期刊
ENERGIES
卷 15, 期 15, 页码 -出版社
MDPI
DOI: 10.3390/en15155540
关键词
carbon market; probability distribution; recurrence network; breakpoints
资金
- National Key Research and Development Program of China [2020YFA0608602]
- National Natural Science Foundation of China [72174091]
- Qing Lan Project of Jiangsu Province [2021]
- Six talent peaks project in Jiangsu Province [JY-055]
- China Postdoctoral Foundation [2021M691312]
This study proposes a method for identifying abrupt transitions in the carbon market from the perspective of a complex network. By considering the influence of random factors on the carbon price series, a recurrence network of carbon price probability density is constructed. The method defines a break index and statistical test method based on the community structure. Empirical analysis shows that there are many abrupt transitions in the carbon price series of the two markets, which are closely related to major events.
The scientific judgement of the structural abrupt transition characteristics of the carbon market price is an important means to comprehensively analyze its fluctuation law and effectively prevent carbon market risks. However, the existing methods for identifying structural changes of the carbon market based on carbon price data mostly regard the carbon price series as a deterministic time series and pay less attention to the uncertainty implied by the carbon price series. We propose a framework for identifying abrupt transitions in the carbon market from the perspective of a complex network by considering the influence of random factors on the carbon price series, expressing the carbon price series as a sequence of probability density functions, using the distribution of probability density to reveal the uncertainty information implied by carbon price series and constructing a recurrence network of carbon price probability density. Based on the community structure, the break index and statistical test method are defined. The simulation verifies the effectiveness and superiority of the method compared with traditional methods. An empirical analysis uses the carbon price data of the European Union carbon market and seven pilot carbon markets in China. The results show many abrupt transitions in the carbon price series of the two markets, whose occurrence period is closely related to major events.
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