Risk Spillover Network in Commodity Markets Under Climate Transition Risk

ABSTRACT The article constructs a connectivity network based on the dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) model and spillover index method, systematically revealing the risk contagion effects within China's commodity markets under the context of climate transition. In the long run, the energy and chemical markets act as risk spillover transmitters in the commodity system, while the metal and agricultural markets function as risk receivers. Gold typically passively absorbs risk spillovers from other markets during risk events, presenting a structure of “receiving more and spilling less.” However, in the short term, the risk roles of markets undergo shifts in response to changes in macroeconomic conditions. The risk roles of different markets exhibit significant time‐varying characteristics, and the network structure experiences dynamic reconstruction under the impact of specific events. In terms of policy recommendations, for spillover industries, it is crucial to promptly identify potential systemic risk sources to prevent high‐carbon industries from generating transition risks. For risk‐receiving industries, their risk‐mitigating role during market turbulence should be fully utilized. Additionally, attention should be given to the potential risks associated with the transformation of risk roles during extreme events or changes in macroeconomic policies.

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Publication Details

Journal
Journal of Forecasting
Published
2025-12-01
DOI
https://doi.org/10.1002/for.70072
Citations
1
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
3.13
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article

Risk Spillover Network in Commodity Markets Under Climate Transition Risk

Zongling Niu, Yan Wang
1 citations
Journal of Forecasting
Market Dynamics and Volatility
3.13
article

Risk Spillover Network in Commodity Markets Under Climate Transition Risk

Zongling Niu, Yan Wang
article en
1 citations

Abstract

ABSTRACT The article constructs a connectivity network based on the dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) model and spillover index method, systematically revealing the risk contagion effects within China's commodity markets under the context of climate transition. In the long run, the energy and chemical markets act as risk spillover transmitters in the commodity system, while the metal and agricultural markets function as risk receivers. Gold typically passively absorbs risk spillovers from other markets during risk events, presenting a structure of “receiving more and spilling less.” However, in the short term, the risk roles of markets undergo shifts in response to changes in macroeconomic conditions. The risk roles of different markets exhibit significant time‐varying characteristics, and the network structure experiences dynamic reconstruction under the impact of specific events. In terms of policy recommendations, for spillover industries, it is crucial to promptly identify potential systemic risk sources to prevent high‐carbon industries from generating transition risks. For risk‐receiving industries, their risk‐mitigating role during market turbulence should be fully utilized. Additionally, attention should be given to the potential risks associated with the transformation of risk roles during extreme events or changes in macroeconomic policies.

Journal of ForecastingVol. 45(3)
University of International Business and Economics (CN)
Openalex Percentile: Top 6%
Market Dynamics and Volatility
3.13
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Risk Spillover Network in Commodity Markets Under Climate Transition Risk — Zongling Niu, Yan Wang · Journal of Forecasting (2025) | TGRS Research Map | TGRS