Editorial
High-frequency trading

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Introduction

What are high-frequency traders (HFTs)? The Securities and Exchange Commission's (SEC's) Concept release on equity market structure (2010) defines them as “professional traders acting in a proprietary capacity that engage in strategies that generate a large number of trades on a daily basis.” The SEC document lists several characteristics commonly attributed to HFTs including “(1) the use of extraordinarily high-speed and sophisticated computer programs for generating, routing, and executing orders; (2) use of co-location services and individual data feeds offered by exchanges and others to minimize network and other types of latencies; (3) very short time-frames for establishing and liquidating positions; (4) the submission of numerous orders that are cancelled shortly after submission; and (5) ending the trading day in as close to a flat position as possible (that is, not carrying significant, unhedged positions over-night).”

The U.S. Commodity Futures Trading Commission (CFTC) Technology Advisory Committee released a draft definition of high-frequency trading in October 2012 that deliberately leaves out holding period and portfolio turnover frequency as attributes of HFTs. Instead, it classifies high-frequency trading as a form of automated trading that employs “algorithms for decision making, order initiation, generation, routing, or execution, for each individual transaction without human direction,” and that satisfies several criteria such as use of low-latency technology, high-speed connections to markets for order entry, and high message rates (orders and cancellations).

Some market observers emphasize that high-frequency trading is simply faster trading. According to this view, many trading strategies employed by HFTs are not new, and therefore nothing has changed in the economics of the market. Furthermore, the speed of trading has been gradually increasing for decades, and hence high-frequency trading may not represent a fundamental shift in the way markets operate. Other market observers view high-frequency trading as a game-changer. The combination of fragmentation like never before and a tremendous disparity in terms of speed between regular investors and those who expand vast resources on technology have joined to shape a new (and important) set of players with its own unique strengths and weaknesses.

As a relatively new phenomenon, much of the discussion on HFTs is not backed by solid academic research. In this special issue of the Journal of Financial Markets on High-Frequency Trading, we present several research papers that aim to inform the discussion on this important issue.

Section snippets

Low-latency trading

Our first paper, Hasbrouck and Saar (in this issue), emphasizes the low latency that high-frequency trading algorithms require in order to profit from the trading environment itself (rather than from investing in financial securities). Hasbrouck and Saar define low-latency activity as “strategies that respond to market events in the millisecond environment,” and proceed to investigate it. Their paper provides a glimpse into the “millisecond environment” in which algorithms of all kinds

Very fast money: high-frequency trading on the NASDAQ

Why did algorithms replace human traders? One oft-cited driver for the ascent of algorithms is lower operating costs. These cost savings could be passed to investors via lower trading costs (e.g., smaller spreads) or become profits for the HFTs. Hence, assessing the profitability of high-frequency trading is of great interest. Our second paper, Carrion (in this issue), demonstrates that the question of profitability of HFTs and how it relates to their strategies is rather sensitive to the

High-frequency trading and the new market makers

The impact of HFTs on informational efficiency depends on the particular strategies they pursue. To understand strategies, however, one may need to focus on the trading of specific HFTs. If trying to capture all HFTs in a single measure is on one end of the spectrum, focusing on just one HFT is on the other end. Our third paper, Menkveld (in this issue), is a case study that looks at just one HFT that follows a market making strategy. It showcases the symbiotic relationship between market

The diversity of high-frequency traders

Of course, market making is not the only strategy HFTs pursue. In fact, it is reasonable to assume that there is heterogeneity in the strategies implemented by HFTs, which complicates the task of figuring out how they impact the market. Our fourth paper, Hagströmer and Nordén (in this issue), uses data that identify the trading of specific HFTs to categorize their strategies and obtain insights into how they affect the market. Specifically, they use a dataset from NASDAQ-OMX Stockholm that

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