Boston Fed researchers look at ‘swing pricing’ tool that could stabilize certain investment funds
Research note explores ways to calibrate swing pricing. But how does it work?
During the onset of COVID-19, certain pooled investment funds – including money market mutual funds – experienced runs as many investors sold their shares amid widespread uncertainty.
To help increase stability, the Federal Reserve – with approval from the U.S. Secretary of the Treasury – established a number of emergency lending facilities. For example, the Money Market Mutual Fund Liquidity Facility helped stabilize short-term credit markets.
Following the pandemic, policymakers are investigating how to make these funds more resilient, said Kenechukwu Anadu, a Federal Reserve Bank of Boston vice president in the Supervision, Regulation & Credit department.
In a research note, members of the Bank’s Supervisory Research and Analysis Unit explore ways to calibrate one option that policymakers have: “swing pricing.”
Swing pricing could help increase funds’ stability
The note, called “Swing Pricing Calibration: A Simple Thought Exercise Using ETF Pricing Dynamics to Infer Swing Factors for Mutual Funds,” was written by Anadu, John Levin, Victoria Liu, Noam Tanner, Antoine Malfroy-Camine, and Sean Baker.
“Swing pricing” is the process of adjusting a fund’s net asset value per share to pass the costs that arise from the buying or selling of fund shares on to those investors responsible for the activity. The amount that the fund’s net asset value per share is adjusted is called the “swing factor.”
A properly calibrated swing pricing mechanism could discourage investors from redeeming, or selling, their shares in a fund during stressful periods since it forces them to pay at least some of the liquidity costs resulting from the sales, the researchers said.
“Let’s say a fund’s current net asset value is $1 and the swing factor is 2 cents, or 2%. If I decide to sell my shares, I’d get 98 cents per share, instead of the full $1,” Anadu said. “And that remaining 2 cents per share would go back to the fund to help build up liquidity.”
Hypothesis about exchange-traded funds leads to swing factor calculation
But how can a fund’s swing factor be calibrated so that it aligns with market signals and has the intended effect?
It can be difficult to measure liquidity costs for mutual funds that primarily hold certain debt instruments as investments which are not traded frequently, like commercial paper, Anadu said.
The authors hypothesized that pricing dynamics for exchange-traded funds that hold similar portfolios to mutual funds could be useful for calibrating swing factors.
A mutual fund’s net asset value per share equals the value of its assets minus its liabilities, divided by the number of outstanding shares at the end of trading on a typical business day, or “market close.” Like a mutual fund, an exchange-traded fund has a net asset value per share that is determined at market close. But because exchange-traded fund shares can be bought and sold throughout the trading day like stocks, exchange-traded funds also have a market price.
The difference between an exchange-traded fund’s share price and its net asset value per share is typically small, Anadu said. But during periods of stress, this difference, or “spread,” can widen.
The authors propose that when an exchange traded fund’s share price falls below its net asset value per share, this “discount” could serve as a proxy for the swing factor of a mutual fund with a similar portfolio.
Authors share findings, note caveats
The authors estimated that average swing-factor proxies could range from 2%-7%, based on a preliminary analysis using March 2020 data from Morningstar, Inc., Bloomberg, and SEC filings on mutual funds that mostly hold short-term corporate bonds. A separate analysis of mutual funds that invest primarily in U.S. government securities yielded much smaller proxies of 0.01%- 0.11%.
The authors note a few caveats, including that exchange-traded funds’ premiums and discounts could reflect numerous factors, such as taxes. This could reduce the degree to which they reflect costs and fees directly associated with investors’ trading.
Still, Anadu said the findings suggest their method of calculating swing factors could be a useful tool.
“The core purpose of this work is to introduce other researchers to this concept of calibrating mutual fund swing factors using the pricing dynamics of exchange-traded funds,” Anadu said. “We’re saying, ‘Here’s something you can use.’”