Develop a computerized trading system that evolves with the market "Evolutionary Computation for Live Trading Systems" is a detailed discussion on the genetic programming methodologies used to create adaptive trading systems. Written by the developers of the high-performing proprietary trading algorithm Zenquant, this book explains the inputs, analysis, and testing methods required for the development of a profitable system. Adaptive trading systems evolve in response to market behavior, and produce different trading signals based on the latest analysis of the market; this book shows you the algorithmic methodologies that enable this type of continuous learning, and how to apply them in the development of your own system. While you won't learn the precise algorithms that underlie the Zenquant system, you "will" gain deeper insight into how they were developed, and a greater understanding of the technologies that make real-world implementation possible, and more importantly, viable. Genetic programming is a machine learning technique, the ultimate goal of which is to teach computers to program themselves. The algorithms come from mathematics, evolutionary computing, swarm intelligence, and bio-inspired techniques; this informative guide shows you how to apply them to finance to create your ultimate computerized trading system. Develop a trading system that adapts to changing market behavior Generate new trading rules as market knowledge accumulates Understand the input, analysis, and testing involved in genetic programming Exploit machine learning technology to outperform the market The authors' Zenquant system, designed for short-term trading, generated an overall stock market gain of 17 percent in 2011, and individual sector gains as high as 42 percent. By harnessing the power of machine learning and genetic programming, you, too, can realize similar gains using the methodologies provided in "Evolutionary Computation for Live Trading Systems."
Publisher: John Wiley & Sons Inc