By Walter Joyce, Head of Investment Services, TIAA Investment Management Group
This article explores best practices in ETF trading currently, in terms of maximizing liquidity and minimizing implicit trading costs. After presenting on and discussing this topic with other traders at Equities Leaders Summit in January, it is clear that there are common strategies that have emerged to achieve better execution and possibly improve overall investment performance, and we will cover some of the practices we have successfully implemented.
Avoid the open
Timing is one important aspect to consider when trading ETFs. Understanding the dynamics of bid-ask spreads and market liquidity can inform sub-optimal (more expensive) times to trade. Specifically, wide bid-ask spreads around the open are common and trading during these times should be avoided if possible. One reason for this is not all constituent stocks in an ETF start trading when the market opens, leading to meaningful price dislocations, adding to the challenge for market makers to determine the fair value of the shares.
Even well after the open, you still want to make sure the ETF you are trading does not have an unusually high spread compared to its average, and that of similar ETFs. Relatively wide bid-ask spreads are like “surge pricing” in other industries and should be monitored actively to help inform optimal trading times.
Use request for quote (RFQ) systems to automate risk trading
In addition to being mindful of timing, there are also tools and strategies available for trading block order quantities that far exceed the displayed liquidity. The most prevalent of these is the request for quote (RFQ) application which automates the risk price discovery process by encouraging competition among market makers. Similar to an algorithmic (algo) trading wheel for equity orders, RFQ applications allow you to submit one or a list of orders simultaneously to market makers and receive two-sided markets almost instantaneously. The manual price discovery process that used to take several minutes can now be done electronically within seconds, making the block trading process more efficient.
Another benefit of the RFQ system is that you see the next best market, also referred to as the cover. When the cover is zero (a tie between one or multiple brokers) that indicates fair value has been found. If the cover is greater than zero, then you can multiply that by the number of shares to estimate the transaction costs you saved on the trade. For example, if you submit an RFQ to buy 500,000 shares of an ETF and the best market from Broker A is $58.64 – $58.68 with a cover of .05 from Broker B, then you effectively saved $25,000 by not trading directly with broker B.
When using the RFQ process some traders are concerned about revealing their entire order to too many brokers at once. To address this, you can limit the brokers selected to just those that have been historically competitive in that specific ETF. Another option is to send a smaller “child,” order to determine which brokers are the most competitive, which helps to find liquidity while minimizing information slippage. Additionally, it is important to request two-way markets (market makers submit both bids and asks) so they remain uncertain about the direction of your trade and to limit information leakage.
Trade the close to save the spread
Another effective approach to minimize the implicit trading costs is to trade the closing auction where orders from all participants are aggregated and matched at a final clearing price. According to a report by Greenwich Associatesi from 2017, trading volumes represented approximately 10-15% of total daily volume, up from less than 5% a decade ago. Similarly, an excerpt from an article by Blackrockii refers to the closing auction as “a forum for deep liquidity and accurate price discovery.” This suggests that more traders are recognizing the benefits (price efficiency and liquidity) that the close offers relative to the rest of the trading day. Unless intraday liquidity is a priority, you can avoid paying the implicit execution costs (the spread) by sending orders as Market on Close (MOC) prior to the 3:50 p.m. ET cut off.
Consider NAV versus risk trading
Another way to avoid paying the spread and minimize exposure to the closing auction is to request NAV (net asset value) markets from your market makers. Typically, these will be priced in basis points above or below the official net asset value, which is a sum of the constituent shares. Even if the ETF you are trading has a penny spread, that cost can be avoided. For example, executing a block of 1,000,000 shares as a guaranteed NAV trade could save up to $10,000 in implicit trading costs. NAV trades also avoid the risk of the closing auction that could potentially have the ETF deviate from its NAV due to supply and demand imbalances in the auction.
One downside of NAV trading is the actual price is not calculated until later in the evening so if you don’t have the operational flexibility to wait a day (or several days if the underlying is in Asia) to back date trades you can request an estimated NAV market which should price shortly after market close.
Switch trades for tactical shifts
In addition to requesting NAV markets to avoid paying the spread and exposure to the closing auction, there are other strategies that traders can employ such as to trade highly correlated ETFs as a pair or ‘switch trade.’
By sending buy and sell orders for two ETFs with similar constituents, traders can save on costs by receiving risk quotes on both sides of the trade, rather than separately. If you have orders to buy and sell two ETFs with similar constituents, you can send them both to your broker or through the RFQ process, as they should only quote you on the actual risk (uncorrelated) components of the trade, or the tails. This is less expensive than receiving risk quotes on both trades at separate times.
Align ETF and Mutual Fund trades to minimize timing risk and price impact
For tax loss harvesting purposes, portfolio managers may sell a Mutual Fund at a loss and use the cash to buy a correlated ETF. If you purchase the ETF intraday, then you will be overexposed in that asset class for the balance of the trading day which poses a risk to both performance and tracking error. You can minimize this timing risk by using the closing auction or NAV trading strategy for the ETF to align with how mutual funds are priced.
Use limit orders to avoid sweeping the book
Another strategy traders have available is using price limits to help manage the impact of the order size on the price of the ETF. For example, if you are trying to buy substantially more than the displayed quantity of shares on the offer, you should add a limit to help you avoid “sweeping the book” to purchase the balance of your order at prices potentially well above where you purchased the first quantity of shares.
The risk associated with using limit orders is the possibility of not getting filled. A limit order will not execute if the market moves and stays beyond your limit so you will have to actively manage your limits to complete the order, which can be time-consuming. It is important to be aware of the risks and use limits in conjunction with other trading strategies to achieve the desired outcomes.
Partner with your Portfolio Managers for more autonomy
Perhaps the most effective way to minimize trading costs is to start with manageable order sizes and have the autonomy to determine the strategy. One way to assure this is to proactively provide your portfolio managers with transaction cost analysis (TCA) reports for their current and proposed holdings (watchlist). These reports help manage return expectations by indicating how much it will cost to implement their investment decisions, which in our case has led to more manageable order sizes.
Trade when underlying markets are open for maximum liquidity
Two additional strategies that can help control costs and improve performance are to trade ETFs when their underlying markets are open and use ETF-specific algo strategies. European markets close at 12:30 PM ET and there are typically five holidays per year and eighteen in certain Asian markets.
Naturally, bid-ask spreads will be tighter and the volume higher when the underlying shares of those markets are open, and the ETFs are still actively trading.
Use ETF-specific algos to save time
Lastly, by using algos designed to assess the price and liquidity of not only the underlying assets of your ETF but also the corresponding futures may be a more time and cost-efficient way to trade. One innovative algo strategy I recently learned of while discussing this topic at Equities Leaders Summit attempts to combine dark pool and RFQ liquidity.
In general, trading ETFs in volatile markets requires a tactical and strategic approach to minimize transaction costs and improve overall investment performance. By implementing these guidelines, we have been able to maximize liquidity and achieve better execution for our investment management portfolios.
