Carbon price prediction considering climate change: A text-based framework
Xie, Qiwei1; Hao, Jingjing1; Li, Jingyu1; Zheng, Xiaolong2
Source PublicationECONOMIC ANALYSIS AND POLICY
ISSN0313-5926
2022-06-01
Volume74Pages:382-401
Corresponding AuthorLi, Jingyu(lijy@bjut.edu.cn)
AbstractCarbon trading is a vital market mechanism to achieve carbon emission reduction. The accurate prediction of the carbon price is conducive to the effective management and decision-making of the carbon trading market. However, existing research on carbon price forecasting has ignored the impacts of multiple factors on the carbon price, especially climate change. This study proposes a text-based framework for carbon price prediction that considers the impact of climate change. Textual online news is innovatively employed to construct a climate-related variable. The information is combined with other variables affecting the carbon price to forecast the carbon price, using a long short-term memory network and random forest model. The results demonstrate that the prediction accuracy of the carbon price in the Hubei and Guangdong carbon markets is enhanced by adding the textual variable that measures climate change. (C)& nbsp;2022 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.
KeywordCarbon price prediction Text mining Climate change Long short-term memory (LSTM) Random forest (RF)
DOI10.1016/j.eap.2022.02.010
WOS KeywordEU-ETS ; CHINA ; MARKET ; VOLATILITY ; EMISSIONS ; IMPACTS ; POLICY ; IDENTIFICATION ; SPILLOVERS ; INTERVAL
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61673381] ; Key programs of social science of Beijing Municipal Education Commission[SZ202210005004] ; Natural Science Foundation of Beijing[9202002] ; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences ; Beijing Postdoctoral Research Foundation[2021-zz-168] ; Ministry of Science and Technology of China[2020AAA0108401] ; Ministry of Science and Technology of China[2019QY(Y)0101] ; China Postdoctoral Science Foundation[2020M680281]
Funding OrganizationNational Natural Science Foundation of China ; Key programs of social science of Beijing Municipal Education Commission ; Natural Science Foundation of Beijing ; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences ; Beijing Postdoctoral Research Foundation ; Ministry of Science and Technology of China ; China Postdoctoral Science Foundation
WOS Research AreaBusiness & Economics
WOS SubjectEconomics
WOS IDWOS:000792955200002
PublisherELSEVIER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/49435
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
Corresponding AuthorLi, Jingyu
Affiliation1.Beijing Univ Technol, Sch Econ & Management, 100 Pingleyuan, Beijing 100124, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Xie, Qiwei,Hao, Jingjing,Li, Jingyu,et al. Carbon price prediction considering climate change: A text-based framework[J]. ECONOMIC ANALYSIS AND POLICY,2022,74:382-401.
APA Xie, Qiwei,Hao, Jingjing,Li, Jingyu,&Zheng, Xiaolong.(2022).Carbon price prediction considering climate change: A text-based framework.ECONOMIC ANALYSIS AND POLICY,74,382-401.
MLA Xie, Qiwei,et al."Carbon price prediction considering climate change: A text-based framework".ECONOMIC ANALYSIS AND POLICY 74(2022):382-401.
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