Measuring Climate Risk Spillovers for Sustainable Finance: A Quantile Time-Frequency Multilayer Network Analysis of Carbon, Energy, and Metals Markets

Global warming has made climate physical and transition risks systemic sources of financial instability and key challenges to sustainability. These risks can spread to carbon, energy, and metals markets, which are central to the low-carbon transition and sustainable finance. This paper, therefore, explores the Quantile Time-Frequency connections among climate physical risk, climate transition risk, and the carbon, energy, and metals markets, with the analysis conducted through the lens of higher-moment risks. Using climate physical and transition risk indices together with daily carbon, energy, and metals futures settlement prices spanning 1 July 2015 to 29 December 2023, we employ the GJRSK model to extract higher-moment risk measures and apply the Quantile Time-Frequency framework to examine spillover effects across return, volatility, skewness, and kurtosis dimensions under different quantiles over the short term and long term. Furthermore, we construct a multilayer network that integrates information on return, volatility, skewness, and kurtosis risks under diverse market conditions and measure the topological properties of this network. The results reveal the following key insights: First, higher-moment risk spillovers are pronounced, though their magnitude is lower than that of return and volatility spillovers. Second, return, skewness, and kurtosis spillovers are primarily short-term driven, while volatility spillovers are concentrated in the long run. Climate risks generally act as receivers, but they shift to transmitters during long-term market downturns. Finally, findings from the multilayer complex network analysis demonstrate pronounced differences in the structural configurations of the interconnected networks linking climate risks to the return, volatility, skewness, and kurtosis risks of the carbon, energy, and metals markets across varying conditional quantiles. These findings support the measurement and monitoring of climate-related systemic risk and provide implications for sustainable finance, carbon and energy transition policies, and cross-market risk governance.

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Publication Details

Journal
Sustainability
Published
2026-10-12
DOI
https://doi.org/10.3390/su182010355
Primary Topic
Sustainable Finance and Green Bonds
Type
article
Field-Weighted Citation Impact
0.00
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article

Measuring Climate Risk Spillovers for Sustainable Finance: A Quantile Time-Frequency Multilayer Network Analysis of Carbon, Energy, and Metals Markets

Yuqin Zhou, Zixuan Luo, Shan Wu
Sustainability
Sustainable Finance and Green Bonds
article

Measuring Climate Risk Spillovers for Sustainable Finance: A Quantile Time-Frequency Multilayer Network Analysis of Carbon, Energy, and Metals Markets

Yuqin Zhou, Zixuan Luo, Shan Wu
article en

Abstract

Global warming has made climate physical and transition risks systemic sources of financial instability and key challenges to sustainability. These risks can spread to carbon, energy, and metals markets, which are central to the low-carbon transition and sustainable finance. This paper, therefore, explores the Quantile Time-Frequency connections among climate physical risk, climate transition risk, and the carbon, energy, and metals markets, with the analysis conducted through the lens of higher-moment risks. Using climate physical and transition risk indices together with daily carbon, energy, and metals futures settlement prices spanning 1 July 2015 to 29 December 2023, we employ the GJRSK model to extract higher-moment risk measures and apply the Quantile Time-Frequency framework to examine spillover effects across return, volatility, skewness, and kurtosis dimensions under different quantiles over the short term and long term. Furthermore, we construct a multilayer network that integrates information on return, volatility, skewness, and kurtosis risks under diverse market conditions and measure the topological properties of this network. The results reveal the following key insights: First, higher-moment risk spillovers are pronounced, though their magnitude is lower than that of return and volatility spillovers. Second, return, skewness, and kurtosis spillovers are primarily short-term driven, while volatility spillovers are concentrated in the long run. Climate risks generally act as receivers, but they shift to transmitters during long-term market downturns. Finally, findings from the multilayer complex network analysis demonstrate pronounced differences in the structural configurations of the interconnected networks linking climate risks to the return, volatility, skewness, and kurtosis risks of the carbon, energy, and metals markets across varying conditional quantiles. These findings support the measurement and monitoring of climate-related systemic risk and provide implications for sustainable finance, carbon and energy transition policies, and cross-market risk governance.

SustainabilityVol. 18(20)
Chongqing Normal University (CN), Nanjing University of Finance and Economics (CN)
Openalex Percentile: Top 8%
Sustainable Finance and Green Bonds
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