We use stock exchange message data to quantify the negative aspect of high-frequency trading, known as "latency arbitrage". This means arbitrage opportunities that are sufficiently mechanical and obvious that capturing them is primarily a contest in speed.
The paper makes three main contributions to the literature. The first is methodological: we utilise the entirety of exchange message data, as opposed to standard order book data, to measure latency arbitrage. The second is the set of empirical facts we document about latency arbitrage. The third contribution is that we develop two new approaches to quantifying latency arbitrage as a proportion of the overall cost of liquidity.
We show that races are very frequent and very fast, and that over 20% of trading volume takes place in races. A small number of firms win the large majority of races, disproportionately as takers of liquidity. Most races are for very small amounts of money, averaging just over half a tick. But even just half a tick, over 20% of trading volume, adds up. The latency arbitrage tax, defined as latency arbitrage profits divided by trading volume, is 0.42 basis points. This amounts to about GBP 60 million annually in the UK. Extrapolating from our UK data, our estimates imply that latency arbitrage is worth about $5 billion annually in global equity markets alone.
The new approaches we develop to quantify latency arbitrage as a proportion of the overall cost of liquidity, used in conjunction with our results, show that latency arbitrage accounts for 33% of the effective spread and 31% of all price impact, and that market designs that eliminate latency arbitrage would reduce the cost of liquidity for investors by 17%.
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