Bruce Vanstone - Designing Stock Market Trading Systems: With and Without Soft Computing

The book is divided into the following ten chapters:

1. Designing Stock Market Trading Systems

Chapter 1 introduces the ideas underpinning stock market trading, both from a practical and academic perspective. It explains why most traders fail, and explains what you must do to succeed. It also explains the reasons why you are more likely to be successful as a systematic, rules-based trader compared to a discretionary trader. Finally, it introduces the idea of soft computing, and explains the reasons why soft computing can have such a profound effect on trading performance.

2. Introduction To Trading

Chapter 2 presents a very brief introduction to trading. It provides you with information on some of the basic approaches that traders use to try and make money in the markets. Its main goal is to stimulate you to think about the kinds of approaches you would like to learn more about. One of the most common flaws for beginners is to try and trade everything they come across in the market. A far better approach is to develop systems to identify specific behaviours, and to wait on the sidelines until the required behaviour is identified.

3. Fundamental Variables

Chapter 3 introduces fundamental variables. These variables provide the means to codify fundamental observations about companies, which are later expressed in the form of a trading strategy. This chapter discusses the academic acceptance of these types of variables, and presents a historical evolution of academic research into these variables. As always, it is important to ensure the findings of published research are applicable to your own trading universe by which we mean the assets or indices you will allocate your money to. This chapter includes a case study that demonstrates techniques that you can use to gain insights into the effects of many fundamental variables.

4. Technical Variables

Chapter 4 introduces technical variables. These variables provide the means to codify behavioural observations about markets and stocks, which will later be expressed in the form of a trading strategy. This chapter discusses the academic credibility of these types of variables, and presents a historical evolution of academic and practitioner research into them. This chapter contains a case study that verifies the credibility of technical analysis.

5. Soft Computing

Chapter 5 introduces you to the various soft-computing paradigms, and shows how soft computing can complement trading systems. It also helps you to gain an understanding of the advantages and disadvantages of soft computing. There is also a detailed review of academic work focused on the use of soft computing in trading, including a brief summary of each work, and its outcomes.

6. Creating Artificial Neural Networks

Chapter 6 explores Artificial Neural Networks (ANN) in greater detail. It describes the process of designing, training and testing an ANN for use within a trading system.

7. Trading Systems And Distributions

Chapter 7 describes the first of the two primary approaches to benchmarking trading systems. It introduces you to the raw trades approach, describing both traders metrics and statistical measures used for benchmarking.

8. Position Sizing