Table of Contents

Part 1: Problem Scope

Chapter 1: Fundamentals of Automated Trading

Chapter 2: Networking Part I: Fetching Data

Part 2: Building the Platform

Chapter 3: Data Preparation

Chapter 4: Indicators

Chapter 5: Rule Sets

Chapter 6: High-Performance Computing

Chapter 7: Simulation and Backtesting

Chapter 8: Optimization

Chapter 9: Networking Part II

Chapter 10: Organizing and Automating Scripts

Part 3: Production Trading

Chapter 11: Looking Forward

Chapter 12: Appendix A: Source Code

Chapter 13: Appendix B: Scoping in Multicore R

About the Author

Chris Conlan began his career as an independent data scientist specializing in trading algorithms. He attended the University of Virginia where he completed his undergraduate statistics coursework in three semesters. During his time at UVA, he secured initial fundraising for a privately held high-frequency forex group as president and chief trading strategist. He is currently managing the development of private technology companies in high-frequency forex, machine vision, and dynamic reporting.