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[ T H O U G H T L E A D E R S H I P | S P O N S O R E D B Y L I Q U I D M E T R I X ] Size matters: A better than average fill metric Chris Sparrow, head of research at LiquidMetrix, examines how firms can adopt better metrics to measure broker performance. W ith the current focus in equity markets on transpar- ency, brokers are being measured by many different metrics to assess their performance, including spread capture and their ability to interact effectively with both lit and dark order books. One of the metrics being used to assess how brokers interact with the market is the average trade size achieved by the broker. This metric is used to proxy liquidity capture and is simple to calculate. The problem is that is also a simplistic measure that doesn’t really tell us what we want to know. When it comes to liquidity cap- ture, there are three dimensions to consider. What can be captured by removing liquidity from an order book, what can be captured from sitting passively in a lit order book and what can be sourced from dark pools. Let’s first consider how to measure the ability of a broker to successfully capture passive liquid- ity that is sitting in one or more lit order books. The average trade size will depend on two things: the size of the active order sent by 30 // TheTrade // Spring 2019 the broker to access the passive liquidity and the structure of the orders that are sitting passively in the order book. An example can help to illus- trate this: consider a broker that would like to immediately execute 1,000 shares. The broker sends a marketable order for 1,000 shares to an order book displaying 1,000 shares. At one extreme, the order book could consist of a single pas- sive order for 1,000 shares while at the other extreme, the order book could consist of 10 passive orders of 100 shares each. In the first case, the broker will execute one trade of 1,000 shares and have an average trade size of 1,000 shares. In the second case, the broker will execute 10 trades for 100 shares each resulting in an average trade size of 100 shares. In both cases the broker captured 1,000 shares of liquidity but the resulting average size depends on the struc- ture of the order book at the time the broker sends their order. The broker has no control over the or- der book, yet if we use average fill size as our proxy for performance, we would come to very different Chris Sparrow, head of research, LiquidMetrix conclusions about how skilled the broker is at liquidity capture. If we had a better metric, we should see no difference between these