Handbook of High Frequency Trading

Greg N. Gregoriou

• Publisher: Academic Press
• Year: 2015
• Print ISBN: 9780128022054
• eBook ISBN: 9780128023624
• Topic: Business
• Subtopic: Investments & Securities
• Index: Business

This comprehensive examination of high frequency trading looks beyond mathematical models, which are the subject of most HFT books, to the mechanics of the marketplace. In 25 chapters, researchers probe the intricate nature of high frequency market dynamics, market structure, back-office processes, and regulation. They look deeply into computing infrastructure, describing data sources, formats, and required processing rates as well as software architecture and current technologies. They also create contexts, explaining the historical rise of automated trading systems, corresponding technological advances in hardware and software, and the evolution of the trading landscape. Developed for students and professionals who want more than discussions on the econometrics of the modelling process, The Handbook of High Frequency Trading explains the entirety of this controversial trading strategy.- Answers all questions about high frequency trading without being limited to mathematical modelling- Illuminates market dynamics, processes, and regulations- Explains how high frequency trading evolved and predicts its future developments

Part 1

Trading Activity

Outline

Chapter 1. High-Frequency Activity on NASDAQ

Chapter 2. The Profitability of High-Frequency Trading: Is It for Real?

Chapter 3. Data Characteristics for High-Frequency Trading Systems

Chapter 4. The Relevance of Heteroskedasticity and Structural Breaks when Testing for a Random Walk with High-Frequency Financial Data: Evidence from ASEAN Stock Markets

Chapter 5. Game Theoretical Aspects of Colocation in High-Speed Financial Markets

Chapter 6. Describing and Regulating High-Frequency Trading: A European Perspective

Chapter 1

High-Frequency Activity on NASDAQ

Martin Scholtus, and Dick van Dijk Econometric Institute and Tinbergen Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands

Abstract

We document stylized facts of overall trading activity and algorithmic trading activity in the S&P 500 Exchange Traded Fund traded on NASDAQ over the period January 6, 2009 up to December 12, 2011. Overall trading activity is characterized by strong periodicity over the day, hour, minute, and second. Algorithmic activity at the top of the order book has no periodicity within the second and is mainly event-based, in particular around macroeconomic news announcements. About 60% of all orders are canceled within 1 second after entering the order book. The percentage of bid or ask improvements that disappears within 1 second is 80%. Especially in 2009 vanished bid or ask improvements leave a worse order book behind.

Keywords

Fleeting orders; High-frequency trading; Macroannouncement effects; Market activity; Periodic effects; Stylized facts

Contents

1.1 Introduction 3

1.2 Data 5

1.3 Results 7

1.3.1 Intraday Overall Message Activity 10

1.3.2 Algorithmic Activity 13

1.3.3 News Events 19

1.4 Conclusion 21

Acknowledgments 23

References 23

1.1. Introduction

Electronic trading and the large investments in IT infrastructure have completely transformed the trading process in recent years. The most practical implication of the rise in automated trading is the large increase in trading activity accompanied by an apparent decline in trading efficiency measured by, for example, the order-cancellation rate. Biais et al. (1995) report that in 1991, 48.2% of all orders for 19 stocks traded on Paris Bourse are executions. Since then the percentage of executions appears to be decreasing over time. For example, Lo et al. (2002) find that, for the 100 largest stocks in the S&P 500 over the period 1994–1995, 37.5% of limit orders submitted through ITG (an institutional brokerage firm) are fully executed, while Ellul et al. (2007) document that between April 30, 2001 and May 4, 2001 the percentage of market orders for 148 stocks traded on the NYSE is 35.2%. By June 2008, just 7.7% of all orders submitted to NASDAQ for a set of 394 stocks consists of executions (Hasbrouck and Saar, 2013).

A clear example of how automation affects trading is provided by Boehmer et al. (2005) who investigate the introduction of the NYSE OpenBook system, which makes it possible for traders to observe depth in the order book in real time at each price level. Following the introduction of OpenBook in 2002, the expected time-to-cancellation of limit orders decreased with 24.3%, while the overall order-cancellation rate increased by 17.2%.¹ Another recent technological change on the NYSE is the introduction of the hybrid market, designed to automate executions and increase trading speed. However, Hendershott and Moulton (2011) do not find conclusive evidence that the introduction of the hybrid market leads to a change in the ratio of canceled shares to total shares placed.

The large increase in order (or message) activity leads to the dilution of traditional market microstructure concepts and, at the same time, to the introduction of new concepts. Hasbrouck and Saar (2009) introduce the notion of fleeting orders, which are nonmarketable limit orders that are canceled within a short time interval after having been submitted to the exchange. Hasbrouck and Saar (2009) document that, for a sample of 100 NASDAQ listed stocks traded on INET during October 2004, 36.7% (11.5%) of the limit orders are fleeting and get canceled within 2 seconds (100 milliseconds). On the other hand, O’Hara (2010) describes how fleeting orders (but also, for example, flash orders or “match only” orders) lead to a situation where it is no longer clear what can be considered a quote and argues for a reexamination of this basic concept.

The increase in message traffic is a concern for regulators such as the SEC and for exchange venues as well. The SEC's task to investigate illegal practices such as insider trading or market manipulation is highly complicated by the huge amount of message act...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of Contributors
• Contributors Biographies
• Editor Biography
• Acknowledgments
• Introduction
• Part 1. Trading Activity
• Part 2. Evolution and the Future
• Part 3. Liquidity and Execution
• Part 4. Impact of News Releases
• Part 5. Impact of Volatility
• Index