HFT Strategies and Execution Costs Goldstein, Kwan and Philip David Walsh Acadian Australia May 2016

Quick Recap of the Idea We know that HFT respond to short term order imbalance more that non-HFT. We also know that HFT market makers will attempt to trade strategically to minimize price risk. So: More likely to submit limit orders on the side away from the price move More likely to cancel limit orders on the side in front of the price move In other words, HFT market makers may respond to order book imbalance by exacerbating the “problem”; reducing liquidity on the thin side and increasing it on the thick side.

Quick Summary This paper assesses the likely direction of price move using the imbalance between the best 5 limit orders on either side of the book for ASX 100 names, at the time of the HFT message (submission or cancellation). The predatory model of Brunnermeier and Pederson (2005) [predators will trade ahead of or front run a larger trader] is invoked as the basis for this. Data: ASX100 names between Jan and July (so 94 stocks in total) All HFT messages (from prop HFT broker IDs) Aggregate order book (± best 5) at each HFT message time stamp HFT submits and cancels orders as expected and cost is borne by non-HFT

Four comments I like the way the paper addresses the HFT liquidity supply question. Contributes to the literature by showing that the cost of limit order strategies to non- HFT may increase in the presence of HFT Suggests metrics more suited to estimating HFT cost than the standard measures – such as reaction to order book depth imbalance, and execution and opportunity cost of limit order strategies. Level of depth imbalance is greater for market order submission than limit order submission, and that the effect for both is inversely related to market cap.

Three other comments I No discussion from me of: applicability of these new metrics to HFT trading in place of more standard measures whether this is just rational market making rather than true predatory behavior the use of the change to ITCH as a natural test Three points to make: 1. Classification of HFTs Broker ID classifications v ASIC categories Most HFT is not through prop HFT brokers How much of these conclusions can be applied to HFT in general?

Three other comments II 2.HFT activity measurement HFTs use much more than just best 5 bid/ask imbalance Examples include: change or trajectory of order book, shape of the whole order book (ex stale orders), conditioning on stock volatility, relative tick size, market cap, ownership structure, order arrival probability, ……. No overnight positions 3.HFT trading strategies The paper here implicitly assumes that limit order submission/cancellation reflects HFT trading strategies May be close to true for market makers but what of limit order amendment? What of mixed limit/market order strategies? What of order submission timing?