This review was commissioned as part of the UK Government’s Foresight Project, The Future of Computer Trading in Financial Markets. The views expressed do not represent the policy of any Government or organisation.

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Jonathan A. Brogaard, Northwestern University, Kellogg School of Management

In this paper I outline the different types of short term information used by high frequency traders (HFTrs) and discuss the various sources of their profits. First, the different sources of information that drive HFTrs’ activity are described. Next, this paper analyzes the possible ways in which HFTrs earn returns. Finally, the paper discusses implications of these results and potential changes in market structure that may occur over the next ten years.

Introduction

The aim of this paper is to clearly identify and describe prominent types of information utilized by high frequency traders (HFTrs) and the ways they earn their profits. High frequency trading (HFT) has risen over the past decade from non-existence to having a dominant presence in many electronic asset markets. The literature on HFT has yet to focus on the type of information that drives HFTrs’ trading and how they use it to earn profits. While HFTrs may not readily share their historical profitability records or the details of their trading strategies, much of the information they use and the source of their trading profits follow from existing academic literature.

There are three parts to this paper’s analysis. First, it outlines the different sources of information that drive HFTrs’ activities. Where HFTrs get their information is important in understanding how other market participants may benefit or be harmed by the introduction of fast algorithmic trading systems. Second, it discusses the possible sources of HFTrs’ profits. The profits of HFT need to be put in context to determine whether they are extracting rents or whether they are being compensated for socially valuable services. Finally, the paper discusses how HFTrs’ role, profitability, and activities may evolve in the future.

There are a variety of types of information that can be useful to HFTrs and that likely influence their trading activity. Among these are 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 come from front running, quote stuffing, or layering.

While there are a variety of information avenues available to HFTrs, the underlying profitability can be categorized into a limited number of groups. These include market making, collecting liquidity rebates, detecting statistical patterns, upholding the law of one price, and manipulating markets.

The final part of the paper examines the future of HFT. The ten year horizon is very uncertain for HFT. There is already a sense that the profitability of HFT is reaching its limit (The Maturation of High-Frequency Trading, 2011). By design there is some upper bound on how much market activity can be by HFTrs before they are simply trading amongst themselves. In addition, as markets continue to mature there will be pressure on the information HFTrs can utilize. Finally, changing regulation may limit HFT outright or reduce its profitability.

HFT can play an important role in financial markets by collecting legitimate information and incorporating it into asset prices. However, the value gained from the speed of this process is not well understood. In addition, the potential for market manipulation is present and needs to be monitored. The future of HFTrs’ role in processing information will depend to a large extent onhow markets and regulations evolve. As the tools to utilize high frequency information become more readily available, competition will likely increase and profits decrease. New regulation could also deter HFTrs from utilizing short term information or could increase competition and reduce profits.

The rest of this paper is as follows. Section 2 discusses the different types of information HFTrs use. Section 3 discusses the different ways HFTrs can earn profits. Section 4 speculates about what may come to fruition over the next ten years regarding HFT, information, and profitability. Section 5 concludes.