Algorithmic Trading based on GA focusing on Fitness Function and Market Trend

Abstract

A method to build trading rules at algorithmic trading by Genetic Algorithm (GA) is presented. The trading rules are built by adapting parameters of technical indices. New fitness functions in GA, which aim at a robuster behavior to change of market trends, are proposed. Furthermore, We have found that the effectiveness of technical indices varies depending on market trend. We propose a hybrid dealing method which switches the technical indices by market trend. The result of experiment shows that profits through dealing are improved by our proposed method.