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Subtle charm in new asset allocation models

There is an over-abundance of literature about the failure of traditional asset allocation models, and the need for a new alternative that will solve all the world’s problems. But a new model by Morgan Stanley Alternative Investment Partners caught my cynicism by surprise this week.

This new model adds liquidity – alongside return, volatility and correlation – as a key determinant in asset allocation decisions. This recognition smacked a lot of investors in the face during and after the GFC, and is not necessarily a new observation. But the way it approaches the problem resonates with me, and so possibly with many other non-investment professionals.

In common with some other new approaches to asset allocation, the Morgan Stanley (MS) model advocates moving away from allocating investments according to broad asset classes.

However it doesn’t replace this approach with the popular new way of allocating assets, namely, by looking at underlying risks. This is the approach now implemented by Alaska Permanent Fund and others.

Rather, it allocates assets according to what it defines as sources of return – beta, alpha and now liquidity.

The approaches are similar, in that this also provides a more transparent view of portfolio risk, and matches the portfolio with the investors risk profile, but there is a nuance in the viewpoint.

The new MS model acknowledges that the way investments “generate” returns means the model also entails different risks.

A US public equity ETF, for example, is often compared to a US public equity manager, as the performance of each depends on the performance of the equity market. However the latter is also dependent on the investment manager’s acumen and the liquidity premium generated from investing in less liquid assets.

By way of example, under this new approach, an asset allocation that had 40 per cent in equity, 30 per cent in fixed income, 15 per cent in hedge funds, 10 per cent in private equity and 5 per cent in real estate would translate to an allocation of 60 per cent to beta, 20 per cent to liquidity and 20 per cent to alpha.

This new model promises to account for portfolio nuances. It acknowledges the limitations of traditional mean-variance optimisation-based models that assume the risk and return of all asset classes are comparable, and that portfolio characteristics, and needs, are stagnant time.

In addition, Morgan Stanley says traditional asset allocation is myopic. It doesn’t consider how asset class characteristics change significantly over time, how decisions made today may affect investors’ future options, nor how investors’ needs vary with time.

So the AIP approach chooses allocations across return sources instead of across asset classes, and considers the changes in risks, returns and correlations of investments over multiple periods. When optimising the portfolio, it also uses Bayesian Forecasting, which allows investors to specify views regarding an investment’s future returns, as well as a confidence level in those views.

This new approach is similar to other evolutionary models in asset allocation in that they both focus on a total portfolio risk, and better understanding of matching the expected risk with the actual risk of the portfolio. But as with many things in life, the charm is in the nuance.


The Morgan Stanley Alternative Investment Partners approach is explained in the article “New Dimensions in Asset Allocation” which can be accessed here

Investment Management Journal

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