The Dynamic Correlation and Volatility Spillover among Green Bonds, Clean Energy Stock, and Fossil Fuel Market

Chaofeng Tang, Kentaka Aruga and Yi Hu ()
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Chaofeng Tang: Graduate School of Humanities and Management, Guangdong Medical University, No.1 New Town Avenue, Songshan Lake Hi-Tech Industrial Development Zone, Dongguan 523121, China
Yi Hu: Graduate School of Humanities and Management, Guangdong Medical University, No.1 New Town Avenue, Songshan Lake Hi-Tech Industrial Development Zone, Dongguan 523121, China

Sustainability, 2023, vol. 15, issue 8, 1-23

Abstract: This study employs mainly the Bayesian DCC-MGARCH model and frequency connectedness methods to respectively examine the dynamic correlation and volatility spillover among the green bond, clean energy, and fossil fuel markets using daily data from 30 June 2014 to 18 October 2021. Three findings arose from our results: First, the green bond market has a weak negative correlation with the fossil fuel (WTI oil, Brent oil, natural gas, heating oil, and gasoline) and clean energy markets, which means that green bonds play a critical hedging role against fossil fuel and clean energy. Second, the green bond and clean energy are net volatility receivers from WTI crude oil and heating oil for the short term, indicating that investors and policymakers need to pay attention to the WTI oil volatility spillover risk when promoting green bonds and clean energy. Third, the correlation and volatility spillover from WTI crude oil to green bonds and clean energy is stronger than that of Brent oil, which implies that investors and policymakers need to consider the price movements of WTI crude oil more than Brent oil when investing in the green bond market. In summary, our conclusion is that investors should be aware that green bond investing addresses the two-pronged investment strategy of (i) risk diversification and (ii) carbon mitigation. Thus, this study can provide essential information for energy investors and policymakers to achieve sustainable investment.

Keywords: fossil fuel; green bond; clean energy; Bayesian DCC-MGARCH models; frequency connectedness methods (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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