Abstract
Genetic Algorithms (GAS) have been successfully used in many scientific and engineering problems but the dynamics is not yet understood completely. This thesis aims to apply GA in multiple time series problem and to investigate the dynamics behind the algorithm. With GAS, classifier system, optimizer system and parallel system are developed in the project. We discuss issues like objective functions, specificity, genetic operations, pattern matching and other control parameters. A simple investigation of Self Organized Criticality (SOC) in the evolutionary process is also discussed. Real financial blue chips' stock prices in Hang Seng Index are used as the time series for the investigation.