Most investors of all sophistication levels are aware of the risk/reward trade-off when making decisions on where and how to invest their savings. The classic approach for determining this trade-off focuses on asset returns as the measure of reward and asset return volatility as the measure of risk. Volatility is a common measure for assessing the uncertainty around the expected returns from investing in a risky asset; the higher the volatility, the greater the possible losses that an investor could face from investing in the asset. Volatility, however, is only one measure for one type of risk: the total market risk of the asset. A less prominent, yet equally important concept, centers around liquidity risk. How does liquidity risk manifest? Take an investor who would like to withdraw funds from a personal portfolio to be place a deposit on a new house only to find that she cannot redeem the amount necessary to meet the down payment requirement. Additionally, the investor finds that the act of liquidating itself has reduced the market value of her portfolio. The investor is experiencing difficulties with the ability to liquidate her investments. Liquidity risk, hence, focuses on the ability – or more appropriately, issues that might impede the ability – of investors to convert their investments into cash within a reasonable time and at minimum cost. New regulations in the U.S. and Europe have brought this often-overlooked and hard to measure risk into the spotlight.
Beginning in 2019, the Securities and Exchange Commission (SEC), with intent to bring more transparency around and to promote investor protection from liquidity risk, will require U.S. registered asset managers offering retail investment funds to show proof of effective liquidity risk management programs. Additionally, the SEC will require registered managers to file annual reports disclosing the liquidity of each applicable fund. The commission will also require fund managers to confidentially notify them when a fund’s level of illiquid investments (those assets that take more than 7 days to liquidate) exceed 15% of net assets or when a fund’s highly liquid assets fall below a fund minimum. The key ingredient needed to successfully meet these requirements is a reliable methodology for measuring liquidity risk. Developing such measurements, however, has proven to be a difficult for many firms, as evidenced by a series of implementation delays and requirement easing since January 2018.
So how do we measure liquidity? The concept is tricky and there is no standard, acceptable methodology. If we return to the example of the investor trying to transfer investments for a down payment on a house, we can identify three components affecting her ability to redeem from her portfolio: order size, time and cost. Many investors may be familiar with the concept of a volatility surface which relates the strike price, implied volatility, and maturity of an equity option (an instrument that gives the holder the right to buy/sell an underlying stock at a predetermined price). Similarly, the size of a trade, the time to liquidate, and the cost to liquidate can be combined to draw a liquidity surface. Once drawn these surfaces can be used to help map out a liquidation horizon or manage expectations around the price impact from a trade. For example, a very large order, one that constitutes a significant portion of a security’s total shares outstanding, may take a longer horizon to liquidate if there are not enough buyers ready to make an acceptable bid. Placing such a large sell order may also require the seller to adjust ask prices downward to be able to trade the full amount, thus negatively impacting the assets’ final value. The liquidity surface mathematically relates the cost and length of time needed to trade a certain amount of a specific security. Using observed trading data as input, creating a liquidity surface should seem straight forward; however, that is not the case. Liquidity surfaces may be relatively easy to estimate in heavily traded equity markets; however, many portfolios include less traded assets for which mathematically deriving a liquidity surface from observable data is a less viable option. Additionally, liquidity metrics derived from available data, may not always reflect the true reality of the market environment in which an investor is trying to redeem.
The regulatory push for more transparency coupled with the lack of reliable measurement approaches introduces an important question for fund managers: where do they get credible metrics to satisfy both regulatory requirements? There are a few general ways firms can answer this question, each with advantages and drawbacks. One approach that some firms have taken, is to outsource the task of estimating liquidity for regulatory requirements to analytics providers who can hook up holdings data provided by client managers to proprietary quantitative models. A benefit of going this route is that for portfolios consisting of more heavily traded assets (e.g. equities or ETFs), readily available data should make quantitatively estimating liquidity metrics more straightforward. Further, using third-party vendors that apply similar methods increases the likelihood that liquidity is estimated consistently across peers and allows firms to focus on the day over day management of funds. On the flipside, relying exclusively on outside quantitative models to estimate available liquidity can mask full insight into the liquidity risk of the firm and could even pose a systemic risk. If a significant portion of the investment industry uses the same handful of providers applying similar methodologies, then firms across the industry will be exposed to the same model errors, especially for portfolios where less or no trading data is available. The latter point is what has prompted some firms to apply an internal approach to either supplement or replace externally provided analytics.
Firm-specific investment characteristics may make certain quantitative estimates less appropriate if not completely unusable. Individual firms could be constrained by factors that “out of the box” models will not account for but that could have material effects on their ability to meet redemption requirements. Firm risk officers (or members of any other function tasked with aggregating liquidity information for regulatory purposes) can also collect information from internal traders about their experience with and relevant idiosyncrasies of specific assets within the trading book. For example, funds that hold significant private placements may require engagements in labor-intensive negotiations to unwind certain positions. Consequently, liquidity estimates derived by a quantitative model for a heavily traded investment grade corporate bond, may not be applicable to private debt with the otherwise same risk characteristics. Where a large notional amount could be traded in a single day for a more liquid bond, it may take multiple days to negotiate specific terms in the unwinding of certain private deals. An adjustment may have to be made to vendor-provided info if not completely overridden by more accurate information to reflect this. While this approach allows firms to calibrate their estimates to more realistic figures, it can also bring additional SEC scrutiny on firms as well. The obvious reason being that any misstatement by internal sources (inadvertent or not) could significantly under or overstate liquidity when compared to peers. In the end, it is up to each individual firm to give honest efforts to not only meet regulatory requirements but also fulfill their fiduciary duty to clients. Too much focus on simply providing numbers to meet a minimum reporting requirement can undermine the reason that new rules were created in the first place: to force firms to think more thoroughly about the liquidity of their products.
Regulators must address fund managers’ concerns about any resulting operational hurdles and work with them to establish a functioning system that addresses the purpose that regulations were intended to solve in the first place: to protect investors. Latest developments show that the SEC is willing to reopen and ratchet back certain rules as they stand, to develop a more effective implementation process. The SEC recently announced the postponement of compliance for certain provisions of the Liquidity Rule. In addition, the SEC indicated that staff has engaged extensively with industry participants regarding the complexities of the Liquidity Rule; especially around concerns about public disclosures of liquidity classifications. Afterall, disclosing information about funds’ liquidity could also mean inadvertently divulging strategy insights to competitors. With that in mind, the SEC is working toward the goal of creating a more flexible, principles-based approach that balances reporting a fund’s liquidity profile with a firms’ ability to keep their investment strategies private. Although the program’s success is not clear, funds subject to the Liquidity Rule must have a written liquidity risk management program in place by December 1, 2018, and so, funds should not take the foot too far off the gas.
About the Author
Gal Vekselman, who has worked as a Business Intelligence Analyst for Guggenheim Partners, is an expert in the Business intelligence field specializing in self-service BI. His passion for helping people in all aspects of data management flows through in the expert industry coverage he provides. In addition to implementing complicated data management frameworks, Gal also trains and lectures in professional events hosted by Microsoft and SoHo Dragon.