Trading in financial markets using pattern recognition optimized by genetic algorithms
Paulo Parracho, Rui Ferreira Neves, Nuno Cavaco Gomes Horta · 2010
In this paper a trading algorithm which identifies up trends on selected stock indexes is proposed. This is accomplished by applying Intelligent Computation techniques to trading rules that are based on the recognition of an upward pattern. Results are promising and it is shown that this application easily beats a passive approach, like the Buy&Hold. This methodology achieves +40% return for the S&P500 against a negative return of -4.69% for the Buy&Hold strategy, in the 2005 to 2010 period.