Mutual fund managers have been concerned about bond market liquidity for several years citing the level of dealer inventories and concerns that regulations, such as the Volcker Rule and Basel III’s capital adequacy requirements are constraining the sell side’s ability to offer liquidity and warehouse risk. In light of mounting liquidity concerns, it is natural for investors and regulators to ask if mutual funds are prepared to meet redemption requests -without significant dilution of remaining investor interests – when central bank interest rates ‘lift-off’.

In the final rule 22e-4 adopted on October 13 the Securities and Exchange Commission (SEC) noted that, at the end of 2015, there were 10,633 open-end funds and ETFs (excluding money market funds) with assets under management of approximately $15 trillion[i]. Clearly investors in these funds hope managers have an “In case of emergency, break the glass, pull out the procedures, and begin an orderly and thoughtful response to satisfying redemption demand” plan. Benjamin Franklin has at least five famous quotes about money, saving and investing. The most fitting to describe this case is “By failing to prepare, you are preparing to fail.”

Inconsistent liquidity planning
The SEC observed that mutual funds use varying degrees of sophistication to ensure that they have the proper amount of liquidity to respond to redemption requests[i]. Under the Investment Company Act of 1940, mutual funds must meet investor redemption requests within seven calendar days. Investors, however, currently expect to have access to their funds the next day because new technologies and operational efficiency have made this practice the norm. The time to think about a proper response is before a crisis, not while you are in the middle of one.

Rule 22e-4 creates a regulatory framework which seeks to assist funds in designing a robust liquidity risk management program. The SEC’s stated goal is to reduce the risk that “a fund will be unable to meet its redemption obligations and minimize dilution of shareholder interests by promoting stronger and more effective liquidity risk management across open-end funds.”[ii]

In our view, the SEC is mandating that fund managers estimate what combination of assets they can sell to raise cash without significantly impacting the market value of those assets – or diluting the remaining investor interests.

To do this, the SEC is now requiring funds to use a methodology that enables them to put the securities in their portfolio into liquidity buckets (Figure 3). In this way, funds will be prepared under current and foreseeable future market conditions to determine what they need to do if they have to redeem interests. Entire positions do not have to be sold – portfolio managers have to balance size and price impact. For example, let’s assume that the fund has a $50MM position in XYZ bond. They know they can’t sell $50MM all at once because this may have an undesirable impact on the value of the bonds. However, the trading desk may be able to sell $10MM in a short period of time without significantly impacting the mark-to-market price of the remaining $40MM bonds they hold.

The entire “bucketing approach” relies on the fund understanding time to liquidation and market impact. In other words, they need to ask, “within an acceptable amount of market impact, how much of a position can be converted to cash within three business days or cannot be sold or disposed of in seven calendar days?”

How do you make this determination – especially for securities that don’t trade very often but otherwise have characteristics that make them easy to sell under normal market conditions? This isn’t solely a “bond problem.” Some ETFs and small/mid-capitalization stocks also suffer from similar liquidity challenges.

Enter the quants

To design and implement a robust, systematic liquidity risk management program mutual funds should have a quantitative framework to categorize current and potential portfolio assets. Fortunately, technological innovations, such as machine learning techniques, make it possible to run data-driven statistical models that estimate “liquidation cost” and “liquidation horizon” for securities that don’t trade very often. Many of these quantitative solutions, such as Bloomberg’s Liquidity Assessment Tool (LQA<GO>), were originally developed to assist the sell side in designing compliance programs for Basel III and the Volcker Rule. These solutions now have application for the buy side where similar but less prescriptive regulations such as UCITS and AIFMD addressing liquidity risk are in place.

SEC Rule 22e-4 is a tremendous opportunity for mutual funds, especially in times of crisis, to hone their operational procedures, reduce trading costs and learn more about their portfolios by elevating liquidity to a risk factor.

[i] See Securities and Exchange Commission, “Investment Company Liquidity Risk Management Programs,”
Final Rule, page 323 at https://www.sec.gov/rules/final/2016/33-10233.pdf.

[ii] See Final Rule, page 39.

[iii] See Final Rule, Page 8.