From fossil fuels to renewables: Analyzing network effects and market responses during China's energy transition

The Chinese energy market is undergoing a critical evolutionary phase driven by carbon neutrality objectives and structural reforms, resulting in fundamental transformations of market operations and pricing mechanisms that may amplify systemic complexity. This study investigates the network structures and intrinsic interactions among Chinese energy firms and their impact on stock return dynamics. Utilizing publicly traded data from 191 listed energy firms spanning both conventional and renewable energy sectors, we construct a high- dimensional network and employ a dynamic network quantile regression (DNQR) model to assess how relevance networks influence energy returns under varying market conditions. Our analysis yields three principal findings: (1) The energy market demonstrates strong interconnectedness with distinct clustering patterns aligned with industry segmentation, where gas emerges as a critical nexus bridging coal and petroleum sectors. (2) Public utilities, particularly electricity and gas, exhibit substantial systemic importance, while traditional thermal power generation maintains significant influence, highlighting the urgent need for renewable energy advancement. (3) Contemporaneous network effects display tail behavior and exert a robust positive influence on energy stock returns, with particularly pronounced effects during periods of market stability and prosperity. These findings offer valuable insights into price formation mechanisms and market performance during stages of China’s energy policy transition.