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

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.

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Publication Details

Journal
Energies
Published
2024-11-20
DOI
https://doi.org/10.3390/en17225806
Citations
8
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
9.03

Funders

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article

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

Shigeyuki Hamori, Yulian Zhang, Wenting Zhang, Tiantian Liu
8 citations
Energies
Market Dynamics and Volatility
9.03
article

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

Shigeyuki Hamori, Yulian Zhang, Wenting Zhang, Tiantian Liu
article en
8 citations

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.

EnergiesVol. 17(22)
Dalian Ocean University (CN), Yamato University (JP), The Institute of Statistical Mathematics (JP), Kobe University (JP)
Japan Society for the Promotion of Science London, Japan Society for the Promotion of Science
Openalex Percentile: Top 3%
Market Dynamics and Volatility
9.03
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