Enhanced decision making mechanism of rule-based genetic network programming for creating stock trading signals

作者：

Highlights：

• A novel rule-based decision making mechanism for stock trading is proposed.

• A large number of effective trading rules are generated by evolution and learning.

• A classification algorithm for stock trading is proposed.

• The results show that the rule-based system is better than individual-based method.

摘要

•A novel rule-based decision making mechanism for stock trading is proposed.•A large number of effective trading rules are generated by evolution and learning.•A classification algorithm for stock trading is proposed.•The results show that the rule-based system is better than individual-based method.

论文关键词：Evolutionary computation,Genetic network programming,Rule extraction,Stock trading,Technical analysis

论文评审过程：Available online 27 May 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.05.037