Vulnerability in Bank–Asset Bipartite Network Systems: Evidence from the Chinese Banking Sector

The interdependence inherent in interbank networks amplifies vulnerability to systemic risk, particularly through correlated asset exposures during exogenous negative shocks. This study employs exponential random graph models (ERGMs) to reconstruct a bipartite network of asset-holding correlations based on the balance sheets of Chinese commercial banks from 2016 to 2022. The reconstructed network closely approximates the topological features of the actual banking system. We then introduce a novel framework for measuring aggregate network vulnerability, which incorporates bank size, initial shocks, interconnectedness, leverage, and asset fire sales to capture key channels of financial contagion. Our results indicate that the reconstructed network aligns closely with empirical data in both link structure and weight distribution. Furthermore, cumulative systemic vulnerability increases non-linearly with the severity of the initial shock and the discount depth of fire sales. For individual banks, indirect vulnerability driven by contagion via deleveraging and fire sales significantly exceeds direct losses from initial shocks. Systemic risk contributions are concentrated in large state-owned banks and nationwide joint-stock commercial banks, whereas the institutions most susceptible to risk shocks are predominantly small and medium-sized rural and urban commercial banks.