Professional Automated Trading

An insider?s view of how to develop and operate an automated proprietary trading network Reflecting author Eugene Durenard?s extensive experience in this field, Professional Automated Trading offers valuable insights you won?t find anywhere else. It reveals how a series of concepts and techniques coming from current research in artificial life and modern control theory can be applied to the design of effective trading systems that outperform the majority of published trading systems. It also skillfully provides you with essential information on the practical coding and implementation of a scalable systematic trading architecture. Based on years of practical experience in building successful research and infrastructure processes for purpose of trading at several frequencies, this book is designed to be a comprehensive guide for understanding the theory of design and the practice of implementation of an automated systematic trading process at an institutional scale. Discusses several classical strategies and covers the design of efficient simulation engines for back and forward testing Provides insights on effectively implementing a series of distributed processes that should form the core of a robust and fault–tolerant automated systematic trading architecture Addresses trade execution optimization by studying market–pressure models and minimization of costs via applications of execution algorithms Introduces a series of novel concepts from artificial life and modern control theory that enhance robustness of the systematic decision making—focusing on various aspects of adaptation and dynamic optimal model choice Engaging and informative, Proprietary Automated Trading covers the most important aspects of this endeavor and will put you in a better position to excel at it. INDICE: Preface xv CHAPTER 1 Introduction to Systematic Trading 1 1.1 Definition of Systematic Trading 2 1.2 Philosophy of Trading 3 1.2.1 Lessons from the Market 3 1.2.2 Mechanism vs. Organism 5 1.2.3 The Edge of Complexity 5 1.2.4 Is Systematic Trading Reductionistic? 6 1.2.5 Reaction vs. Proaction 6 1.2.6 Arbitrage? 7 1.2.7 Two Viable Paths 7 1.3 The Business of Trading 7 1.3.1 Profitability and Track Record 8 1.3.2 The Product and Its Design 10 1.3.3 The Trading Factory 12 1.3.4 Marketing and Distribution 15 1.3.5 Capital, Costs, and Critical Mass 16 1.4 Psychology and Emotions 19 1.4.1 Ups and Downs 19 1.4.2 Peer Pressure and the Blame Game 20 1.4.3 Trust: Continuity of Quality 20 1.4.4 Learning from Each Other 21 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 2.1.1 Adaptive Reactions vs. Rigid Anticipations 33 2.1.2 Accumulation vs. Divestment Games 37 2.1.3 Phase Transitions under Leverage 38 2.1.4 Derivatives: New Risks Do Not Project onto Old Hedges 40 2.1.5 Socio–Political Dynamics and Feedbacks 41 2.2 The Market Is a Complex Adaptive System 42 2.2.1 Emergence 43 2.2.2 Intelligence Is Not Always Necessary 44 2.2.3 The Need to Adapt 45 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 6.2.1 Elementary Price Events 85 6.2.2 Order Book Data 85 6.2.3 Tick Data: The Finest Grain 88 6.3 Sampling: Clock Time vs. Event Time 89 6.4 Compression 90 6.4.1 Slicing Time into Bars and Candles 90 6.4.2 Slicing Price into Boxes 96 6.4.3 Market Distributions 97 6.5 Representation 97 6.5.1 Charts and Technical Analysis 99 6.5.2 Translating Patterns into Symbols 101 6.5.3 Translating News into Numbers 102 6.5.4 Psychology of Data and Alerts 104 CHAPTER 7 Basic Trading Strategies 105 7.1 Trend–Following 105 7.1.1 Channel Breakout 106 7.1.2 Moving Averages 106 7.1.3 Swing Breakout 112 7.2 Acceleration 114 7.2.1 Trend Asymmetry 115 7.2.2 The Shadow Index 116 7.2.3 Trading Acceleration 117 7.3 Mean–Reversion 118 7.3.1 Swing Reversal 118 7.3.2 Range Projection 120 7.4 Intraday Patterns 122 7.4.1 Openings 122 7.4.2 Seasonality of Volatility 122 7.5 News–Driven Strategies 124 7.5.1 Expectations vs. Reality 124 7.5.2 Ontology–Driven Strategies 125 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 10.2.1 Orders and Algorithms 148 10.2.2 Simulating Slippage 149 10.2.3 Simulating Order Placement 151 10.2.4 Simulating Order Execution 153 10.2.5 A Model for the OMS 155 10.2.6 Operating the OMS 156 10.3 Running Simulations 158 10.3.1 Setting Up a Back Test 158 10.3.2 Setting Up a Forward Test 160 10.4 Analysis of Results 162 10.4.1 Continuous Statistics 163 10.4.2 Per–Trade Statistics 164 10.4.3 Parameter Search and Optimization 165 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 12.1.1 Internal World 179 12.1.2 Strategies as Generalized Filters 180 12.1.3 Implicit Market Regimes 181 12.1.4 Persistence of Regimes 183 12.2 Fitness Feedback Control 184 12.2.1 Measures of Fitness 186 12.3 Robustness of Strategies 192 12.4 Efficiency of Control 193 12.4.1 Triggering Control 193 12.4.2 Measuring Efficiency of Control 194 12.4.3 Test Results 196 12.4.4 Optimizing Control Parameters 197 CHAPTER 13 Simple Swarm Systems 199 13.1 Switching Strategies 199 13.1.1 Switching between Regimes 200 13.1.2 Switching within the Same Regime 200 13.1.3 Mechanics of Switching and Transaction Costs 205 13.2 Strategy Neighborhoods 206 13.3 Choice of a Simple Individual from a Population 208 13.4 Additive Swarm System 210 13.4.1 Example of an Additive Swarm 211 13.5 Maximizing Swarm System 214 13.5.1 Example of a Maximizing Swarm 215 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 16.4.1 Reaction to Aggression 235 16.4.2 Limits to Openness 235 CHAPTER 17 Estimating Algorithmic Execution Tools 237 17.1 Basic Algorithmic Execution Tools 237 17.2 Estimation of Algorithmic Execution Methodologies 240 17.2.1 A Simulation Engine for Algos 240 17.2.2 Using Execution Algo Results in Model Estimation 241 17.2.3 Joint Testing of Models and Algos 242 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 19.3.1 Messaging Bus 258 19.3.2 Remote Procedure Calls 259 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 21.1.1 Communication Breakdown 273 21.1.2 External Systems Breakdown 274 21.1.3 Trades Busted at the ECN Level 275 21.1.4 Give–Up Errors Causing Credit Line Problems 276 21.1.5 Internal Systems Breakdown 277 21.1.6 Planned Maintenance and Upgrades 277 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 23.2.1 Orders: FIX 292 23.2.2 Specific ECNs 293 23.2.3 Price Sources: FAST 293 23.3 Dealing with Latency 294 23.3.1 External Constraints and Co–Location 294 23.3.2 Avoid Being Short the Latency Option 295 23.3.3 Synchronization under Constraints 296 23.3.4 Improving Internal Latency 297 CHAPTER 24 The Aggregation and Disaggregation Layer 299 24.1 Quotes Filtering and Book Aggregation 300 24.1.1 Filtering Quotes 300 24.1.2 Synthetic Order Book 301 24.2 Orders Aggregation and Fills Disaggregation 301 24.2.1 Aggregating Positions and Orders 301 24.2.2 Fills Disaggregation 303 24.2.3 Book Transfers and Middle Office 303 CHAPTER 25 The OMS Layer 305 25.1 Order Management as a Recursive Controller 305 25.1.1 Management of Positions 307 25.1.2 Management of Resting Orders 307 25.1.3 Algorithmic Orders 308 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 26.1.1 Parameter Control 311 26.1.2 Scheduled Flattening of Exposure 312 26.2 Manual Orders Aggregator 313 26.2.1 Representing a Trader by an Agent 313 26.2.2 Writing a Trading Screen 314 26.2.3 Monitoring Aggregated Streams 314 26.3 Position and P & L Monitor 314 26.3.1 Real–Time Exposure Monitor 315 26.3.2 Displaying Equity Curves 315 26.3.3 Online Trade Statistics and Fitnesses 315 26.3.4 Trades Visualization Module 317 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 29.1.1 Testing of Code before a Release 327 29.1.2 Versioning of Code and Builds 328 29.1.3 Persistence of State during Version Releases 328 29.2 Hardware Considerations 329 29.2.1 Bottleneck Analysis 329 29.2.2 The Edge of Technology 330 Appendix Auxiliary LISP Functions 333 Bibliography 341 Index 351

• ISBN: 978-1-118-12985-2
• Editorial: John Wiley & Sons
• Encuadernacion: Cartoné
• Páginas: 384
• Fecha Publicación: 29/11/2013
• Nº Volúmenes: 1
• Idioma: Inglés