A Model for Analyzing Transaction Price Volatility of Generation Rights Trade Market Based on Cellular Automata and Complex Network Theories

被引:0
|
作者
Wu Yang [1 ]
Liu Junyong [1 ]
Liu Jichun [1 ]
Huang Yuan [1 ]
Yan Zhanxin [1 ]
Zhang Li [1 ]
Gao Hongjun [1 ]
机构
[1] Sichuan Univ, Sch Elect Engn & Informat, Chengdu, Peoples R China
关键词
cellular autontation; complex networks; generation rights trade; individual behavior; price volatility;
D O I
暂无
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
For the researches on the relationship between the influence factors of the generation rights transaction price and the price volatility arc very few, the effects of individual behavior on the price volatility of generation rights trade market are studied in this paper based on cellular automata (CA) and complex networks (CN) theories. Firstly, the CA model of generation rights trade market is proposed. Then, the behavior model of the generation rights trader forecasting the coal price trends is constructed based on CN theory. At last, depending on the above two models, combining the transformation rules of generation rights trade CA with the behavior model, the model for analyzing the price volatility of generation rights trade market is established. The simulation results show that the individual behavior is an important factor of causing price volatility of generation rights trade market. It is verified that the relationship between the individual behavior and the price volatility of generation rights trade market can be depicted clearly by the proposed model, and it provides a new method for constructing the model of influence factors of power generation rights trade market by complex system theories.
引用
收藏
页码:87 / 92
页数:6
相关论文
共 4 条
  • [1] Analysis of the transmission characteristics of China's carbon market transaction price volatility from the perspective of a complex network
    Jia, Jingjing
    Li, Huajiao
    Zhou, Jinsheng
    Jiang, Meihui
    Dong, Di
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2018, 25 (08) : 7369 - 7381
  • [2] Analysis of the transmission characteristics of China’s carbon market transaction price volatility from the perspective of a complex network
    Jingjing Jia
    Huajiao Li
    Jinsheng Zhou
    Meihui Jiang
    Di Dong
    [J]. Environmental Science and Pollution Research, 2018, 25 : 7369 - 7381
  • [3] Volatility forecasting for stock market index based on complex network and hybrid deep learning model
    Song, Yuping
    Lei, Bolin
    Tang, Xiaolong
    Li, Chen
    [J]. JOURNAL OF FORECASTING, 2024, 43 (03) : 544 - 566
  • [4] Copper cross-market volatility transition based on a coupled hidden Markov model and the complex network method
    Shen, Junjie
    Huang, Shupei
    [J]. RESOURCES POLICY, 2022, 75