Risk Spillover Network in Commodity Markets Under Climate Transition Risk

IF 2.6 3区 经济学 Q1 ECONOMICS
Journal of Forecasting Pub Date : 2026-03-03 Epub Date: 2025-12-01 DOI:10.1002/for.70072
Zhihong Niu, Yan Wang
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引用次数: 0

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.

气候转型风险下商品市场的风险溢出网络
本文基于动态条件相关广义自回归条件异方差(DCC-GARCH)模型和溢出指数方法构建了连通性网络,系统揭示了气候变化背景下中国商品市场的风险传染效应。从长期来看,能源和化学市场在商品系统中充当风险外溢的传递者,而金属和农产品市场则充当风险的接收者。在风险事件中,黄金通常被动地吸收来自其他市场的风险溢出,呈现出一种“接收多、溢出少”的结构。然而,在短期内,市场的风险角色会随着宏观经济条件的变化而发生变化。不同市场的风险角色表现出显著的时变特征,网络结构在特定事件的影响下经历动态重构。在政策建议方面,对于外溢产业,应及时识别潜在的系统性风险源,防止高碳产业产生转型风险。对于接受风险的行业,应充分发挥其在市场动荡中的风险缓解作用。此外,应注意在极端事件或宏观经济政策变化期间与风险作用转变有关的潜在风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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