An integrated approach to optimize moving average rules in the EUA futures market based on particle swarm optimization and genetic algorithms

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• 作者：Xiaojia Liu^a ; ^b ; Haizhong An^a ; ^b ; ^c ; ^{ahz369@163.com} ; Lijun Wang^a ; ^b ; Xiaoliang Jia^a ; ^b
• 关键词：Carbon emission trading ; EUA futures market ; Moving average trading rules ; Particle swarm optimization ; Genetic algorithms
• 刊名：Applied Energy
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：185
• 期：part_P2
• 页码：1778-1787
• 全文大小：1153 K
• 卷排序：185

文摘

We proposed an integrated approach to optimize trading rules in EUA futures market. Adaptive moving average rules with different weights are used to make decision. The integrated rule is adjusted dynamically with PSO and genetic algorithms. Our results show generated trading rules can adapt price changes and make profits. This approach is helpful for traders in choosing trading rules and evading risks.