If the financial crisis of a decade ago taught us anything, it’s that the liquidity of traded financial instruments is unpredictable and can fluctuate wildly in a matter of seconds. During the crisis, the eventual loss of liquidity, combined with the highly interconnected nature of modern directives, ultimately led to a rapid cycle of collapsing prices.

Changes post-crisis

In the years since the crisis, regulators have responded by exploring new rules and statutes aimed at requiring fund managers to report and maintain a plethora of data about the liquidity of their portfolios, including the time it might take to sell them. In the U.S., for example, all eyes are on the new set of rules mandated by the SEC aimed at quantifying liquidity risk in most mutual fund and ETF portfolios. Directed towards the risk that a fund could not meet redemption requests without significant impact on remaining investors in the fund, the new rules require a fund to classify positions around four main parameters.

Rules, rules, rules

Most of these new rules around data come into effect next year, with reporting requirements starting June 1, 2019 for large funds and December 1, 2019 for smaller funds. These are likely just the beginning of many compliance burdens for fund managers when it comes to measuring liquidity. This means managers will need easy and efficient ways to assess the true liquidity of their portfolios to satisfy regulators’ demands, which can be difficult because not all assets or markets are “equal”; what might be a fairly straightforward and easy to calculate transaction in a “normal” market can be difficult to estimate in markets that are less efficient. In fact, markets for different bonds are highly variable even across multiple tranches of the same issue and information is very sparse.

How to satisfy these new demands?

In order to satisfy regulators’ new demands, it is essential to have technology that helps visualize how the bond markets create liquidity. At StatPro, we have created a module that algorithmically determines each bond’s relative liquidity score from a number of market variables like amount outstanding, bond age and size of the bond’s specific market. We also surveyed a wide array of individuals that operate in various areas of fixed income markets, as well as in different currencies and issuer industries, to create unique profiles. We then asked the traders to quantify liquidity for representative bonds from each cluster, giving us a meaningful calibration from each bond’s relative liquidity score to the time and cost to liquidate the bond.

Conclusion

Ultimately, we hope such a tool will benefit traders by allowing them to easily and quickly satisfy regulatory demands for measuring and reporting liquidity risk.

Like most new regulatory measures, we think the SEC’s new rules will take some time to really be applied properly. It will also initially be subjective; what’s relevant for one portfolio manager may be just market noise for others. The bottom line is that the ability to liquidate any asset depends on three things – how much of it you have to sell, how quickly you must sell it, and the price you are willing (or required) to take – and then systematically tracking such exposure. To us, the goal of the regulation is to measure the likelihood a fund will get caught – as Warren Buffett once said – swimming without a bathing suit when the tide goes out.

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