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ETF Liquidity: Hidden Depths

Published in Automated Trader Magazine Issue 30 Q3 2013

A quick glance at the screen would seem to suggest that ETFs have a mounting liquidity problem. Not so, explains Gary Stone, Chief Strategy Officer, Bloomberg Tradebook. If you know where and how to look there is ample available liquidity.

Exchange Traded Products (ETPs) have had a great run in recent years, with both their number and assets under management growing sharply. From the start of 2010 to the close of 2012, the number of ETPs (of which ETFs represent the bulk) has grown by 63%. This growth is an important element in the fundamental shift underway in the asset management business. Recent figures from Rosenblatt Securities serve to underline these changes: outflows from mutual funds have reached USD261bn since May 2010 (the flash crash), but over the same period USD314bn flowed into US equity ETFs (Figure 1, left hand scale).

Figure 1
Figure 1

Real liquidity

However, despite the rapid growth in assets under management held in ETFs, average daily exchange traded volumes have stalled and now appear to be in decline (see Figure 2, right-hand scale). Trading venues such as Nasdaq, NYSE and BATS have responded to this decline with various measures including new order types, trading incentives and even a "new" exchange (Nasdaq OMX's re-launch of its PSX exchange as an ETF-focused venue).

On this basis, it looks as if ETFs' waning liquidity is becoming a major problem. But this overlooks a crucial distinction between ETFs and many other assets: the fact that ETF liquidity is accessible in two distinct flavours. The "exchange" variety and the "underlying". This distinction arises because ETFs actually interact with two markets: the secondary on-exchange market and the primary (creation/redemption) market.

Figure 2
Figure 2

As a result, what is on the screen is not the complete liquidity picture. A trader wishing to buy an ETF can approach an authorised participant and request a block price. If the authorised participant is part of a programme desk it will typically buy the constituents of the ETF basket and derive a price from that transaction for the buyer. On the settlement date, the authorised participant will deliver the constituents to the manager of the ETF, who will then issue (or create) the requisite additional ETF shares and issue the participant with an ETF certificate for delivery to the end customer. In the case of redemptions, the same process essentially operates in reverse. (See Figure 3 for illustrations of the creation and redemption workflows.) This process is possible because the liquidity of an ETF's constituents is the primary driver of its own liquidity.

Apart from straightforward availability, there are other advantages to tapping this "created on the fly" liquidity. One of the most important is market impact. Unlike individual stocks, an authorised participant may not be competing directly with the buyer for liquidity in an ETF. This is because while the market maker may be buying the underlying basket, this activity won't necessarily drive the ETF price because it will be diffused through all the basket constituents. Alternatively, the market maker may back out the other side as part of a statistical arbitrage play, in which case it may not drive the ETF price either. Contrast this with the situation for a stock, where if a market maker is selling a block of shares, it will almost certainly be buying that block back. This probably won't happen directly on a share for share basis - it may, for example, be offset in the futures market instead - but eventually in some way the equivalent of the block of stock sold to the original buyer will be bought back.

Another consideration is the difference between the settlement price of an ETF bought in the market with a market on close (MOC) order and the settlement price of an ETF created on the fly from its constituents. An MOC order on an ETF does not have to settle at the net asset value of the fund. However if an MOC order is placed for all the constituents in the ETF basket, which are submitted to the fund manager to create new ETF shares, then these shares will settle at the closing net asset value of the fund. The two instances are essentially decoupled because the settlement price of the exchange traded ETF can be at a premium or discount to the net asset value.

Figure 3
Figure 3

The third and perhaps most important advantage to tapping on the fly ETF liquidity is execution timing and its implications for market impact and workflow efficiency. A large ETF order might take several days to complete if just executed on-exchange. By accessing additional on the fly liquidity, it may be possible to complete the order far more quickly, perhaps (depending on the liquidity of the ETF's constituents) in a single day. The scale of the potential additional liquidity opportunity can be gauged from Figure 4's data on ETPs.

30-day Exchange Traded AVD Total ETPs in Sample Total Member Liquidity Is Greater Than Exchange ETP Liquidity Percent Member Liquidity is Greater than Exchange Liquidity Percent Added Liquidity that Creation/Redemption Could Represent
20MM-36MM 8 0 0% 18%
10MM-20MM 17 4 24% 29%
5MM-10MM 18 7 39% 45%
1MM-5MM 77 35 45% 49%
0.5MM-1MM 64 22 34% 31%
Figure 4 Source: Bloomberg

Best of both worlds

While being able to tap two potential sources of ETF liquidity is clearly valuable, the biggest value-add comes from knowing (given the trader's individual order circumstances) the most opportune moment to tap which liquidity source. Fluctuating liquidity in the ETF (as traded on-exchange) and its constituents are one factor that determines their relative price premium/discount. For example, if an ETF has one or more components that are illiquid, then this will be reflected as a discount in the ETF price, because somebody has to assume that illiquid component risk in order to make a price in the ETF. This and other factors - for instance arbitrage activity (which can also create additional liquidity - see Figure 5) and idiosyncrasies such as the MOC orders mentioned earlier - mean that the ETF/constituent premium/discount is continually fluctuating. This can result in significant price improvement for the trader able to spot the optimal moment to tap the respective markets.

Figure 5
Figure 5

The market intelligence that enables traders to detect and act upon these opportunities is now available from Bloomberg Tradebook, which also has relationships with authorised participants and other liquidity providers to provide the on the fly liquidity as required. The Bloomberg Terminal displays the constituents of each ETF (see Figure 6), as well as the minimum creation unit and the number of shares of each constituent that need to be delivered to the ETF issuer for an ETF share to be created (Figure 7). The number of constituent shares delivered in the event of an ETF redemption by the ETF issuer is also available.

The Strategy Analyzer (Figure 8) takes things a step further by providing immediately actionable statistical guidance on execution strategies, together with a snapshot of current ETF liquidity conditions. The Indicator tab displays the ETF's exchange average daily volume liquidity together with the "implied" liquidity that an authorised participant can provide on the fly by trading the fund constituents and creating (redeeming) shares with the fund manager. The Strategy Analyzer also provides more detailed guidance in two important areas:

• By checking the available liquidity on-exchange and, if it is appropriate to trade there, advising on the best execution algorithm to use for current conditions.

• By highlighting price inflection points at which it might be advisable to buy (sell) a block. These points are expressed as buy/sell "tolerance" levels that when plotted appear similar to Bollinger Bands, so price approaching the lower band is an opportunity to tap the primary market for new on the fly liquidity.

The Strategy Analyzer (Figure 8) takes things a step further by providing immediately actionable statistical guidance on execution strategies, together with a snapshot of current ETF liquidity conditions. The Indicator tab displays the ETF's exchange average daily volume liquidity together with the "implied" liquidity that an authorised participant can provide on the fly by trading the fund constituents and creating (redeeming) shares with the fund manager. The Strategy Analyzer also provides more detailed guidance in two important areas:

• By checking the available liquidity on-exchange and, if it is appropriate to trade there, advising on the best execution algorithm to use for current conditions.

• By highlighting price inflection points at which it might be advisable to buy (sell) a block. These points are expressed as buy/sell "tolerance" levels that when plotted appear similar to Bollinger Bands, so price approaching the lower band is an opportunity to tap the primary market for new on the fly liquidity.

Figure 6 ETFs Underlying basket (MHD <Go>)
Figure 6
ETFs Underlying basket (MHD)
Figure 7 ETFs Creation unit
Figure 7
ETFs Creation unit
Figure 8 ETFs Strategy analyzer (STAZ <Go>)
Figure 8
ETFs Strategy analyzer (STAZ)

While this data is obviously valuable, the key is how effectively traders can act upon it. Practical experience shows that in the case of less liquid ETFs a combination of algos (such as TWAP, VWAP or Go-Along) and Tradebook's Execution Consultants works well. The algos should minimise adverse impact (especially if on-exchange liquidity is thin), while the Execution Consultants can obtain anonymous quotes on blocks from Tradebook's network of liquidity providers, market-makers and authorised participants. Authorised participants initiate the EFT creation/redemption with Tradebook, which can then be delivered to the trading entity.

Obviously individual circumstances vary considerably, but two execution strategies that makes the best of both primary and secondary ETF liquidity are:

1. Anonymously purchasing an initial block of ETFs from an ETF liquidity provider and putting the remainder of the order into a participation (Go-Along) algorithm

2. Starting in a participation (Go-Along) or Scheduled (VWAP) algorithm and, using the Strategy Analyzer's momentum models, picking points at which to buy (sell) blocks of ETFs anonymously from (to) an ETF liquidity provider.

Critical point: use an ETF algo

While the above strategies are highly effective methods for improving execution performance, there is one hugely important caveat: any algos used must be ETF-specific. Even if benefitting from access to primary market ETF liquidity, the use of generic stock execution algos for the on-exchange component will result in sub optimal execution. Extensive research by Tradebook's quantitative research group has revealed that there are major structural differences in the ways that stocks and ETFs of similar average daily volume (ADV) trade. For example, an ETF with ADV below 200,000 typically has a best bid or offer (BBO) spread of 20bps - less than half the spread size of a stock of comparable liquidity. The percentage difference is similar for stocks/ETFs of medium and high liquidity. There are similarly important differences as regards relative average BBO sizes, with ETFs typically displaying appreciably larger size than stocks, especially when compared with highly liquid stocks. Another key distinction is that the relative market impact of ETF orders is also lower than for stock orders of a comparable percentage of ADV, with the discrepancy being particularly pronounced for larger orders representing 20-25% of ADV.

As a result, applying unmodified stock execution techniques to ETFs will at a macro level often erroneously extend the trading horizon by over-emphasising stealth versus speed. At this level, ETFs can be traded more rapidly than stocks of similar liquidity, so a 60 minute execution strategy for a stock might only be a 20 minute execution strategy for an ETF.

Conversely, at the micro level, the picture is complete different, because the way in which ETF order books function actually makes the slower firing of orders

beneficial. The key is for the algo to pause before moving to the next price level in the order book, to allow liquidity at the existing price level to replenish, thus presenting an opportunity to trade again at a better price. By contrast, an algo that steps immediately to the next price level after clearing out the current level (or one that fires orders at multiple price levels simultaneously) will almost inevitably be overpaying/underselling.

Tradebook's ETF-specific algos reflect all these characteristics, plus throw in short term ETF-specific price prediction models for good measure. These models provide a reliable indication of the immediate direction of the ETF that helps to determine whether a more/less aggressive trading stance is appropriate (i.e. if it is worth crossing the spread). Coupling these models with ETF-specific execution techniques allowed Tradebook to deliver more effective U.S. ETF executions.

Conclusion

Probably one the greatest challenges with the current market structure is that the most important insights are often buried beneath the data. In the case of ETFs, addressing that involves two steps:

• Deciding when/where/how to tap primary market liquidity from authorised participants or when/where/how to trade on-exchange.

• Being able to act upon the resulting decisions as quickly and efficiently as possible.

With Strategy Analyzer, ETF-specific algos and using execution consultants to tap their network of liquidity providers, Tradebook delivers on both.

This communication is directed only to market professionals who are eligible to be customers of the relevant Bloomberg Tradebook entity, communicated, as applicable, by Bloomberg Tradebook LLC; Bloomberg Tradebook Europe Limited, authorized and regulated by the U.K. Financial Conduct Authority; Bloomberg Tradebook (Bermuda) Ltd.; Bloomberg Tradebook Services LLC. Please visit http://www.bloombergtradebook.com/pdfs/disclaimer.pdf for more information and a list of Tradebook affiliates involved with Bloomberg Tradebook products in applicable jurisdictions. Nothing in this document constitutes an offer or a solicitation of an offer to buy or sell a security or financial instrument or investment advice or recommendation of a security or financial instrument. Bloomberg Tradebook believes the information herein was obtained from reliable sources but does not guarantee its accuracy.

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