A PSO Approach to Search for Adaptive Trading Rules in the EUA Futures Market

被引:3
作者
Wang, Lijun [1 ,2 ]
An, Haizhong [1 ,2 ,3 ]
Liu, Xiaojia [1 ,2 ]
机构
[1] China Univ Geosci, Sch Humanities & Econ Management, Beijing 100083, Peoples R China
[2] Minist Land & Resources, Key Lab Carrying Capac Assessment Resource & Envi, Beijing 100083, Peoples R China
[3] China Univ Geosci, Lab Resources & Environm Management, Beijing 100083, Peoples R China
来源
CLEAN, EFFICIENT AND AFFORDABLE ENERGY FOR A SUSTAINABLE FUTURE | 2015年 / 75卷
关键词
Carbon emission trading; Futures markets; Technical trading rules; Particle Swarm Optimization;
D O I
10.1016/j.egypro.2015.07.246
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The carbon emission futures markets become more and more important in worldwide. More and more counties begin to emphasize environmental protection in the economic development. Carbon emission trading has become an important part of the energy finance. How to make more profits in the carbon emission futures market is concern by more and more traders and scholars. This paper proposed an approach to search for optimal trading rules in the CO2 allowance futures markets. A group of different moving average trading rules with different weights are used to constitute an integrated trading rule. This is better than a single fixed moving average trading rule. Similarity of trading rules, a parameter we designed, is used to help select basic rules. The authors use static particle swarm optimization process to find the best weights distributions of the selected basic trading rules. After the initial weight distribution is determined, the weights of the basic trading rules will adjusted dynamically every day in the trading process using particle swarm optimization algorithms. Experiments using the EUA Futures Market price data were conducted to find out best adaptive trading rules in the carbon emission futures market. According to our results, it is not necessary to use two moving average trading rules that making same investment advice at a probability higher than 70%. The results show this approach have good performance in adjusting the weights according to the price changes. We found that the adaptive trading rules can help traders make profit in the EUA Futures Market except extreme special circumstances after price change significantly. This approach might be helpful for traders to make scientific decision in actual investments. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
引用
收藏
页码:2504 / 2509
页数:6
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