A new model of liquidity

The risk-adjusted benefit of being able to rebalance a portfolio is worth tens of basis points, according to new research that assigns risk and return measures to liquidity so it can be analysed alongside other portfolio decisions. The award-winning research is now being used by large sovereign wealth funds, to determine the value they should put on allocations to illiquid assets.

In their paper, Liquidity and portfolio choice: a unified approach, authors Will Kinlaw, Mark Kritzman and David Turkington, use “shadow allocations” of liquidity treating it as an asset or liability depending on the purpose.

They say that liquidity can be deployed for offensive or defensive purposes, where an offensive use improves the optimality of the baseline (examples would be tactical or dynamic asset allocation), and the defensive restores optimality (such as rebalancing).

The purpose of the use of liquidity, will determine whether it is treated in the study as a liability or asset. For a defensive allocation of liquidity it becomes a shadow liability.

The authors use this framework to analyse liquidity, and the implications for asset allocation.

Because there is limited data, and theory, when it comes to shadow liquidity assets, the authors relied on simulations for their case studies.

One example considered a case where an investor could continually rebalance compared to where they couldn’t.

Thousands of Monte Carlo simulations later, they found that the risk-adjusted benefit of being able to rebalance is worth about 40 basis points.

“Being able to rebalance is an important use of liquidity, and this shows that benefit,” Will Kinlaw, senior managing director and head of the portfolio and risk management group at State Street Global Exchange, says.

“This research shows that liquidity is a concern for all investors, and it’s just not to meet cash needs, but it’s to capitalise on opportunities.”

Kinlaw, and his co-authors Mark Kritzman chief executive of Windham Capital Management and professor at MIT Sloan School and David Turkington a fellow State Street managing director, won the 2013 Peter L. Bernstein award for the paper published in the Journal of Portfolio Management.

One of the more important, and practical, implications of the study is it frames liquidity into the language of risk and return. This means it can be examined in the same context as other portfolio decisions.

“It shows that liquidity is ‘X’ so you know what you are foregoing. You can ask how much to allocate to illiquidity, or you can also frame it in the context of ‘given our allocations how much should we demand from illiquid assets’,” Kinlaw says. “We are working with a number of clients including a large sovereign wealth fund, which is using it to assess what premium to demand from illiquid assets. It has very practical applications.”

In the past liquidity has been assessed as a separate part of the portfolio.

“But we think this makes for arbitrary decisions regarding risk and return,” Kinlaw says. “What we are doing is accounting for reality, liquidity does have risk and return characteristics.”

The authors are not arguing that liquidity should trump other portfolio assessments, but that risk and return assumptions should be adjusted for liquidity.

“Some investors ask isn’t it already priced in, for example Treasury bonds versus mortgage instruments. And this is true, but only for the average investor. Every investor has different needs and liquidity profiles.”

By way of example, Kinlaw says given an asset or portfolio and its return is forecast with perfect insight, then if the asset is completely illiquid, it can’t be traded, then the return you get will reflect the forecast.

But if it is tradeable, then at the end of the year the return is not that of the asset, but something higher because it can be traded.

“It is a measure of the benefit the investor has from holding the asset,” he says.

The analysis has implications for asset allocation and portfolio construction decisions.

The authors looked at model portfolios with allocations to listed equities, fixed income, private equity and hedge funds, which are considered illiquid because of lock-up periods.

“Portfolio optimisations show an allocation to 80 per cent hedge funds and private equity. This is because the optimiser only sees risk measured as standard deviation. It doesn’t account for many things, including liquidity. Our model layers in liquidity considerations in the shadow asset allocation, which results in a reduction in the allocation to those assets.”

The winning paper was chosen through a blind review process by an independent committee that included Gary Gastineau (ETF Consultants), William Goetzmann (Yale School of Management) and Ronald Kahn (Blackrock).