We develop a network-based probabilistic model to analyze systemic risk within a network of interconnected institutions. Harnessing the power of economic connections, we construct a weighted network that effectively captures the extent of direct risk spillovers. Then the risk contagion probabilistic model is constructed with the aid of the risk orbit contagion idea and inter-institutional dependencies. Our model examines contagion characteristics, uncertainty, and interdependence, revealing that neither a ring nor a complete financial network is optimal. We discover that the expected loss of the network does not have a monotonic relationship with the number of partners, depending on the trade-off between the network density and direct risk spillovers to mitigate systemic risk.

我们开发了一种基于网络的概率模型来分析互连机构网络内的系统性风险。利用经济联系的力量，我们构建了一个加权网络，可以有效地捕捉直接风险溢出的程度。然后借助风险轨道传染思想和机构间依赖关系构建风险传染概率模型。我们的模型研究了传染特征、不确定性和相互依赖性，揭示了环和完整的金融网络都不是最优的。我们发现网络的预期损失与合作伙伴的数量并不具有单调关系，取决于网络密度和降低系统性风险的直接风险溢出之间的权衡。