The time-frequency connectedness among carbon, traditional/new energy and material markets of China in pre- and post-COVID-19 outbreak periods

Jiang, Wei; Chen, Yunfei

doi:10.1016/j.energy.2022.123320

Cited by 70 publications

(19 citation statements)

References 47 publications

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“…The occurrence of tail quantile-extreme events is also a part of greater interest to investors and governments. In the Chinese carbon trading market, the transmission of market risk is exacerbated by extreme events and the market suffers severe shocks (Zhu et al, 2021;Jiang and Chen, 2022;Zhao and Wen, 2022). Third, this paper also presents novel information/risk transmission findings in the carbon market with energy, commodities and financial markets.…”

Section: Introductionmentioning

confidence: 90%

“…There are few studies related to highcarbon products and carbon markets in the existing literature. Most scholars have selected steel, iron ore, and aluminum as the subjects of research on the relationship with carbon spillovers (Ma and Wang, 2021;Jiang and Chen, 2022). Jiang and Chen (2022) include steel and aluminum in the materials market, and the results after COVID-19 indicate an increase in spillovers in the materials market.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Most scholars have selected steel, iron ore, and aluminum as the subjects of research on the relationship with carbon spillovers (Ma and Wang, 2021;Jiang and Chen, 2022). Jiang and Chen (2022) include steel and aluminum in the materials market, and the results after COVID-19 indicate an increase in spillovers in the materials market. The carbon market in China is still evolving and remains sensitive to other markets.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In recent years, scholars have extensively discussed the risk contagion of carbon markets (Balc et al, 2020;Yuan and Yang, 2020;Zhu et al, 2020;Xu, 2021), analyzing the spillover effects of carbon markets with energy, commodity and financial markets (Ji et al, 2018;Wang and Guo, 2018;Gong et al, 2021;Ma and Wang, 2021;Jiang and Chen, 2022). Nonetheless, most studies on risk contagion in previous generations lack a systematic framework.…”

Section: Introductionmentioning

confidence: 99%

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Identifying Risk Transmission in Carbon Market With Energy, Commodity and Financial Markets: Evidence From Time-Frequency and Extreme Risk Spillovers

et al. 2022

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The carbon market is a vital tool to achieve carbon neutrality. This paper uses daily closing price data of Shenzhen carbon trading market, energy, commodity and financial markets from 18 October 2018 to 19 August 2021, examining the transmission of risk/information from the perspective of market volatility spillover and tail risk transmission based on quantile spillover. The stock market crash and COVID-19 have increased the volatility of the system substantially. Next, the increase in trading frequency is accompanied by an increase in total volatility connectivity, and the carbon market transforms into a recipient of systemic shocks. Finally, the results of tail risk transmission reveal that the net effect of carbon reception increases significantly. These findings have implications for policymakers to improve the carbon market and provide important insights for investors to trade in turbulent periods.

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Section: Introductionmentioning

confidence: 90%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identifying Risk Transmission in Carbon Market With Energy, Commodity and Financial Markets: Evidence From Time-Frequency and Extreme Risk Spillovers

et al. 2022

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“…Thus, Wang, Wang 40 advised that boosting decarbonization or energy-saving systems directly contributes to a reduction in carbon intensity. However, Jiang and Chen 41 claimed that the post-outbreak carbon market spillovers are roughly twice as large as the pre-COVID-19 period.…”

Section: Introductionmentioning

confidence: 99%

Evidence from the nonlinear autoregressive distributed lag model on the asymmetric influence of the first wave of the COVID-19 pandemic on energy markets

Armeanu

Gherghina

Vasile

et al. 2022

Energy & Environment

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The COVID-19 pandemic remained a global risk factor and integrated into various means in the functioning of companies, economies and financial markets. Therefore, this paper investigates how COVID-19 influences the energy market in the main financial markets (China, France, Germany, Italy, Spain and the United States), using time series from February 28, 2020, to November 3, 2020. The goal of this research is to investigate the asymmetric impact of COVID-19 from leading financial markets on energy commodities. In this regard, the non-linear auto-regressive distributed lag (NARDL) framework is employed to capture the long-run asymmetric reactions. The econometric design allows to explore the long-term asymmetric reactions of dependent variables through positive and negative partial sum decompositions of changes in the explanatory variables. The quantitative results show a significant long-run asymmetric interdependence between the number of new SARS-CoV-2 incidence and mortality and the daily percent change in close price of future contracts pertaining to Brent oil, crude oil WTI, carbon emissions, gasoline RBOB, heating oil, Chukyo kerosene, and natural gas. Furthermore, no asymmetry is found in the case of ethanol and fuel oil futures. The novelty of this article is the study of the impact of COVID-19 on the energy sector during the first two waves of COVID-19 by applying the NARDL model that allows to capture long-term asymmetric reactions. Certainly, further research on this topic is necessary due to the permanent shifts in the pandemic, as well as the availability of longer data periods on COVID-19.

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Research on the risk spillover effect of carbon emission trading market and various industry markets in China and the European Union

Cui,

Fan,

2024

Energy Science & Engineering

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Widely concerns over the carbon emission problems have been aroused. Prior studies have documented the correlation between the carbon emission market and industries separately. This study compared the tail risks and risk spillover effect of the carbon emission and 11 industries markets in China and the European Union (EU) by using the multivariate multi‐quartile conditional autoregressive at‐risk model. Moreover, to evaluate the risk spillover of each market under extreme risk conditions in time domain and frequency domain, DY spillover index and BK spillover index were constructed via generalized forecast error variance decomposition and generalized causation spectrum, respectively. Findings are as follows: (1) The tail risks and fluctuation of the trend of Chinese industry markets reflects more higher and larger than those in the EU; (2) The EU suffers from smaller external shocks, while China has the opposite result and can recover relatively faster; (3) In China, energy, industrial, information technology, financial, real estate, consumer goods, carbon emissions, and discretionary consumption industries are risk spillover industries, while healthcare, materials, telecommunication services, and utilities industries are risk receiving industries. In contrast, the risk spillover industries in the EU remain consistent with those of the Chinese markets except for the materials, discretionary consumption, consumer goods, information technology and real estate industries. (4) On the short‐term, medium‐term and long‐term scales, the risk spillover of China's carbon emission trading market and various industries is basically consistent with that of the EU. These findings contribute to reducing greenhouse gas emissions and achieving the goal of carbon peak and carbon neutrality.

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The time-frequency connectedness among carbon, traditional/new energy and material markets of China in pre- and post-COVID-19 outbreak periods

Cited by 70 publications

References 47 publications

Identifying Risk Transmission in Carbon Market With Energy, Commodity and Financial Markets: Evidence From Time-Frequency and Extreme Risk Spillovers

Identifying Risk Transmission in Carbon Market With Energy, Commodity and Financial Markets: Evidence From Time-Frequency and Extreme Risk Spillovers

Evidence from the nonlinear autoregressive distributed lag model on the asymmetric influence of the first wave of the COVID-19 pandemic on energy markets

Research on the risk spillover effect of carbon emission trading market and various industry markets in China and the European Union

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