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Designing Stock Market Trading Systems: With and without soft computing

Book Description

In Designing Stock Market Trading Systems Bruce Vanstone and Tobias Hahn guide you through their tried and tested methodology for building rule-based stock market trading systems using both fundamental and technical data. This book shows the steps required to design and test a trading system until a trading edge is found, how to use artificial neural networks and soft computing to discover an edge and exploit it fully. Learn how to build trading systems with greater insight and dependability than ever before Most trading systems today fail to incorporate data from existing research into their operation. This is where Vanstone and Hahn's methodology is unique. Designed to integrate the best of past research on the workings of financial markets into the building of new trading systems, this synthesis helps produce stock market trading systems with unrivalled depth and accuracy. This book therefore includes a detailed review of key academic research, showing how to test existing research, how to take advantage of it by developing it into a rule-based trading system, and how to improve it with artificial intelligence techniques. The ideas and methods described in this book have been tried and tested in the heat of the market. They have been used by hedge funds to build their trading systems. Now you can use them too.

Table of Contents

  1. Cover
  2. Publishing details
  3. Preface
  4. Acknowledgements
  5. Introduction
  6. Chapter 1 –Designing Stock Market Trading Systems
    1. 1.1 Introduction
    2. 1.2 Motivation
    3. 1.3 Scope and data
    4. 1.4 The efficient market hypothesis
    5. 1.5 The illusion of knowledge
    6. 1.6 Investing versus trading
    7. 1.7 Building a mechanical stock market trading system
    8. 1.8 The place of soft computing
    9. 1.9 How to use this book
  7. Chapter 2 – Introduction to Trading
    1. 2.1 Introduction
    2. 2.2 Different approaches to trading
    3. 2.3 Conclusion
    4. 2.4 The next step
  8. Chapter 3 – Fundamental Variables
    1. 3.1 Introduction
    2. 3.2 Informational advantage and market efficiency
    3. 3.3 A note on adjustments
    4. 3.4 Core strategies
    5. 3.5 The elements of a fundamentals-based filter
    6. 3.6 Fundamental ratios and industry comparisons
    7. 3.7 A final note on cross-country investing and research
    8. 3.8 The next step
    9. 3.9 Case Study: Analysing a variable
  9. Chapter 4 – Technical Variables
    1. 4.1 Introduction
    2. 4.2 Charting and pattern analysis
    3. 4.3 Technical indicators
    4. 4.4 Alternative approaches
    5. 4.5 On use and misuse of technical analysis
    6. Case Study: Does Technical Analysis Have Any Credibility?
  10. Chapter 5 – Soft Computing
    1. 5.1 Introduction
    2. 5.2 Review of research
    3. 5.3 Conclusion
    4. 5.4 The next step
  11. Chapter 6 – Creating Artificial Neural Networks
    1. 6.1 Introduction
    2. 6.2 Expressing your problem
    3. 6.3 Partitioning data
    4. 6.4 Finding variables of influence
    5. 6.5 ANN architecture choices
    6. 6.6 ANN training
    7. 6.7 ANN in-sample testing
    8. 6.8 Conclusion
    9. 6.9 The next step
  12. Chapter 7 – Trading Systems and Distributions
    1. 7.1 Introduction
    2. 7.2 Studying a group of trades
    3. 7.3 Conclusions
    4. 7.4 The next step
  13. Chapter 8 – Position Sizing
    1. 8.1 Introduction
    2. 8.2 Pyramiding
    3. 8.3 Conclusions
    4. 8.4 The next step
  14. Chapter 9 – Risk
    1. 9.1 Introduction
    2. 9.2 Trade Risk
    3. 9.3 Risk of ruin
    4. 9.4 Portfolio Risk
    5. 9.5 Additional portfolio metrics
    6. 9.6 Monte Carlo Analysis
    7. Case study: are stops useful in trend trading systems?
  15. Chapter 10 – Case Studies
    1. 10.1 Introduction
    2. 10.2 A note about data
    3. 10.3 A note about the case studies
    4. 10.4 Building a technical trading system with neural networks
    5. 10.5 Building a fundamental trading system with neural networks
    6. Final thoughts
  16. Appendices
    1. Script segments
    2. Bibliography
  17. About this eBook