Early Warning of Systemic Risk in Commodity Markets Based on Transfer Entropy Networks: Evidence from China

被引:2
作者
Zhao, Yiran [1 ]
Gao, Xiangyun [1 ,2 ]
Wei, Hongyu [1 ]
Sun, Xiaotian [1 ]
An, Sufang [3 ]
机构
[1] China Univ Geosci, Sch Econ & Management, Beijing 100083, Peoples R China
[2] Minist Nat Resources, Key Lab Carrying Capac Assessment Resource & Envir, Beijing 100083, Peoples R China
[3] Hebei GEO Univ, Sch Management, Shijiazhuang 050031, Peoples R China
基金
中国国家自然科学基金;
关键词
transfer entropy; causality networks; risk contagion; early warning; commodity markets; CRUDE-OIL MARKET; INFORMATION; VOLATILITY; SPILLOVER; ENERGY; INTERCONNECTEDNESS; CONNECTEDNESS; DEPENDENCE; DIVERSIFY; DYNAMICS;
D O I
10.3390/e26070549
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
This study aims to employ a causal network model based on transfer entropy for the early warning of systemic risk in commodity markets. We analyzed the dynamic causal relationships of prices for 25 commodities related to China (including futures and spot prices of energy, industrial metals, precious metals, and agricultural products), validating the effect of the causal network structure among commodity markets on systemic risk. Our research results identified commodities and categories playing significant roles, revealing that industry and precious metal markets possess stronger market information transmission capabilities, with price fluctuations impacting a broader range and with greater force on other commodity markets. Under the influence of different types of crisis events, such as economic crises and the Russia-Ukraine conflict, the causal network structure among commodity markets exhibited distinct characteristics. The results of the effect of external shocks to the causal network structure of commodity markets on the entropy of systemic risk suggest that network structure indicators can warn of systemic risk. This article can assist investors and policymakers in managing systemic risk to avoid unexpected losses.
引用
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页数:18
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