Return and volatility connectedness among carbon and energy markets based on time- and frequency-domain approaches

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Abstract

With heightened concern over carbon neutrality and increased energy market fluctuations against the backdrop of increasing global uncertainty, it becomes imperative to thoroughly investigate the information transmission and risk contagion between carbon and energy markets. This paper empirically explores the return and volatility connectedness among carbon and energy markets (electricity, natural gas, crude oil, and coal) from April 2008 to September 2021 by employing the time-frequency domain connectedness approaches. This paper indicates: i) the return connectedness exceeds volatility connectedness, and extreme events can intensify the dynamic changes; ii) the return connectedness is predominantly concentrated at high-frequency, while the volatility connectedness is concentrated at medium- and low-frequency. Net volatility connectedness maintains a consistent direction across all markets in the time-frequency domain. In contrast, net return connectedness exhibits an opposing direction at high-frequency and medium- and low-frequency. iii) the natural gas and coal markets predominantly act as net transmitters in both return and volatility connectedness, while the electricity, crude oil, and carbon markets operate as net receivers. Moreover, during the COVID-19 pandemic, the carbon market emerged as an information receiver in time-frequency domains and acted as a risk transmitter, exporting risk, particularly to the electricity market. These conclusions help investors, high-carbon enterprises, and policymakers to comprehensively understand the carbon-energy relationships, thereby supporting sustainable energy development and low-carbon economic goals. Simultaneously, this paper provides insights for enhancing carbon markets in emerging markets like China.

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APA

Wu, Y., Ren, W., Xiong, Y., Cao, G., Liang, P., & Zeng, W. (2023). Return and volatility connectedness among carbon and energy markets based on time- and frequency-domain approaches. Frontiers in Environmental Science, 11. https://doi.org/10.3389/fenvs.2023.1315893

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