Preface xv
CHAPTER 1 - Introduction to Systematic Trading 1
1.1 Definition of Systematic Trading 2
1.2 Philosophy of Trading 3
1.3 The Business of Trading 7
1.4 Psychology and Emotions 19
1.5 From Candlesticks in Kyoto to FPGAs in Chicago 22
PART ONE - Strategy Design and Testing
CHAPTER 2 - A New Socioeconomic Paradigm 33
2.1 Financial Theory vs. Market Reality 33
2.2 The Market Is a Complex Adaptive System 42
2.3 Origins of Robotics and Artificial Life 45
CHAPTER 3 - Analogies between Systematic Trading and Robotics 49
3.1 Models and Robots 49
3.2 The Trading Robot 50
3.3 Finite-State-Machine Representation of the Control System 52
CHAPTER 4 - Implementation of Strategies as Distributed Agents 57
4.1 Trading Agent 57
4.2 Events 60
4.3 Consuming Events 60
4.4 Updating Agents 61
4.5 Defining FSM Agents 63
4.6 Implementing a Strategy 66
CHAPTER 5 - Inter-Agent Communications 73
5.1 Handling Communication Events 73
5.2 Emitting Messages and Running Simulations 75
5.3 Implementation Example 76
CHAPTER 6 - Data Representation Techniques 83
6.1 Data Relevance and Filtering of Information 83
6.2 Price and Order Book Updates 84
6.3 Sampling: Clock Time vs. Event Time 89
6.4 Compression 90
6.5 Representation 97
CHAPTER 7 - Basic Trading Strategies 105
7.1 Trend-Following 105
7.2 Acceleration 114
7.3 Mean-Reversion 118
7.4 Intraday Patterns 122
7.5 News-Driven Strategies 124
CHAPTER 8 - Architecture for Market-Making 127
8.1 Traditional Market-Making: The Specialists 127
8.2 Conditional Market-Making: Open Outcry 128
8.3 Electronic Market-Making 129
8.4 Mixed Market-Making Model 131
8.5 An Architecture for a Market-Making Desk 134
CHAPTER 9 - Combining Strategies into Portfolios 139
9.1 Aggregate Agents 139
9.2 Optimal Portfolios 141
9.3 Risk-Management of a Portfolio of Models 142
CHAPTER 10 - Simulating Agent-Based Strategies 145
10.1 The Simulation Problem 146
10.2 Modeling the Order Management System 147
10.3 Running Simulations 158
10.4 Analysis of Results 162
10.5 Degrees of Over-Fitting 167
PART TWO - Evolving Strategies
CHAPTER 11 - Strategies for Adaptation 173
11.1 Avenues for Adaptations 173
11.2 The Cybernetics of Trading 175
CHAPTER 12 - Feedback and Control 179
12.1 Looking at Markets through Models 179
12.2 Fitness Feedback Control 184
12.3 Robustness of Strategies 192
12.4 Efficiency of Control 193
CHAPTER 13 - Simple Swarm Systems 199
13.1 Switching Strategies 199
13.2 Strategy Neighborhoods 206
13.3 Choice of a Simple Individual from a Population 208
13.4 Additive Swarm System 210
13.5 Maximizing Swarm System 214
13.6 Global Performance Feedback Control 216
CHAPTER 14 - Implementing Swarm Systems 219
14.1 Setting Up the Swarm Strategy Set 220
14.2 Running the Swarm 220
CHAPTER 15 - Swarm Systems with Learning 223
15.1 Reinforcement Learning 224
15.2 Swarm Efficiency 224
15.3 Behavior Exploitation by the Swarm 225
15.4 Exploring New Behaviors 227
15.5 Lamark among the Machines 227
PART THREE - Optimizing Execution
CHAPTER 16 - Analysis of Trading Costs 231
16.1 No Free Lunch 231
16.2 Slippage 232
16.3 Intraday Seasonality of Liquidity 233
16.4 Models of Market Impact 234
CHAPTER 17 - Estimating Algorithmic Execution Tools 237
17.1 Basic Algorithmic Execution Tools 237
17.2 Estimation of Algorithmic Execution Methodologies 240
PART FOUR - Practical Implementation
CHAPTER 18 - Overview of a Scalable Architecture 247
18.1 ECNs and Translation 247
18.2 Aggregation and Disaggregation 249
18.3 Order Management 250
18.4 Controls 250
18.5 Decisions 251
18.6 Middle and Back Office 251
18.7 Recovery 252
CHAPTER 19 - Principal Design Patterns 253
19.1 Language-Agnostic Domain Model 253
19.2 Solving Tasks in Adapted Languages 254
19.3 Communicating between Components 257
19.4 Distributed Computing and Modularity 260
19.5 Parallel Processing 262
19.6 Garbage Collection and Memory Control 263
CHAPTER 20 - Data Persistence 265
20.1 Business-Critical Data 265
20.2 Object Persistence and Cached Memory 267
20.3 Databases and Their Usage 269
CHAPTER 21 - Fault Tolerance and Recovery Mechanisms 273
21.1 Situations of Stress 273
21.2 A Jam of Logs Is Better Than a Logjam of Errors 277
21.3 Virtual Machine and Network Monitoring 278
CHAPTER 22 - Computational Efficiency 281
22.1 CPU Spikes 281
22.2 Recursive Computation of Model Signals and Performance 282
22.3 Numeric Efficiency 285
CHAPTER 23 - Connectivity to Electronic Commerce Networks 291
23.1 Adaptors 291
23.2 The Translation Layer 292
23.3 Dealing with Latency 294
CHAPTER 24 - The Aggregation and Disaggregation Layer 299
24.1 Quotes Filtering and Book Aggregation 300
24.2 Orders Aggregation and Fills Disaggregation 301
CHAPTER 25 - The OMS Layer 305
25.1 Order Management as a Recursive Controller 305
25.2 Control under Stress 309
25.3 Designing a Flexible OMS 310
CHAPTER 26 - The Human Control Layer 311
26.1 Dashboard and Smart Scheduler 311
26.2 Manual Orders Aggregator 313
26.3 Position and P & L Monitor 314
CHAPTER 27 - The Risk Management Layer 319
27.1 Risky Business 319
27.2 Automated Risk Management 320
27.3 Manual Risk Control and the Panic Button 320
CHAPTER 28 - The Core Engine Layer 323
28.1 Architecture 323
28.2 Simulation and Recovery 325
CHAPTER 29 - Some Practical Implementation Aspects 327
29.1 Architecture for Build and Patch Releases 327
29.2 Hardware Considerations 329
Appendix
Auxiliary LISP Functions 333
Bibliography 341
Index 351
