Tail dependence and risk spillover effects between China's carbon market and energy markets

被引:25
作者
Liu, Jianing [1 ]
Man, Yuanyuan [1 ]
Dong, Xiuliang [1 ]
机构
[1] Jilin Univ, Sch Business & Management, Changchun 130012, Jilin, Peoples R China
关键词
Carbon market; Energy markets; China; Tail dependence; Risk spillover effects; EMISSION TRADING SCHEME; VOLATILITY SPILLOVER; PRICE DRIVERS; OIL; MODELS; ALLOWANCES; COMMODITY; POLICY; GAS;
D O I
10.1016/j.iref.2022.11.013
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This study measures the tail dependence and risk spillover effects between China's carbon market and the coal, crude oil, and natural gas markets using the TVP-Copula-CoVaR method. Our results indicate that China has a high-risk carbon market as it is more vulnerable to extreme external shocks or seasonal fluctuations than the energy markets. Additionally, the upside and downside tail dependence are asymmetric, indicating that investing in carbon markets diminishes the risk of investing in energy commodities. The spillover of downside risks between these markets is noticeably greater than that of upside risks, implying that the carbon and energy markets are all the more susceptible to adverse news and sensitive to extreme declines. The results reveal implications regarding risk assessment and management for investors, portfolio managers, and policymakers at the initial stage of a new carbon market.
引用
收藏
页码:553 / 567
页数:15
相关论文
共 59 条
[1]   Bootstrap tests for distributional treatment effects in instrumental variable models [J].
Abadie, A .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2002, 97 (457) :284-292
[2]  
Adekoya O. B., 2021, RESOUR POLICY, V74
[3]   CoVaR [J].
Adrian, Tobias ;
Brunnermeier, Markus K. .
AMERICAN ECONOMIC REVIEW, 2016, 106 (07) :1705-1741
[4]   Price drivers and structural breaks in European carbon prices 2005-2007 [J].
Alberola, Emilie ;
Chevallier, Julien ;
Cheze, Benoit .
ENERGY POLICY, 2008, 36 (02) :787-797
[5]   A copula-GARCH approach for analyzing dynamic conditional dependency structure between liquefied petroleum gas freight rate, product price arbitrage and crude oil price [J].
Bai, Xiwen ;
Lam, Jasmine Siu Lee .
ENERGY ECONOMICS, 2019, 78 :412-427
[6]   Risk spillovers across the energy and carbon markets and hedging strategies for carbon risk [J].
Balcilar, Mehmet ;
Demirer, Riza ;
Hammoudeh, Shawkat ;
Duc Khuong Nguyen .
ENERGY ECONOMICS, 2016, 54 :159-172
[7]   Forecasting carbon futures volatility using GARCH models with energy volatilities [J].
Byun, Suk Joon ;
Cho, Hangjun .
ENERGY ECONOMICS, 2013, 40 :207-221
[8]   Volatility spillover effect and dynamic correlation between regional emissions allowances and fossil energy markets: New evidence from China's emissions trading scheme pilots [J].
Chang, Kai ;
Ye, Zhifang ;
Wang, Weihong .
ENERGY, 2019, 185 :1314-1324
[9]   Characterizing the dynamic evolutionary behavior of multivariate price movement fluctuation in the carbon-fuel energy markets system from complex network perspective [J].
Chen, Weidong ;
Xiong, Shi ;
Chen, Quanyu .
ENERGY, 2022, 239
[10]   Modeling the nexus of crude oil, new energy and rare earth in China: An asymmetric VAR-BEKK (DCC)-GARCH approach [J].
Chen, Yufeng ;
Zheng, Biao ;
Qu, Fang .
RESOURCES POLICY, 2020, 65