Systemic financial risk continues to pose a serious challenge for modern economies, as shown by repeated crises such as the global financial collapse of 2008, the Chinese stock market turmoil of 2015, and the economic disruption caused by the COVID-19 pandemic. Much existing research has tended to analyse financial sectors separately or to focus on simple pairwise spillovers between them. While useful, these approaches often miss the broader picture of how risks can simultaneously spread across industries, reinforcing one another and escalating into systemic threats. This study responds to that limitation by examining how collective risk emerges through multi-sector interactions in China’s stock market.

Rather than relying on conventional two-sector models, the research focuses on higher-order interactions in which risk is shared across groups of sectors simultaneously. This perspective recognises that financial instability is rarely transmitted in a linear or isolated way. Instead, shocks often propagate through tightly connected clusters of sectors whose risks move together. By capturing these group-level dynamics, the study offers a richer and more realistic account of how systemic risk develops and evolves, particularly during periods of market stress.

To achieve this, the authors analyse data from 24 Chinese stock market sectors covering the period from 2007 to 2024. Sectoral risk is measured using volatility estimates derived from established econometric models. In contrast, a higher-order network framework is used to track how risk co-movement forms and dissolves over time. In this network, links are not limited to pairs of sectors but can connect several sectors simultaneously, allowing the identification of synchronised risk “resonance” across the market. Network indicators are then used to assess both the importance of individual industries and the overall system structure.

The results show that the most common form of risk interaction involves four sectors moving together, indicating that traditional pairwise analyses significantly underestimate the complexity of risk transmission. The findings also reveal significant differences between industries. Insurance consistently plays a central role in the risk network, while energy becomes especially influential during periods of geopolitical tension. Significantly, the composition of high-risk clusters changes from one crisis to another, demonstrating that systemic vulnerability is not fixed but shaped by the nature of external shocks.

At the system level, the market’s ability to absorb shocks improves gradually over the long term, suggesting some strengthening of financial resilience. However, this resilience fluctuates sharply during crises, when network structures reorganise, and risk becomes more concentrated. Financial sectors tend to cope better with shocks, whereas industries such as retail and capital goods remain relatively fragile. Major events are shown to reshape network density and connectivity, confirming that crises fundamentally alter how risk spreads across the market.

Overall, the study highlights the importance of moving beyond traditional risk models to understand modern financial systems. By revealing how collective, multi-sector risk can build up and propagate, it offers valuable insights for regulators, investors, and risk managers. The approach provides a clearer basis for monitoring systemic threats, designing more effective safeguards, and anticipating hidden vulnerabilities in increasingly interconnected financial markets.

More information: Zisheng Ouyang et al, Collective risk resonance behavior and network resilience in Chinese stock sectors: evidence from higher-order financial network, China Finance Review International. DOI: 10.1108/CFRI-06-2025-0394

Journal information: China Finance Review International Provided by Shanghai Jiao Tong University Journal Center