Building trade system by genetic algorithm

Abstract

This paper employs a genetic algorithm to evolve an optimized stock market prediction system. The prediction based on a range of technical indicators generates signals to indicate the price movement. The performance of the system is analyzed and compared to market movements as represented by its index. Also investment funds run by professional traders are selected to establish a relative measure of success. The results show that the evolved system outperforms the index and funds in different market environments. © Springer-Verlag 2009.