Designing Stock Market Trading Systems: WIth and Without Soft Computing

Whilst reviewing this book I was struck by the observation that it is only recently that books on systems and systems development and testing have become available to retail traders. I guess constant improvements in personal computers and their increasing power, and the availability of suitable programs, have contributed greatly to this. Once the domain of large hedge funds and institutional traders, trading systems and mechanical trading are becoming more widely accepted and used by individual traders. Traders find them to be a much more reliable way to achieve trading success than by using arbitrary decision-making processes and other esoteric approaches to arrive at buy and sell decisions. However, back to this book.

Dr Bruce Vanstone is an Assistant Professor at Bond University in Australia, where he teaches stock market trading courses. He has a PhD in computational finance, published academic work on stock market trading systems, and is a consultant for a boutique hedge fund. He is well qualified to write a book on trading system design. His co-author, Tobias Hahn, is completing a PhD at Bond University, focusing on market microstructure and the application of machine learning techniques to the pricing of derivative products.

The design, testing and implementation of mechanical trading systems is not the most exciting topic for those who have been sold the hype of salespeople and spruikers promising more than can be delivered by most approaches to trading. However, retail traders and investors are becoming aware that a mechanical or mathematical approach to the markets that focuses on a long-term edge or range of probable outcomes is a very professional approach, which can be applied at the retail level.

The authors explain how they build a rule-based system. They show the steps in designing and testing a system until an edge is found, and then how to fully exploit that edge to maximise returns. They take a detailed look into the development of a trading system as well as the many things not to incorporate into a trading system.

Parts of this book will challenge many readers’ beliefs and paradigms about the markets and how they work. One example is Chapter 4.5, ‘On use and misuse of technical analysis’, where authors discuss the concept of ‘data snooping’ that is employed by many technical analysts. In a case study on the place of stops in a trend trading system the use of stop losses is examined in great mathematical detail, particularly the use of the commonly applied Average True Range (ATR) stops. Their research conclusions are that “having tested a large number of medium-term and long-term trend based systems, we have not yet found a single case where the system results are improved by the use of a stop-loss rule.” As I said, this book challenges many of the existing ‘chestnuts’ that exist in trader-education circles.

This book is a must-read for anyone serious about their system-based trading, and for those who trade using subjective analysis, to fully understand what they are up against in the markets. It is one of the most interesting books I have had the pleasure of reviewing.