Quantile Connectedness of Uncertainty Indices, Carbon Emissions, Energy, and Green Assets: Insights from Extreme Market Conditions

Tiantian Liu, Yulian Zhang, Wenting Zhang and Shigeyuki Hamori
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Tiantian Liu: School of Economics and Management, Dalian Ocean University, Dalian 116023, China
Yulian Zhang: School of Finance and Trade, Wenzhou Business College, Quhai District, Wenzhou 325034, China
Wenting Zhang: The Institute of Statistical Mathematics, Tachikawa 190-8562, Japan

Energies, 2024, vol. 17, issue 22, 1-24

Abstract: In this study, we investigate the volatility spillover effects across uncertainty indices (Infectious Disease Equity Market Volatility Tracker (IDEMV) and Geopolitical Risk Index (GPR)), carbon emissions, crude oil, natural gas, and green assets (green bonds and green stock) under extreme market conditions based on the quantile connectedness approach. The empirical findings reveal that the total and directional connectedness across green assets and other variables in extreme market conditions is much higher than that in the median, and there is obvious asymmetry in the connectedness measured at the extreme lower and upper quantiles. Our findings suggest that the uncertainty caused by COVID-19 has a more significant impact on green assets than the uncertainty related to the Russia–Ukraine war under normal and extreme market conditions. Furthermore, we discover that the uncertainty indices are more important in predicting green asset volatility under extreme market conditions than they are in the normal market. Finally, we observe that the dynamic total spillover effects in the extreme quantiles are significantly higher than those in the median.

Keywords: green finance market; quantile connectedness; uncertainty; COVID-19; volatility spillover effects (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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