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Dynamic nonlinear connectedness between the green bonds, clean energy, and stock price: the impact of the COVID-19 pandemic

Shanglei Chai Orcid Logo, Wenjun Chu, Zhen Zhang, Zhilong Li, Abedin Abedin

Annals of Operations Research

Swansea University Author: Abedin Abedin

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DOI (Published version): 10.1007/s10479-021-04452-y

Abstract

This paper uses weekly data from July 01, 2011 to July 09, 2021 to examine the dynamic nonlinear connectedness between the green bonds, clean energy, and stock price around the COVID-19 outbreak in the global markets. By building a time-varying parameter vector autoregression model (TVP-VAR), the co...

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Published in: Annals of Operations Research
ISSN: 0254-5330 1572-9338
Published: Springer Science and Business Media LLC
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URI: https://cronfa.swan.ac.uk/Record/cronfa64233
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Abstract: This paper uses weekly data from July 01, 2011 to July 09, 2021 to examine the dynamic nonlinear connectedness between the green bonds, clean energy, and stock price around the COVID-19 outbreak in the global markets. By building a time-varying parameter vector autoregression model (TVP-VAR), the comparison analyses of pre- and during the COVID-19 sample groups verify the existence of nonlinear and dynamic correlation among the three variables. First, prior to the COVID-19 pandemic, the simultaneous impacts of clean energy on stock price increased over time. Second, the results of impulse responses at different horizons indicate that green bonds lead to a short-term increase of clean energy, and it exerts an increasingly positive impacts after the COVID-19 outbreak. The COVID-19 has weakened the negative impacts of green bonds on stock price in the medium term. Finally, through the analysis of impulse responses at different points, we find that stock prices will rise when clean energy is subjected to a positive shock, and this positive effect is stronger during economic recovery period than in the other two periods.
Keywords: Green bonds, Clean energy market, Stock price, COVID-19 pandemic, TVP-VAR
College: Faculty of Humanities and Social Sciences
Funders: This work was supported by the National Natural Science Foundation of China (Nos. 71704098, 71971039, 72001191, 72003110), and the Natural Science Foundation of Henan Province (No. 202300410442).

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