Journal of Economics and Management

Journal of Economics and Management
Volume 18, No. 1

March, 2022
Innovative Candlestick Technical Trading Strategies Using Genetic Algorithms
Ya-Chi Huang
Department of International Business, Lunghwa University of Science and Technology, Taiwan
Rueiher Tsaur
Department of Computer Information and Network Engineering, Lunghwa University of Science and Technology, Taiwan
Kuo-An Tseng
Department of Finance, Lunghwa University of Science and Technology, Taiwan
The issue of whether the candlestick analysis method is profitable has been extensively discussed in academia in recent years, and the related studies have all been published in influential journals. Early studies regarding candlestick analysis methods focused on the six types of two-day solid candlestick patterns. Although the studies can be viewed as a milestone in the literature, the hit ratios for the proposed buy signals were only slightly higher than 50%. In this paper, we use genetic algorithms to evolve the candlestick technical trading strategies, which can effectively reduce the complexity of the information processing and enables us to consider factors that may affect the price trend more comprehensively. We incorporate the “rolling forward method” and split the data into a training period, a validation period, and a testing period to prevent the overfitting problem. To the best of our knowledge, we are the first to combine genetic algorithms with the candlestick analysis method to create innovative trading strategies.
Keywords:Candlestick Analysis Method, Genetic Algorithms, Artificial Intelligence,Technical Analysis.
JEL Classifications:G11, C63.