Extreme volatility risk dynamic diffusion in financial market based on a new VEBN framework

Understanding how volatility risk spreads during financial crises is vital for market stability and effective risk management. We introduce the Volatility Entropy-based Network (VEBN), a new framework that quantifies volatility risk diffusion using weighted network statistics. Applying this method to the Chinese stock market, we reveal the asymmetry of risk diffusion across industries and explore the changes of risky industries under different types of extreme events. Notably, internal industry linkages drive risk transmission more strongly than external shocks, and extreme events intensify this effect while promoting inter-industry cooperation. These findings suggest that risk managers and regulators should focus on monitoring industry interconnections and adapt risk controls dynamically during periods of heightened volatility. Robustness checks with stochastic volatility and GARCH models confirm our results. Our work offers a novel quantitative tool for analyzing and mitigating systemic risk in complex financial networks.