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

doi:10.1016/j.eap.2022.02.010

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	Carbon price prediction considering climate change: A text-based framework
	Xie, Qiwei 1; Hao, Jingjing 1; Li, Jingyu 1; Zheng, Xiaolong2
发表期刊	ECONOMIC ANALYSIS AND POLICY
ISSN	0313-5926
	2022-06-01
卷号	74 页码:382-401
通讯作者	Li, Jingyu(lijy@bjut.edu.cn)
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.
关键词	Carbon price prediction Text mining Climate change Long short-term memory (LSTM) Random forest (RF)
DOI	10.1016/j.eap.2022.02.010
关键词[WOS]	EU-ETS ; CHINA ; MARKET ; VOLATILITY ; EMISSIONS ; IMPACTS ; POLICY ; IDENTIFICATION ; SPILLOVERS ; INTERVAL
收录类别	SCI
语种	英语
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]
项目资助者	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
WOS研究方向	Business & Economics
WOS类目	Economics
WOS记录号	WOS:000792955200002
出版者	ELSEVIER
引用统计	被引频次：22[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/49435
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者	Li, Jingyu
作者单位	1.Beijing Univ Technol, Sch Econ & Management, 100 Pingleyuan, Beijing 100124, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, 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.