Liquidity risk is an essential risk that all investors face. However, properly balancing liquidity requirements against other portfolio objectives can prove complex to manage, and several important investment impairments can arise within portfolios that encounter liquidity shortfalls.
While the most severe outcome from having insufficient liquidity is to default on a required cash outflow or commitment, there are many other disruptive impacts that a lack of liquidity can impose on an investment portfolio.
Illiquidity risk has the potential to deprive an investor of the advantages of investing for the long term and force undesirable trading activity. Further, liquidity-driven forced selling can push a portfolio significantly away from its desired target allocations.
Two general methods — direct and indirect approaches — can be used individually or in combination to manage liquidity risk.
The idea is to set aside a percentage of assets in cash. The size of this allocation to liquidity can be designed to cover some quantifiable period of expected net cash outflows — known as encumbered liquidity — plus additional funds to manage against unexpected outflows, or full liquidity. This approach, depending upon the predictability of future cash flows, would provide investors a measure of confidence that the forced selling of assets would not be required. As these earmarked cash reserves are drawn down, the investor can routinely tap the investment portfolio's convertible-liquidity sources to maintain the desired liquidity buffer.
While an explicit allocation of cash does not guarantee against the possibility of forced selling of assets into a down market, it can significantly dampen such risks and make them manageable through a more orderly process.
Although the direct method works well in meeting short-term and predictable cash flows, its heavy utilization of unproductive cash assets can make it a costly form of liquidity management over the longer-term. It is therefore worth considering a more dynamic hybrid process that complements the limited use of a direct approach with a structured indirect method. The indirect method attaches liquidity metrics, or scores, to all asset classes to accommodate the inclusion of important liquidity considerations when identifying and analyzing portfolios during asset allocation studies.
A liquidity metric can be quantified on a scale from zero to 100%, with zero reflecting low levels of liquidity and 100% reflecting a high level of liquidity.
The overall liquidity metric for each asset class can be derived by applying liquidity penalties to a beginning level of assumed market liquidity, constructing the framework as follows:
1. Establish market liquidity levels. The liquidity scoring process begins with a general notion of marketable vs. private/off-market transactions. Most marketable asset classes reflect a 90% or 100% starting level of market liquidity, while private asset classes reflect zero for market liquidity. This step of the process attempts to capture the tradeability of the assets.
2. Identify liquidity penalties. Market liquidity levels are further reduced by applying a liquidity penalty concept to reflect the potential erosion of liquidity that can result from asset class volatility and, perhaps more importantly, the sensitivity of that volatility to specific economic regimes. We include the following three liquidity penalties:
a. Growth penalty. The growth penalty captures the potential loss in liquidity that can result from asset class vulnerability to environments with disappointing or decelerating economic growth. Growth penalties range from zero, for asset classes with negative or low sensitivity to economic growth, to -50% for asset classes with significant positive exposure to growth. While it is not our intention to imply great precision in the -50% maximum penalty, the growth penalty attempts to generally quantify the liquidity impact as it relates to the risk of selling assets at distressed prices during growth-driven bear markets.
b. Inflation penalty. The inflation penalty captures the loss in potential liquidity that comes from asset class vulnerability to inflationary economic environments. Inflation penalties range from zero, for asset classes with positive or low negative sensitivity to inflation, to -17% (a third of the maximum growth penalty) for asset classes with significant negative exposure to inflation. The inflation penalty quantifies the liquidity impact as it relates to the risk of selling assets at distressed prices due to an inflationary-driven event.
c. Volatility penalty. Although the combination of growth and inflation penalties described above adequately capture the liquidity impairments for most asset classes, the process includes an additional check on each asset class' general level of volatility to ensure that the overall penalty accounts for all sources of volatility, whether driven by growth, inflation or some other factor exposure. Volatility penalties range from zero, for low-volatility asset classes, to -40% for asset classes with elevated levels of absolute volatility. Importantly, the volatility penalty is only applied if it is larger than the combined impact from the growth and inflation penalties. This treatment protects against the potential double-counting of volatility impacts already accounted for through the growth and inflation penalty process.
3. Overall liquidity metric: The overall liquidity metric reflects the combination of market liquidity and the impact from applying the various liquidity penalties. Since zero is the lowest value to express illiquid asset classes, we apply a zero value to those scores that would have otherwise resulted in negative values (i.e., where the size of the penalty exceeds the market liquidity level).
The following exhibit illustrates our current liquidity metric assumptions for several major asset classes across the three steps described above and includes a formula to demonstrate how the penalties are applied within the process.
We provide a few general observations to draw attention to several key results of this framework and to provide some intuition as to how these liquidity metrics provide an appropriate quantitative representation of important liquidity characteristics.
• Cash equivalents. Unsurprisingly, cash has a score of 100% for both its level of market liquidity and for its overall liquidity metric.
• Private equity. Due to its private/off-market transactional nature, private market equity has a value of zero for its market level of liquidity. As such, despite its proposed growth (-50%) and volatility (-40%) penalties, it maintains the minimum liquidity metric score of zero — i.e., there is no need to apply a penalty.
• U.S. stocks. While U.S. stocks begin with the maximum market-liquidity score of 100%, its overall liquidity metric drops to 50% due to the 50% growth penalty. This captures the downside volatility of stocks during weak growth environments and effectively indicates that U.S. stocks have half the liquidity they would have if we only consider tradeability. We do not apply the -24% volatility penalty in this case since the growth penalty sufficiently reflected the critical aspects of liquidity erosion from volatility risk as it relates to stock drawdowns. As a point of context against other asset classes, U.S. stocks' liquidity metric of 50% suggests that it fits at the midpoint between the dependable liquidity of cash and the illiquidity of private equity. It is such relative comparisons between asset classes, rather than the absolute values of the figures themselves, that make these metrics valuable when examining the potential trade-offs among various candidate portfolios.
Each level of liquidity score can then be used as inputs in asset-liability studies. Along with expected return and risk levels, a comparison of liquidity scores across candidate portfolios can serve as valuable information from which to drive portfolio preferences.
A combination of the direct and indirect approaches is ideal for most investors and can support a robust decision-making framework encompassing liquidity management. The introduction of quantitative asset class liquidity metrics provides a powerful tool in managing this critical risk against other potentially competing portfolio priorities.
Steven J. Foresti is a managing director of Wilshire Associates and chief investment officer of Wilshire Consulting in Santa Monica, Calif. This article represents the views of the author. It was submitted and edited under Pensions & Investments guidelines, but is not a product of P&I's editorial team.