Fuzzy Rule-Based Stock Trading System

被引：0
|
作者：
Yeh, I-Cheng [1 ]
Lien, Che-hui [2 ]
机构：
[1] Chung Hua Univ, Dept Informat Management, Hsinchu 30067, Taiwan
[2] Univ Kamploos, Dept Management, Kampo, BC, Canada
来源：
IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011) | 2011年
关键词：
fuzzy rule; market timing; stock market; moving average; over-learning; NEURAL-NETWORK; GENETIC ALGORITHMS; PREDICTION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Our study investigates the generalization capability of fuzzy rule-based trading systems and conducted an empirical study on Taiwan's stock market during 1991/1/1-2010/12/31. The empirical conclusions are as follows (1) The investment performance in the training period is much better than that in the testing period, which exhibits over-learning. (2) The symmetry rules approach demonstrates that the pure price trend trading system is better than the pure volume trend trading system and hybrid price-volume trend trading system. The pure volume trend trading system is the poorest system. (3) The asymmetry rules approach demonstrates that the trading system optimized in one period may be performed poorer in another period. The pure price trend buy-rule combined with the pure volume trend sell-rule has good performance in 1991-2000 but acts poorly in 2001-2010.
引用
收藏
页码：2066 / 2072
页数：7
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