收益、波动与投资者情绪的多维网络特征——以中国能源上市公司为例

Returns,Volatility and Investor Sentiment Networks:Evidence from China's Listed Energy Companies

能源行业上市公司作为重要的经济主体,在能源金融一体化深度发展的当下,其股价联动呈现出复杂的网络特征.文章从股票收益、波动与投资者情绪的三维复合视角,构建中国新能源和传统能源上市公司股价关联的最小生成树网络,识别了新冠疫情和双碳政策对中国能源上市公司股价关联网络特征的影响.实证结果表明:1)情绪网络的传导效率最高且易于在两类公司之间传导,收益网络的传导效率最低且易于在同类公司内部传导;2)新冠疫情期间,各类网络传导效率均增加;3)双碳政策后,两类公司间关联减弱,三维网络间相似度提升.文章有助于辅助监管机构监测系统性重要公司、指导投资者结合多维网络特征进行风险管理.

Due to the deepening of the integration of the energy finance sector,listed companies in energy exhibit complex network features in their share price connection as a significant economic entity.This study builds the minimum spanning tree network of stock price correlation between Chinese new energy and traditional energy listed companies from the three-dimensional composite perspective of stock returns,volatility,and investor sentiment.It also demonstrates the impact of the COVID-19as well as carbon peak and carbon neutralization on the characteristics of the stock price related network of energy listed companies in China.The empirical findings demonstrate that:1) The emotional network has the highest transmission efficiency and is the easiest to transmit between different types of businesses,while the income network has the lowest transmission efficiency and is the easiest to transmit within similar companies;2) During the COVID-19,the transmission efficiency of various networks are all increased;3) The link between the two types of businesses deteriorated after carbon peak and carbon neutralization,whereas three-dimensional networks became more comparable.This study can help regulators keep an eye on systemically important businesses and direct investors toward risk management strategies based on multidimensional network properties.