Dynamic network of commodity futures market and systemic risk contribution of key commodities

Abstract

Based on the time-varying Copula model and Minimum Spanning Tree (MST), a dynamic network of China’s commodity futures market is established by using the 5-minute intraday data of 47 major commodities in China’s commodity futures market. The systematic risk contribution of commodity nodes, the time-varying characteristics of commodity clusters and commodity networks are identified. According to study, it is found that coking coal (JM) and glass (FG) play key roles in the network. The clustering characteristics of commodities are distinct, which matching with the traditional industry grouping. The coking coal belongs to energy commodities, and the black commodities downstream are the core commodity categories. Network topology has a significant impact on the systemic risk, and key commodities also have great contributions to the systemic risk of commodity futures market. After the regulation implemented in May 2021, which measures of the price inflation of commodity futures, the correlation of the structure in futures market has changed significantly. The results of this paper provide new insights in studying the impact of management regulation regarding market correlation structure, and risk management of commodity portfolio during commodity price boom.