Risk spillover between carbon markets and stock markets from a progressive perspective: Measurements, spillover networks, and driving factors

Dong, Qingli; Zhao, Yanzhi; Ma, Xiaojun; Zhou, Yanan

doi:10.1016/j.eneco.2023.107228

Cited by 19 publications

(3 citation statements)

References 43 publications

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“…Silver, gold, copper, platinum, aluminum, and sugar emerge as net transmitters of volatility transmission. Dong et al (2024) highlight prior research confirming risk correlations and spillover effects between carbon and stock markets. Xu et al (2022) identified positive crosscorrelations between carbon-intensive industry stock returns and carbon allowance price returns in Shenzhen and Shanghai, contrasting with negative correlations in Beijing, Guangdong, and Hubei.…”

Section: Volatility Spillovermentioning

confidence: 57%

“…Zhang and Zhang (2023) observed that carbon price returns adversely impact firms' stock returns within regional markets, notably in Shenzhen and Guangdong. Dong et al (2024) revealed that the Chinese carbon and stock markets exhibit significant, asymmetric, and extreme-event-sensitive spillover effects, predominantly positioning the carbon market as an information net recipient. Zhang et al (2022) highlighted the nascent interconnectivity between China's carbon and stock markets.…”

Section: Volatility Spillovermentioning

confidence: 99%

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Volatility Spillover from Carbon Prices to Stock Prices: Evidence from China’s Carbon Emission Trading Markets

Ma,

Feng,

Chen

et al. 2024

JRFM

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The carbon emission trading markets represent an emerging domain within China. The primary objective of this study is to explore whether carbon price volatility influences stock market volatility among companies subject to these emission trading regulations. Employing daily returns data from 293 publicly traded companies regulated by these emission trading markets, this study encompasses the national carbon market and eight pilot regional carbon markets spanning from August 2013 to October 2023. The results demonstrate that volatility in regional carbon prices positively impacts the stock volatility of companies in the corresponding emission trading region, indicating a volatility spillover effect. Moreover, this spillover effect is more pronounced in sectors marked by lesser carbon intensity than those with greater carbon intensity. The volatility transmission is more pronounced in coastal areas than in inland regions. However, no notable distinctions in volatility transmission are discerned between the periods before and throughout the COVID-19 pandemic. Vector autoregression analyses substantiate that lagged carbon price fluctuations possess limited predictive capacity for contemporaneous equity market volatility and vice versa. The robustness of these outcomes is fortified by applying the E-GARCH model, which accounts for the volatility clustering phenomenon. As the first investigation into the volatility spillover effect between China’s emission trading market and corresponding stock markets, this study offers valuable insights into the investment strategies of retail investors, the formulation of carbon regulations by policymakers, and the carbon emission strategies of corporate managers.

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Section: Volatility Spillovermentioning

confidence: 57%

Section: Volatility Spillovermentioning

confidence: 99%

Volatility Spillover from Carbon Prices to Stock Prices: Evidence from China’s Carbon Emission Trading Markets

Ma,

Feng,

Chen

et al. 2024

JRFM

View full text Add to dashboard Cite

show abstract

“…Consequently, we put forward the second hypothesis: (2024) propose that the integration of the international carbon markets is weak and the EU ETS continues to be a net transmitter. Dong et al (2024) find that the Chinese carbon market displays notable, imbalanced spillover effects, and tends to be a net receiver. Guo & Feng (2021) suggest that the spillover effects among Chinese carbon emissions trading pilots are relatively constrained.…”

Section: Literature Reviewmentioning

confidence: 89%

Sustainability and Stability: Asymmetric Time–Frequency Connectedness and Risk Spillovers Among EU–China ETSs, Clean Energy, Precious Metals, and Green Bonds

Yu,

Chen,

2024

Preprint

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Emission trading schemes (ETSs) have become vital tools in striving toward global emission reduction objectives and promoting a sustainable economy. This paper empirically investigates the impact of market conditions on interconnectedness within precious metals, clean energy, green bonds, and carbon markets, focusing on China and the EU ETSs as the study subjects. A TVP-VAR-based asymmetric connectedness approach is adopted to capture the evolving relationships between the variables of interest in the time–frequency domain. The empirical findings reveal that: First, time-varying asymmetric connectedness and spillover effects among clean energy, precious metals, green bonds, and carbon markets are identified in both time and frequency domains under diverse market conditions, with long-term connectedness asymmetry being particularly sensitive, although spillovers exhibit variations. Second, the role and intensity of net transmitters or receivers vary across market conditions and frequency domains, indicating the complex and nuanced nature of market interactions. The EU ETS demonstrates a higher level of connectivity with global markets for clean energy, precious metals, and green bonds when compared to the Chinese ETS. However, it also shows greater susceptibility to fluctuations in market conditions. These results have significant implications for both investors striving to build sustainable diversified portfolios and regulators endeavoring to craft effective policies for risk regulation and sustainable development.

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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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Risk spillover between carbon markets and stock markets from a progressive perspective: Measurements, spillover networks, and driving factors

Cited by 19 publications

References 43 publications

Volatility Spillover from Carbon Prices to Stock Prices: Evidence from China’s Carbon Emission Trading Markets

Volatility Spillover from Carbon Prices to Stock Prices: Evidence from China’s Carbon Emission Trading Markets

Sustainability and Stability: Asymmetric Time–Frequency Connectedness and Risk Spillovers Among EU–China ETSs, Clean Energy, Precious Metals, and Green Bonds

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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