Developing a rule change trading system for the futures market using rough set analysis. (15th October 2016)

• Record Type: Journal Article
• Authors: Kim, Youngmin; Enke, David
• Is Part Of: Expert systems with applications. Volume 59(2016)
• Page Start: 165
• Page End: 173
• Publication Date: 2016-10-15
• Subjects: Rough set -- Genetic algorithm -- Rule change trading system -- Futures market; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2016.04.031
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: This study proposes a unique rule change trading system for the futures market. Rough set analysis is adopted for generating trading rules. A genetic algorithm is used to optimize the thresholds for buying and selling signals. To verify the proposed system, a sliding window method is applied. Abstract: Many technical indicators have been selected as input variables in order to develop an automated trading system that determines buying and selling trading decision using optimal trading rules within the futures market. However, optimal technical trading rules alone may not be sufficient for real-world application given the endlessly changing futures market. In this study, a rule change trading system ( RCTS ) that consists of numerous trading rules generated using rough set analysis is developed in order to cover diverse market conditions. To change the trading rules, a rule change mechanism based on previous trading results is proposed. Simultaneously, a genetic algorithm is employed with the objective function of maximizing the payoff ratio to determine the thresholds of market timing for both buying and selling in the futures market. An empirical study of the proposed system was conducted in the Korea Composite Stock Price Index 200 (KOSPI 200) futures market. The proposed trading system yields profitable results as compared to both the buy-and-hold strategy, and a system not utilizing a genetic algorithm for maximizing the payoff ratio.