A Practical Guide to Algorithmic Strategies and Trading Systems
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IRENE ALDRIDGE is an investment consultant, portfolio manager, a recognized expert on the subjects of quantitative investing and high-frequency trading, and a seasoned educator. She is currently Industry Professor at New York University, Department of Finance and Risk Engineering, Polytechnic Institute, as well as Managing Partner and Quantitative Portfolio Manager at Able Alpha Trading Ltd., an investment consulting firm and a proprietary trading vehicle specializing in quantitative and high-frequency trading strategies. Aldridge is also a founder of AbleMarkets.com, an online resource making the latest high-frequency research for institutional investors and broker-dealers. Aldridge holds an MBA from INSEAD, an MS in financial engineering from Columbia University, a BE in electric engineering from the Cooper Union in New York, and is in the process of completing her PhD at New York University. She is a frequent speaker at top industry events and a contributor to academic, practitioner, and mainstream media publications, including the Journal of Trading, Futures magazine, Reuters HedgeWorld, Advanced Trading, FX Week, FINalternatives, Dealing With Technology, and Huffington Post.
Preface xi Acknowledgments xiii Chapter 1 How Modern Markets Differ from Those Past 1 Media, Modern Markets, and HFT 6 HFT as Evolution of Trading Methodology 7 What Is High-Frequency Trading? 13 What Do High-Frequency Traders Do? 15 How Many High-Frequency Traders Are There? 17 Major Players in the HFT Space 17 Organization of This Book 18 Summary 18 End-of-Chapter Questions 19 Chapter 2 Technological Innovations, Systems, and HFT 21 A Brief History of Hardware 21 Messaging 25 Software 33 Summary 35 End-of-Chapter Questions 35 Chapter 3 Market Microstructure, Orders, and Limit Order Books 37 Types of Markets 37 Limit Order Books 39 Aggressive versus Passive Execution 43 Complex Orders 44 Trading Hours 45 Modern Microstructure: Market Convergence and Divergence 46 Fragmentation in Equities 46 Fragmentation in Futures 50 Fragmentation in Options 51 Fragmentation in Forex 51 Fragmentation in Fixed Income 51 Fragmentation in Swaps 51 Summary 52 End-of-Chapter Questions 52 Chapter 4 High-Frequency Data 53 What Is High-Frequency Data? 53 How Is High-Frequency Data Recorded? 54 Properties of High-Frequency Data 56 High-Frequency Data Are Voluminous 57 High-Frequency Data Are Subject to the Bid-Ask Bounce 59 High-Frequency Data Are Not Normal or Lognormal 62 High-Frequency Data Are Irregularly Spaced in Time 62 Most High-Frequency Data Do Not Contain Buy-and-Sell Identifiers 70 Summary 73 End-of-Chapter Questions 74 Chapter 5 Trading Costs 75 Overview of Execution Costs 75 Transparent Execution Costs 76 Implicit Execution Costs 78 Background and Definitions 82 Estimation of Market Impact 85 Empirical Estimation of Permanent Market Impact 88 Summary 96 End-of-Chapter Questions 96 Chapter 6 Performance and Capacity of High-Frequency Trading Strategies 97 Principles of Performance Measurement 97 Basic Performance Measures 98 Comparative Ratios 106 Performance Attribution 110 Capacity Evaluation 112 Alpha Decay 116 Summary 116 End-of-Chapter Questions 116 Chapter 7 The Business of High-Frequency Trading 117 Key Processes of HFT 117 Financial Markets Suitable for HFT 121 Economics of HFT 122 Market Participants 129 Summary 130 End-of-Chapter Questions 130 Chapter 8 Statistical Arbitrage Strategies 131 Practical Applications of Statistical Arbitrage 133 Summary 144 End-of-Chapter Questions 144 Chapter 9 Directional Trading Around Events 147 Developing Directional Event-Based Strategies 148 What Constitutes an Event? 149 Forecasting Methodologies 150 Tradable News 153 Application of Event Arbitrage 155 Summary 163 End-of-Chapter Questions 163 Chapter 10 Automated Market MakingNave Inventory Models 165 Introduction 165 Market Making: Key Principles 167 Simulating a Market-Making Strategy 167 Nave Market-Making Strategies 168 Market Making as a Service 173 Profitable Market Making 176 Summary 178 End-of-Chapter Questions 178 Chapter 11 Automated Market Making II 179 Whats in the Data? 179 Modeling Information in Order Flow 182 Summary 193 End-of-Chapter Questions 193 Chapter 12 Additional HFT Strategies, Market Manipulation, and Market Crashes 195 Latency Arbitrage 196 Spread Scalping 197 Rebate Capture 198 Quote Matching 199 Layering 200 Ignition 201 Pinging/Sniping/Sniffing/Phishing 201 Quote Stuffing 201 Spoofing 202 Pump-and-Dump 202 Machine Learning 207 Summary 208 End-of-Chapter Questions 208 Chapter 13 Regulation 209 Key Initiatives of Regulators Worldwide 209 Summary 222 End-of-Chapter Questions 223 Chapter 14 Risk Management of HFT 225 Measuring HFT Risk 225 Summary 244 End-of-Chapter Questions 244 Chapter 15 Minimizing Market Impact 245 Why Execution Algorithms? 245 Order-Routing Algorithms 247 Issues with Basic Models 258 Advanced Models 262 Practical Implementation of Optimal Execu