Sentiment-Driven Risk Contagion: An Emotionally Enhanced TENET Analysis of China’s Stock Market

This study investigates how investor sentiment magnifies inter-industry risk spillovers across 18 industrial sectors in the Chinese stock market. We propose a sentiment-enhanced framework that integrates the ΔCoVaR approach with the tail-event driven network (TENET) model to construct a directed, weighted risk contagion network. Utilizing weekly data from 2015 to 2024—a period encompassing multiple systemic crises—our empirical analysis yields four key findings. First, incorporating investor sentiment universally improves the model’s explanatory power for tail risk spillovers, with capital-intensive sectors such as Mining and Real Estate exhibiting the highest sensitivity. Second, we identify a robust bilateral feedback loop between investor sentiment and sectoral risk, driving a self-reinforcing cycle of financial instability. Third, among various transmission mechanisms, the capital flow channel exerts the dominant moderating effect, transforming highly liquid sectors into critical risk-transmission hubs. Finally, this sentiment-driven amplification is highly asymmetric, spiking dramatically during extreme market events such as the 2015 stock market crash and the COVID-19 pandemic. These findings provide actionable empirical evidence for policymakers to design sentiment-integrated early-warning systems and targeted macro-prudential interventions to mitigate systemic risk.