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Carbon price prediction considering climate change: A text-based framework

文献类型：期刊论文

作者Xie, Qiwei2; Hao, Jingjing2; Li, Jingyu2; Zheng, Xiaolong1
刊名ECONOMIC ANALYSIS AND POLICY
出版日期2022-06-01
卷号74页码:382-401
关键词Carbon price prediction Text mining Climate change Long short-term memory (LSTM) Random forest (RF)
ISSN号0313-5926
DOI10.1016/j.eap.2022.02.010
通讯作者Li, Jingyu(lijy@bjut.edu.cn)
英文摘要Carbon 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.
WOS关键词EU-ETS ; CHINA ; MARKET ; VOLATILITY ; EMISSIONS ; IMPACTS ; POLICY ; IDENTIFICATION ; SPILLOVERS ; INTERVAL
资助项目National 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]
WOS研究方向Business & Economics
语种英语
WOS记录号WOS:000792955200002
出版者ELSEVIER
资助机构National 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
源URL[http://ir.ia.ac.cn/handle/173211/49434]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心
通讯作者Li, Jingyu
作者单位1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Beijing Univ Technol, Sch Econ & Management, 100 Pingleyuan, Beijing 100124, Peoples R China
推荐引用方式
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.

入库方式： OAI收割

来源：自动化研究所

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