Abstract: The spatial spillover of hog market price risks increases the complexity of risk management. In-depth analysis of the spillover relationships holds significant theoretical and practical implications for advancing a unified national market. Based on hog price data from 30 provinces (autonomous regions and municipalities) from July 2016 to August 2023, this study first measures hog market risks using the Value at Risk (VaR) and Expected Shortfall (ES) methods. Subsequently, the Time-Varying Parameter Vector Autoregression-based Generalized Forecast Error Variance Decomposition (TVP-VAR-DY) approach is employed to calculate the dynamic spatial spillover indices of risks, and the social network analysis method is utilized to explore the network topology characteristics of the inter-provincial risk spillovers. Empirical results show that the hog market price risk level in China demonstrates an ascending trajectory, with supply-demand imbalances and unexpected event shocks serving as key drivers of risk escalation. The price risk spillover of hog market exhibits pronounced time-varying characteristics and is influenced by hog transportation activities: The dynamic total spillover index following an approximate U-shaped evolutionary pattern synchronized with adjustments in hog transportation policy, while the dynamic directional spillover index and dynamic net spillover index maintaining strong associations with the cross-regional transfer-out and transfer-in behaviors. The price risk spillover network in China’s hog market exhibits a tightly interconnected structure with robust systemic correlations, where major risk spillover regions, such as Heilongjiang, Hubei, and Shandong, occupy central positions within the network topology. Based on these findings, this study proposes the following targeted recommendations: 1) the governmental agencies should optimize the market price risk management framework; 2) the small-to-medium scale hog producers should mitigate hog market price risk; and 3) investors should formulate rational investment strategies.