Developing a rule change trading system for the futures market using rough set analysis

被引:37
|
作者
Kim, Youngmin [1 ]
Enke, David [2 ]
机构
[1] Missouri Univ Sci & Technol, Dept Engn Management & Syst Engn, 205 Engn Management,600 W 14th St, Rolla, MO 65409 USA
[2] Missouri Univ Sci & Technol, Dept Engn Management & Syst Engn, 221 Engn Management,600 W 14th St, Rolla, MO 65409 USA
关键词
Rough set; Genetic algorithm; Rule change trading system; Futures market; TECHNICAL ANALYSIS; GENETIC ALGORITHMS; STOCK; PREDICTION; NETWORKS; MODEL; INDEX;
D O I
10.1016/j.eswa.2016.04.031
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:165 / 173
页数:9
相关论文
共 50 条
  • [1] A relative value trading system based on a correlation and rough set analysis for the foreign exchange futures market
    Lee, Sukjun
    Enke, David
    Kim, Youngmin
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2017, 61 : 47 - 56
  • [2] Using rough set to support investment strategies of real-time trading in futures market
    Suk Jun Lee
    Jae Joon Ahn
    Kyong Joo Oh
    Tae Yoon Kim
    [J]. Applied Intelligence, 2010, 32 : 364 - 377
  • [3] Using rough set to support investment strategies of real-time trading in futures market
    Lee, Suk Jun
    Ahn, Jae Joon
    Oh, Kyong Joo
    Kim, Tae Yoon
    [J]. APPLIED INTELLIGENCE, 2010, 32 (03) : 364 - 377
  • [4] An intelligent hybrid trading system for discovering trading rules for the futures market using rough sets and genetic algorithms
    Kim, Youngmin
    Ahn, Wonbin
    Oh, Kyong Joo
    Enke, David
    [J]. APPLIED SOFT COMPUTING, 2017, 55 : 127 - 140
  • [5] Behavior analysis of futures trading agents using fuzzy rule extraction
    Kitano, H
    Nakashima, T
    Ishibuchi, H
    [J]. INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOL 1-4, PROCEEDINGS, 2005, : 1477 - 1481
  • [6] SEMICONDUCTOR MARKET FLUCTUATION INDICATORS AND RULE DERIVATIONS USING THE ROUGH SET THEORY
    Huang, Chi-Yo
    Tzeng, Gwo-Hshiung
    Chan, Chien-Chung
    Wu, Hong-Chun
    [J]. INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2009, 5 (06): : 1485 - 1503
  • [7] A Decision Support System for Trading in Apple Futures Market Using Predictions Fusion
    Deng, Shangkun
    Huang, Xiaoru
    Wang, Jiahui
    Qin, Zhaohui
    Fu, Zhe
    Wang, Aiming
    Yang, Tianxiang
    [J]. IEEE ACCESS, 2021, 9 : 1271 - 1285
  • [8] Short Term Intraday Trading of Futures Market Analysis
    Chen, Chiu-Chin
    Liao, Chia-Chun
    [J]. PROCEEDINGS 2018 33RD YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC), 2018, : 549 - 554
  • [9] Weekly Quantitative Analysis and Trend Trading in Futures Market
    Masteika, Saulius
    Driaunys, Kestutis
    Moskaliova, Vera
    [J]. BUSINESS INFORMATION SYSTEMS WORKSHOPS, BIS 2012, 2012, 127 : 61 - 68
  • [10] Selection of trading rule set by Genetic Fuzzy Expert Trading System
    Ng, HS
    Lam, SS
    [J]. 8TH WORLD MULTI-CONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL IX, PROCEEDINGS: COMPUTER SCIENCE AND ENGINEERING: I, 2004, : 86 - 91