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Connectedness and frequency connection among green bond, cryptocurrency and green energy-related metals around the COVID-19 outbreak

Hongjun Zeng, Qingcheng Huang, Mohammad Abedin Orcid Logo, Abdullahi D. Ahmed, Brian Lucey

Research in International Business and Finance, Volume: 73, Start page: 102547

Swansea University Author: Mohammad Abedin Orcid Logo

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DOI (Published version): 10.1016/j.ribaf.2024.102547

Abstract

We investigate the return interdependence among green bonds, cryptocurrency indices and green energy-related metals. We apply time-varying parametric vector autoregression (TVP-VAR) conenctedness, wavelet coherence, Wavelet Quantile Correlation （WQC) and Quantile on Quantile (QQR) Connectedness Meth...

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Published in: Research in International Business and Finance
ISSN: 0275-5319 1878-3384
Published: Elsevier BV 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa67510
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Abstract: We investigate the return interdependence among green bonds, cryptocurrency indices and green energy-related metals. We apply time-varying parametric vector autoregression (TVP-VAR) conenctedness, wavelet coherence, Wavelet Quantile Correlation （WQC) and Quantile on Quantile (QQR) Connectedness Methods. Our empirical findings show that return connectedness has become even stronger after the outbreak of COVID-19, with both green bonds and cryptocurrency indices acting as net receivers of return spillovers. Surprisingly, Copper functioned as a net sender of return spillovers over the entire observation period. Findings revealed that the cryptocurrency index exhibited a consistent positive correlation with the green energy-related metals market at medium to short-term frequencies, whereas green bonds showed a negative correlation with metals market at short-term frequencies and a positive correlation at long-term frequencies.
Keywords: Green bond, cryptocurrency, green energy-related metals, return connectedness, wavelet coherence, quantile
College: Faculty of Humanities and Social Sciences
Funders: This paper was supported by the Major Program of the National Social Science Foundation of China (Grant No. 23&ZD175), the National Natural Science Foundation of China (Grant Nos. 72173096, 72303139, 71873103). Hongjun Zeng acknowledges the support of RMIT Research Stipend Scholarships (RRSS-SC).
Start Page: 102547

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