Advanced Trading Rules, Second Edition (Quantitative Finance)

Advanced Trading Rules is the essential guide to state of the art techniques currently used by the very best financial traders, analysts and fund managers. The editors have brought together the world's leading professional and academic experts to explain how to understand, develop and apply cutting edge trading rules and systems. It is indispensable reading if you are involved in the derivatives, fixed income, foreign exchange and equities markets.

Advanced Trading Rules demonstrates how to apply econometrics, computer modelling, technical and quantitative analysis to generate superior returns, showing how you can stay ahead of the curve by finding out why certain methods succeed or fail.

Profit from this book by understanding how to use: stochastic properties of trading strategies; technical indicators; neural networks; genetic algorithms; quantitative techniques; charts.

Financial markets professionals will discover a wealth of applicable ideas and methods to help them to improve their performance and profits. Students and academics working in this area will also benefit from the rigorous and theoretically sound analysis of this dynamic and exciting area of finance.

• The essential guide to state of the art techniques currently used by the very best financial traders, analysts and fund managers
• Provides a complete overview of cutting edge financial markets trading rules, including new material on technical analysis and evaluation
• Demonstrates how to apply econometrics, computer modeling, technical and quantitative analysis to generate superior returns

Stephen Satchell is a Fellow of Trinity College, the Reader in Financial Econometrics at the University of Cambridge and Visiting Professor at Birkbeck College, City University Business School and University of Technology, Sydney. He provides consultancy for a range of city institutions in the broad area of quantitative finance. He has published papers in many journals and has a particular interest in risk.