need for an integrated approach
We believe that a more integrated approach, which holistically evaluates markets within asset classes and relationships across asset classes, is better suited to deal with the complexity and the opportunities of multi-asset investing. Such an approach systematically evaluates risk, return and implementation costs for all markets and asset classes simultaneously.
Modern quantitative methods greatly help model the inherent complexity effectively and allow for comparisons within and across asset classes in an objective and consistent way. In particular, this type of methodology provides greater investment breadth, allowing portfolios to take fuller advantage of potential opportunities, via thousands of signals, forecasts and decisions across a large universe of assets.
An integrated approach to MACS investing seeks to capture both the idiosyncratic nature of individual asset classes and the relationships across these asset classes. This requires an expanded universe of factors for return forecasting: asset-specific factors seek to capture return drivers within asset classes, such as value, momentum, carry, and quality, each adapted to reflect the distinct nature of its respective asset class, while macro factors seek to capture cross-asset class effects.
How exactly to construct such macro factors involves some subtlety. Standard economic data has limitations as a forecasting tool, due to its lagged and backward-looking nature. However, Acadian’s research has shown that market-priced metrics – in particular, measures of cross-asset momentum – can serve as indicators of macro conditions that are predictive of future asset prices. This allows themes like growth, stimulus and inflation to be defined by market prices and incorporated into a multi-asset framework in a timely and actionable way, enhancing the potential for predicting asset returns.
Active focus on risk
Taking diverse assets and forecasts and combining them into a robust portfolio require particular attention to risk.
Individual asset classes may behave quite differently, and their underlying assets may interact in surprising ways, possibly leading to portfolios with undesirable risk exposures. Portfolio positions need to be understood in terms of the risk they contribute, and how this aligns with potential returns.
The ability to go long/short is a helpful tool to tailor exposures and mitigate unwanted risks, with the goal of maintaining low correlations at the overall portfolio level with respect to traditional and alternative betas.
We view modern MACS more as a capability than an off-the-shelf product, namely a skills-based approach that can be engineered to achieve specific investor outcomes.
Moreover, nimble implementation may enhance return opportunities and result in more efficient risk control. Well-implemented MACS strategies represent a best-of-both-worlds approach, borrowing investor focus and bespoke implementation from the “institutional, long-only world,” and looking to the model of the “hedge-fund world” for efficient implementation of investment ideas.
Outcome-oriented investing is an expanding and enduring trend. Investors can no longer afford to set a basic asset allocation with off-the-shelf investment strategies and hope for the best. They are increasingly looking to the funding needs of their plan first and working actively with a broad range of investment options to craft a program specifically tailored to a desired result.
Expertise in each asset class is required to build an effective multi-asset investment process.
MACS underscores the role that quantitative investment approaches are increasingly playing.
Institutions are getting better and better at working productively with managers to obtain the strategies and outcomes they need. Increasingly sophisticated institutional staff want ever more opportunity to fine-tune and customise. They want to work with managers who offer platforms of capabilities, rather than simply products. MACS is just one example of a customisable, creative solution to a low-return environment.
Ilya Figelman, senior vice-president and director of multi-asset class strategies, Acadian Asset Management
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