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High-dimensional nonlinear dependence and risk spillovers analysis between China’s carbon market and its major influence factors
In July 2021, China began its national emissions trading scheme, marking a new stage of development for the country’s carbon market. This study analyzes the multidimensional correlation between carbon prices in the Guangdong pilot market and eight influencing factors from three perspectives (the int...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9167038/ https://www.ncbi.nlm.nih.gov/pubmed/35694370 http://dx.doi.org/10.1007/s10479-022-04770-9 |
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author | Zhang, Shaobin Ji, Hao Tian, Maoxi Wang, Binyao |
author_facet | Zhang, Shaobin Ji, Hao Tian, Maoxi Wang, Binyao |
author_sort | Zhang, Shaobin |
collection | PubMed |
description | In July 2021, China began its national emissions trading scheme, marking a new stage of development for the country’s carbon market. This study analyzes the multidimensional correlation between carbon prices in the Guangdong pilot market and eight influencing factors from three perspectives (the international carbon market, energy prices, and China’s economic situation), using the ARMA-GARCH-vine copula model. The CoVaR between the carbon price and each factor is then calculated using copula-CoVaR. The results show that the crude oil market plays the primary role in the vine structure, and that the carbon market is not strongly correlated with other markets. China’s carbon market is still a regional market driven by government policy, and the international carbon and energy markets (especially the crude oil market) have upward risk spillover effects upon it. This indicates an asymmetric risk spillover between influencing factors and the carbon market. The findings of this study will help market participants prepare risk management strategies and make related investment decisions, and provide a reference for policy makers to formulate national emission trading scheme policies. GRAPHICAL ABSTRACT: [Image: see text] |
format | Online Article Text |
id | pubmed-9167038 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-91670382022-06-07 High-dimensional nonlinear dependence and risk spillovers analysis between China’s carbon market and its major influence factors Zhang, Shaobin Ji, Hao Tian, Maoxi Wang, Binyao Ann Oper Res Original Research In July 2021, China began its national emissions trading scheme, marking a new stage of development for the country’s carbon market. This study analyzes the multidimensional correlation between carbon prices in the Guangdong pilot market and eight influencing factors from three perspectives (the international carbon market, energy prices, and China’s economic situation), using the ARMA-GARCH-vine copula model. The CoVaR between the carbon price and each factor is then calculated using copula-CoVaR. The results show that the crude oil market plays the primary role in the vine structure, and that the carbon market is not strongly correlated with other markets. China’s carbon market is still a regional market driven by government policy, and the international carbon and energy markets (especially the crude oil market) have upward risk spillover effects upon it. This indicates an asymmetric risk spillover between influencing factors and the carbon market. The findings of this study will help market participants prepare risk management strategies and make related investment decisions, and provide a reference for policy makers to formulate national emission trading scheme policies. GRAPHICAL ABSTRACT: [Image: see text] Springer US 2022-06-04 /pmc/articles/PMC9167038/ /pubmed/35694370 http://dx.doi.org/10.1007/s10479-022-04770-9 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Zhang, Shaobin Ji, Hao Tian, Maoxi Wang, Binyao High-dimensional nonlinear dependence and risk spillovers analysis between China’s carbon market and its major influence factors |
title | High-dimensional nonlinear dependence and risk spillovers analysis between China’s carbon market and its major influence factors |
title_full | High-dimensional nonlinear dependence and risk spillovers analysis between China’s carbon market and its major influence factors |
title_fullStr | High-dimensional nonlinear dependence and risk spillovers analysis between China’s carbon market and its major influence factors |
title_full_unstemmed | High-dimensional nonlinear dependence and risk spillovers analysis between China’s carbon market and its major influence factors |
title_short | High-dimensional nonlinear dependence and risk spillovers analysis between China’s carbon market and its major influence factors |
title_sort | high-dimensional nonlinear dependence and risk spillovers analysis between china’s carbon market and its major influence factors |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9167038/ https://www.ncbi.nlm.nih.gov/pubmed/35694370 http://dx.doi.org/10.1007/s10479-022-04770-9 |
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