摘要
以中国商品期货市场流动性较好的45种关键商品日内5分钟高频数据为研究样本,分析商品期货价格波动响应机制,识别关键商品节点的价格波动风险以及商品集群。研究发现,商品的行业聚类特征明显,与传统行业分组相匹配,焦煤所属的能源商品及其下游的黑色商品是核心商品类别,焦煤和玻璃在商品网络中发挥关键作用;网络拓扑结构对商品的系统性金融风险存在显著影响,网络节点中心性和聚类系数较大的关键商品对商品期货市场系统性金融风险具有较大影响。
Based on the time-varying Copula model and minimum spanning tree,a dynamic network of China's commodity futures market is established using the 5-minute intra-day data of 45 major commodities in China's commodity futures market.The systematic risk contribution of commodity nodes and commodity networks are identified.It is found that coking coal and glass play key roles in the network.The clustering characteristics of commodities are obvious,matching with the traditional industry grouping.The energy commodities belonging to coking coal and the black commodities downstream are the core commodity categories.Network topology has a significant impact on the systemic risk of commodities,and key commodities have a great impact to the systemic risk of commodity futures market.
作者
刘曙华
黄轲
LIU Shu-hua;HUANG Ke(Guangxi Academy of Social Sciences,Nanning Guangxi 530022,China;School of Digital Economy,Nanning University,Nanning Guangxi 530004,China)
出处
《技术经济与管理研究》
北大核心
2024年第8期84-89,共6页
Journal of Technical Economics & Management
基金
国家自然科学基金项目(71763004)
广西壮族自治区哲学社会科学规划一般项目(23FYJ026)。