Connectedness of China’s green bond and green stock markets at the low- and high-order moments: The role of economic and climate policy uncertainty

Yu Wang, Adrian Wai Kong Cheung, Wan-Lin Yan and Bin Wang

The North American Journal of Economics and Finance, 2025, vol. 78, issue C

Abstract: Economic policy uncertainty (EPU) and climate policy uncertainty (CPU) may affect green finance (GF) markets not only on lower-order moments (mean and variance) but also on higher-order moments (skewness and kurtosis). This study analyses the impacts of these uncertainties on the high-order moment connectedness in green bond (GB) and green stock (GS) markets in China using the Glosten, Jagannathan, and Runkle GARCH with Skewness and Kurtosis (GJRSK) model, time- and frequency-domain methodologies, and quantile-on-quantile regression. Static analysis shows that spillovers from higher order moments (skewness 63.18 % and kurtosis 68.91 %) are higher than those from lower order moments (return 51.52 % and volatility 61.83 %), and that spillovers from return (48.88 %), skewness (33.8 %), and kurtosis (56.81 %) occur mainly in the short term, whereas spillover from volatility (38.23) occurs mainly in the long term. The dynamic analysis indicates significant time-variation in the dynamic total and net connectedness indices. COVID-19 has a greater impact on the connectedness of volatility, skewness, and kurtosis, and a relatively weaker impact on the connectedness of returns. The dynamic total return and kurtosis spillovers occur mainly in the short term, while the dynamic total volatility and skewness spillovers occur mainly in the long term. In terms of the net-pairwise directional connectedness, GB is the largest shock emitter, while stocks in the environmental protection (EP) sector are the primary receivers of skewness and kurtosis spillovers. In addition, we find that CPU and EPU affect the upside risk of total spillovers in the GF market more than the downside risk, and exhibit significant heterogeneity across time, frequency, and quantiles. The results offer both insights for policymakers to coordinate the GF markets and for investment institutions to design asset allocation and risk management strategies, contributing to the understanding of the complex dynamics of the GF market’s response to climate and economic policies, thereby promoting economically sustainable development and financial stability.

Keywords: Green financial market; Economic policy uncertainty; Climate policy uncertainty; Spillover effect; Quantile-on-quantile regression (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:78:y:2025:i:c:s1062940825000506

DOI: 10.1016/j.najef.2025.102410

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