Intelligent Stock Trading System Based on QTS Algorithm in Japan´s Stock Market

In this paper, we propose a novel method named Quantum-inspired Tabu Search (QTS) algorithm for applying to a trading system. Determining the best time to buy and sell in a stock market and thereby maximizing the profit with lower risks are important issues in financial research. In order to find ideal trading points, the proposed trading system use technical indicators as the composition of trading rules. Also, it makes use of sliding window to avoid the major problem of over-fitting. The experiment results of earning profit in Japan stock market outperform Buy & Hold method which is a common benchmark in this field. Especially, the proposed method also shows better performance than other approach.