Two weeks ago we wrote about how the liquidity of an ETF cannot simply be measured in the same way we evaluate a stock’s liquidity, even though they have similar trading characteristics. The interrelated factors driving an ETF’s liquidity are: 1) the flexible supply of shares due to the creation / redemption mechanism, 2) the liquidity of the ETF’s underlying portfolio, and 3) the arbitrage relationship between the ETF’s market price and its net asset value. For advisors and ETF investors, the question now becomes how to quantify the liquidity for a specific ETF?
A common gauge to estimate an ETF’s liquidity is what is known as implied liquidity. An ETF’s implied liquidity evaluates the ease of trading the holdings in the creation/redemption basket based upon each security’s weight and average trading volume while accounting for the ETF’s creation unit size, effectively drilling down to what we can call the ETF’s liquidity-minimizing security. This security is ultimately the limiting factor in an ETF’s liquidity and dictates how many creation units can potentially be traded before impacting the market. Performing this exercise for equity ETFs is relatively easy, as equities are traded in high volumes on public exchanges. Bloomberg or other ETF market data providers may be able to provide this metric with little effort on the part of the analyst.
Due to the over-the-counter trading nature of bonds, there is not a simple implied liquidity metric that is officially calculated by Bloomberg or other ETF market data providers. Likewise, due to the flexible supply of ETF shares in the underlying ETFs, the common implied volatility calculation also falls short for ETFs that use a fund-of-funds construction (holding other ETFs as part of the underlying basket of securities). Fortunately, we can combine the key principle of the typical implied liquidity calculation—finding the liquidity-minimizing security in the basket—with common capital markets practices to arrive at something very similar to an implied liquidity metric for such an ETF.
Stepping Through the Process
We’ll use a hypothetical ETF to walk through this process. “ETF X” is constructed using index-tracking fixed income ETFs, cash, equities, and equity options. We will use the following process to determine the implied liquidity of ETF X: 1) identify the liquidity-minimizing security in each basket of ETF X’s underlying fixed income ETFs, 2) determine a $ estimate of how much of that ETF could be traded before the market is impacted, and 3) determine an estimate of how much of ETF X could be traded before the market is impacted based on the weight of the “least liquid” ETF in its portfolio.
Step 1: Identify the liquidity-minimizing security in each underlying fixed income ETF
Identifying the liquidity-minimizing security is simply a function of 1) the number of bonds of a specific issuance in one creation unit basket, 2) the amount outstanding in that issuance, and 3) how many baskets could be created until the 1% outstanding threshold is breached for any one issue à the liquidity-minimizing security. Let’s say ETF X holds only one non-Treasury ETF, a short-term corporate bond ETF (“ETF Y”). In analyzing ETF Y’s recent basket holdings of about 200 different bonds, the below bond stood out as the liquidity-minimizing security.
|ETF||Holding||# of Bonds in 1 CU of ETF||# of Bonds Outstanding||1% Outstanding||# of CUs needed to hit 1% threshold|
|ETF Y||BOND Z 3.3 03/19/25||75||300,000||3,000||40|
It would take 40 creation units of ETF Y before a threshold of trading more than 1% of the issuance of this bond is breached; all other bonds in ETF Y’s basket would still be below the 1% outstanding threshold with 40 creation units.
2) Determine the $ estimate of how much of that ETF could be traded before the market is impacted
Now that we have our estimate of trading 40 ETF Y creation units before impacting the market, we determine the notional dollar value of that trade by using this number with ETF Y’s recent share price and creation unit size:
|ETF||Creation Unit Size (Shares)||Recent Share Price||Maximum CUs||Notional Value of Est. Maximum Trade Size|
By our estimate, ETF Y can handle a trade of over $300M in notional value before we could anticipate market impact.
3) Determine the $ estimate of how much ETF X could be traded before the market is impacted based on the weight of the “least liquid” ETF in ETF X’s portfolio
We have identified ETF Y as the liquidity-minimizing security in ETF X’s basket and determined the notional value of how much ETF Y can be traded before we expect market impact. For the last step we need to reconcile that number with ETF Y’s weight in ETF X’s basket to determine the how much could be traded before there would be market impact.
|Notional Value of Max ETF Y Trade Size||$308 million|
|Approximate ETF Y Weight in ETF X Basket||15%|
|Divide Notional Value / Weight||308 / .15 =|
|Notional Value of Max ETF X Trade Size||$2.05 billion|
We estimate ETF X can handle a trade of more than $2 billion before the market would be impacted. We should emphasize that this liquidity figure is a function of ETF X’s basket mix. For example, if ETF Y was 50% of the basket instead of 15%, this maximum trade estimate drops to approximately $616M.
So does this mean if you want to buy $2 billion of ETF X (or any ETF for that matter) you should just enter an order for millions of shares? Absolutely not. We recommend that for any trade of 1 creation unit or more of any ETF (ETFs trade in creation units of various sizes, but usually tens of thousands of shares) you contact the ETF sponsor and have them put you in touch with their capital markets partners. Most capital markets partners can not only help execute large trades but may also be able to trade within the on-screen spread. For advisors or clients doing large trades in ETFs, it always pays to reach out to the ETF sponsor first.
Putting it All Together
The liquidity of an ETF is dependent on the liquidity of the least liquid underlying asset. For funds-of-funds such as the example given above, you must drill down through the underlying funds to find the least liquid underling security. From there, you can use the maximum trade size of the underlying as well as the portfolio weights to determine the maximum trade size you can make before impacting the market. Note that for most ETFs using highly liquid bond funds, equities, and equity options, this number can be in the hundreds of millions to billions. Far beyond the trade size for most advisors and clients, and certainly a trade that would warrant a phone to the ETF sponsor first. If you would like to know more about ETF liquidity or how this impacts any of Build’s products, please reach out to us via the contact links on this page.
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