Some Secrets Of HFT Revealed

The Brogaard study has been waved around in the HFT world for months now as it proclaims that HFT “activities are not detrimental to non-HFTs and that HFT tends to improve market quality.” Prof. Brogaard is hailed as some sort of champion in the HFT world and his paper “High Frequency Trading and Its Impact on Market Quality” is quoted from in almost every pro-HFT hit piece. A few months back, we took some time to point out a few facts about this study that most pro-HFT types seem to have missed

Anyway, we happened to find a new piece that Prof. Brogaard has published as part of the UK Foresight project titled “High Frequency Trading, Information and Profits.” Read Paper Here After reviewing this paper, something tells us that the pro-HFT crowd won’t be waving this Brogaard paper around much.

In this paper, Prof. Brogaard reveals a few HFT secrets about how they derive their profits. “Information drives HFT activity” says Prof Brogaard. Well, no surprise there. But what type of information? Let’s see what Prof. Brogaard says:

“The information subcategories include order book dynamics, trade dynamics, past stock returns, cross stock correlations, cross asset correlations, and cross exchange information delays. Other types of information that may be illegitimately obtained or created could result from front running, quote stuffing, or layering.”

Now that is quite a statement. Let’s look at a few subcategories:

Order book dynamics – think of this as the jet fuel that runs the HFT supercomputers. Private data feeds that are supplied by the exchanges contain all sorts of nuggets that the HFT’s can use to sniff out the “real” order flow. Prof. Brogaard has this to say:

“Beyond the number of orders on each side of the book, the proximity of those orders to the best bid and offer can be informative. In addition, the size of the orders as well as the sequence of orders, the cancellation of orders, time the order is active, time before the order is crossed and whether orders are displayed or hidden may be used to detect the buy and sell interests of traders.”

Trade Dynamics – here the HFT is not just looking at the consolidated tape and checking for time and sales. The HFT is using information in the data feeds to help him deconstruct what type of trade occurred. Prof Brogaard says:

“In addition, the size of past trades, the time between trades, which exchange those trades occurred on, the trades’ time of day, and the number of trades in a given period can provide predictive information regarding asset prices.”

Cross exchange information delays – we refer to this as Latency Arbitrage and wrote an entire white paper dedicated to it Read Paper Here To sum it up briefly, the fragmentation of the equity markets has created near risk free profits for those fast enough to take advantage of the differences in speed. Prof. Brogaard pretty much validates our paper with this statement:

“The different trading venues can lead to differences in data reporting between the exchange data and the consolidated tape data. This difference can give those with the exchange data feeds notice of trades prior to market participants who only monitor the consolidated tape. Such a speed of information differential may provide HFTrs information that is useful in determining forthcoming buying or selling.”


Prof Brogaard seems to be concerned that the regulators and the institutional and retail investors that HFT has been stealing from over the past few years are starting to figure out the game. He seems to be worried that the HFT profit machine which funds countless lobbyists and academic studies may soon be coming to an end:

“The avenues by which HFTrs obtain information that drives their trading strategies are limited. Some types of information over the next ten years may be more difficult to detect. For example, order book dynamics as well as trade and price dynamics may become less informative of future trading opportunities. This follows from the likelihood that smaller institutional investors will either learn that they are indirectly providing valuable future price information through their patterned trades and quotes or that the cost of algorithmic randomization services will decrease so they become worthwhile for smaller firms to use.”

The only question that we have is – what the heck are they going to do with all those server farms now?