A hybrid (μ+λ) evolutionary algorithm for evolving simple trading rules: Case study on stock Exchange of Thailand (SET50)

This paper proposes a new hybrid method for generating trading rules. The proposed technique employs genetic algorithm to evolve the rules' structure and uses evolution strategy to determine constant parameters, simultaneously. The evolved trading rules are tested with historical data of SET50. The results are compared with a commonly used indicator (MACD). The testing period starts from June to October 2013, which the SET50 index dropped 3.77%. Generally, it is difficult for traders to earn profit in a downtrend market. However, the proposed method yields the 3.94% average profit return while MACD incurs -0.52%. It shows that the proposed technique can find profit generating rules although the overall market is bearish.