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Professional Automated Trading: Theory and Practice [NOOK Book]

Overview

Trading is a science based on a variety of fields, from mathematics to physics. It is also an art based on knowing and respecting the markets and, equally important, knowing oneself. But most of all, trading is a business that hinges on a carefully understood discipline and process of seeking reward in the face of risk.

No one is more familiar with this than author Eugene Durenard. A recognized expert in automated trading – who has long ...

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Professional Automated Trading: Theory and Practice

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Overview

Trading is a science based on a variety of fields, from mathematics to physics. It is also an art based on knowing and respecting the markets and, equally important, knowing oneself. But most of all, trading is a business that hinges on a carefully understood discipline and process of seeking reward in the face of risk.

No one is more familiar with this than author Eugene Durenard. A recognized expert in automated trading – who has long incorporated aspects of artificial life and robotics systems research into his trading – he knows what it takes to create systematic trading strategies that are adaptive and opportunistic. Now, with this new book, he shares those valuable insights with you. Whether you’re part of a professional prop trading desk or an ambitious individual trader, this practical guide will put you in a better position to successfully navigate today’s competitive markets.

Divided into four comprehensive parts, Professional Automated Trading: Theory and Practice opens with an introductory chapter that sets the stage for modern systematic trading. It critically examines the merits of systematic trading from a philosophical and psychological perspective, as well as focuses on it as a business activity.
With this information in hand, Durenard moves on to skillfully cover the theory, practice, and technologies needed to excel at this endeavor.

Part I introduces the basic conceptual and programmatic framework for the design of trading strategies as trading agents – exploring data representation, indicators, basic model types, and techniques to test them

Part II introduces innovative concepts designed to tackle adaptation of trading strategies to changing market conditions. Those include Swarm Systems that help navigate the higher complexity of the markets at lower timescales.

Part III focuses on the important aspect of trading costs and slippage – discussing the analysis of the intraday bid-offer and volume seasonality in major markets and detailing several algorithmic execution strategies designed to help reduce market impact

Part IV presents the practical implementation of a real-time, low-latency automated trading infrastructure designed to support a Swarm of Trading Agents operating on a collection of Electronic Commerce Networks (ECNs)

 Engaging and accessible, Professional Automated Trading contains the information you need to make the most of automated trading in free markets.

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Product Details

  • ISBN-13: 9781118419298
  • Publisher: Wiley
  • Publication date: 10/4/2013
  • Series: Wiley Trading
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • Pages: 384
  • File size: 7 MB

Meet the Author

Eugene A. Durenard is CEO of DTC Ltd in Bermuda, a firm that specializes in applying systematic techniques to leveraged and real money trading across a wide variety of asset classes. DTC has been acting over the years as investment advisor and manager for a range of institutions including banks, hedge funds, and proprietary trading groups. DTC is currently advising Capital G, the largest private bank in Bermuda, where Eugene acts as Head of Research and Product Development. Eugene is a partner and CIO of ERA Capital Partners, a Chicago-based quantitative systematic Proprietary Trading Group.
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Table of Contents

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

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