Collective risk resonance behavior and network resilience in Chinese stock sectors: evidence from higher-order financial network

Purpose We investigate latent higher-order dependencies in Chinese sectoral risk connectedness networks, characterize their topology and quantify resilience at both the system and sector levels, thereby offering new insights for mitigating systemic risk and preserving financial stability. Design/methodology/approach Employing the RHOSTS approach, we construct higher-order risk connectedness networks for Chinese stock sectors and analyze their structure with network-topology metrics. These metrics are then embedded in a coupled-map-lattice model to track the time-varying resilience of the overall network and its constituent sectors. Findings The sectoral network exhibits pronounced higher-order interactions, with four-sector synchronous resonance as the prevailing motif. Shock-specific core resonance clusters emerge and although system-wide resilience increases over time, marked heterogeneity across sectors persists. Originality/value By moving beyond traditional pairwise spillover models, our higher-order financial network reveals collective risk resonance spanning multiple sectors. The topology-based metrics we propose enable simultaneous assessment of system-level and sector-specific resilience and its evolution.