The hedging performance of green bond markets in China and the U.S.: Novel evidence from cryptocurrency uncertainty

Yufei Zhong, Xuesheng Chen, Chengfang Wang, Zhixian Wang and Yuchen Zhang

Energy Economics, 2023, vol. 128, issue C

Abstract: Analysing the green bond's hedging performance against cryptocurrency uncertainty is essential to maximising investment returns. The study innovatively uses the TVP-SV-VAR process to capture the time-dependent connection among cryptocurrency uncertainties and the green bond markets in China and the U.S. The quantitative outcomes present that cryptocurrency policy uncertainty (CPU) has favourable effects on China's green bond (CGB), often evidencing the property of China's green bond to hedge against cryptocurrency uncertainty. However, CPU's adverse and insignificant impacts on CGB refute this opinion. CPU has negative effects on U.S. green bonds (USGB) most of the time, which underlines that the U.S. green bond market is not an effectual safe haven against cryptocurrency uncertainty. By comparison, China's green bond has better hedging performance than the U.S. one regarding the uncertainties in the cryptocurrency market. Additionally, various time points accompanied by massive undulations in CPU and critical incidents exhibit interrelations among CPU, CGB and USGB. Further, we replace CPU with cryptocurrency price uncertainty (CPRU) to examine the robustness and confirm that the reported results and corresponding discussions are credible. Under the severe cryptocurrency risks, the conclusion offers significant implications to investors and relevant policymakers.

Keywords: Green bond; Hedging performance; Cryptocurrency uncertainty; Time-dependent; China; The United States (search for similar items in EconPapers)
JEL-codes: C32 D80 G12 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:128:y:2023:i:c:s0140988323006928

DOI: 10.1016/j.eneco.2023.107194

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