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The trading of blocks in the European equity market has never been more prevalent, with the large in scale market (LIS) now accounting for 37% of the on exchange dark activity and on average 1.59bn(1) Euros being traded above LIS every day. 

The combination of regulatory pressure to trade in larger size while in the dark, the adoption of the conditional order type and the continuing execution quality challenges of trading in the lit (e.g. small execution size and information leakage) have resulted in blocks becoming an increasing part of a trader’s workflow. 

How LIS trading sits within a clients Best Execution policy is however of increasing concern so here we discuss the issues involved and a possible solution. 

Why everyone’s on the hunt.

With the hunt for liquidity a continual battle, the allure of executing multiple days average daily volume (ADV) in a single trade has obvious appeal. Couple this with the ability to rest orders conditionally, particularly now as part of an algorithmic order, and the result is a growing block market. 

With Best Execution now a major part of any market participant’s operational consideration however, block trades need to perform in terms of execution quality. Studies of post-trade price movement continually show that block venues, such as Liquidnet, exhibit the lowest occurrence of price movement immediately after the execution, and the lowest absolute price movement in bps. For example, executions occurring on the Liquidnet MTF experienced a price movement of less than 0.28bps(2) in the 1 second after execution, the lowest of any venue.  

So, while execution quality can be fairly easily proved from a venue or child execution point of view, how do you prove Best Execution for the overall trade? 

The Value of a Block

There are two common problems with the way blocks are currently measured in TCA, 1) Opportunity cost is not properly attributed due to the conditional nature of resting in block venues and 2) the arrival time used to calculate performance can lead to confusing results, again due to the conditional nature of the interaction. 

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Therefore, the industry needs to find a new way to measure the value of a block trade. At Liquidnet we have developed a model called “Value of the Block” which uses the sum of three clear metrics; spread, market impact and incremental Alpha as metrics for evaluation. This model is open, transparent and uses metrics freely available to all market participants. 

Firstly, spread: The vast majority of executions on the Liquidnet platform, including human-negotiated trades, occur at the midpoint, therefore saving the participants 50% of the spread. This is the first significant saving of trading a block. 

Secondly, market impact: Executing an order via a single large block, in a dark venue with natural liquidity exhibits very little market impact (as highlighted by the price movement statistics quoted earlier), therefore it is fair to say that block trades save the participants the equivalent of the pre-trade market impact estimate. At Liquidnet we use our own internal market impact model based on the Almgren model, which is commonly used across the industry, even though any pre-trade model may also be used. 

Finally, incremental Alpha: Executing in a single block trade means the quantity does not have to be executed in the market over x number of minutes, thereby reducing any timing risk that may exist. This risk can be measured using a PWP at a certain percentage. Our default calculation is 10%, highlighting the out or under performance vs. this realised price. 

Combining the three measures gives a single basis point and dollar number that can be used to quickly and easily ascertain if trading the block was the right thing to do. As an example, the largest LIS execution in October (103m USD of EXPN.L) saved 2.5bps of spread, 32.2bps of market impact and 92.8bps of timing risk, with an expected duration of over 19 days.

How do blocks improve algo performance?

Blocks will not be appropriate for every algo order, however, when trying to achieve the arrival price, either via dark aggregation or a liquidity-seeking strategy, then trying to find block trades can be beneficial. 

We analysed all Liquidnet dark and Barracuda orders between 1st July 2019 and 31st October 2019 to see what difference block executions had on performance vs. arrival and the results were striking. 

Orders that executed >75% of the total order notional as LIS executions outperformed the arrival price (mid) by 1.65bps. Orders that executed <75% missed the arrival price by -2.12bps(3)

Due to the full access Liquidnet Dark and Barracuda have to the block market, i.e. connected to all four of the main conditional venues (Liquidnet, CBOE LIS, Virtu Posit and Turquoise Plato Block Discovery Service), these algorithms are fully exposed to the opportunity of block executions. 

The performance of these algorithms was recently recognised in a poll produced by K&KGC(4) which highlighted Liquidnet Dark as the most popular dark aggregation algorithm by buy-side traders across Europe. Barracuda was also in the top-3 liquidity seeking algorithms. 

Happy hunting

With a robust model to measure the quality of execution and whether LIS block trades achieved Best execution now available, the hunt for LIS blocks is sure to continue. It is therefore important to ensure you’re fully exposed to the block opportunities that exist via your execution tools, in order to find liquidity and achieve Best Execution. 



1 Liquidnet Analysis – Bloomberg dark MTF, on-exchange executions, 1st – 31st October 2019
2 Source: Big XYT Liquidity Cockpit – January 1st to October 31st 2019
3 Source: Liquidnet Dark and Barracuda algo orders between 1st July 2019 and 31st October 2019
4 Source: K&KGC, The Buy-side Perspectives 2019 The top 3 equities algorithmic trading brand preference ranking – December 2019



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