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Designing Stock Market Trading Systems: With and without soft computing
 
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Designing Stock Market Trading Systems: With and without soft computing [Hardcover]

Bruce Vanstone , Tobias Hahn
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Product Description

Product Description

Everybody knows there is potential to make big money in the stock market. But what most people don't know is how to go about it. This book will guide you step-by-step through the authors' tried and tested method for building rule-based stockmarket trading systems. It shows you how to design, test and trade a rule-based system. It differs from other books in that it takes a scientific approach to developing trading systems, based on what others have done before. This book reviews previous work, and shows that some of it is gold dust because it provides information about what works and what doesn't work in trading. Better still, most of this information can be unearthed on the internet for free! There is no need to start from scratch or re-invent the wheel. For most of us, what is missing is a way to incorporate other people's ideas and research into our own trading systems. That's where my methodology fits in. It shows you how to test existing research, how to take advantage of it by developing it into a rule-based trading system, and even 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!

About the Author

Dr. Bruce Vanstone is an Assistant Professor at Bond University in Australia. He completed his PhD in Computational Finance in 2006. He is a regular presenter and publisher of academic work on stockmarket trading systems at an international level. He teaches stockmarket trading courses at university, and is a consultant for a boutique hedge fund in Australia. More information on Bruce's research and methods can be found at http://trading.it.bond.edu.au. Tobias Hahn is currently studying towards a PhD at Bond University in Australia. His research focuses on market microstructure and, in particular, the application of machine learning techniques to the pricing of derivative products.

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