Department of Administrative Sciences, Metropolitan College, Boston University, 1010 Commonwealth Avenue, Boston, MA, 02215, USA.
Center for Polymer Studies and Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, MA, 02215, USA.
Sci Rep. 2021 Feb 8;11(1):3358. doi: 10.1038/s41598-021-82904-y.
We propose a dynamic model for systemic risk using a bipartite network of banks and assets in which the weight of links and node attributes vary over time. Using market data and bank asset holdings, we are able to estimate a single parameter as an indicator of the stability of the financial system. We apply the model to the European sovereign debt crisis and observe that the results closely match real-world events (e.g., the high risk of Greek sovereign bonds and the distress of Greek banks). Our model could become complementary to existing stress tests, incorporating the contribution of interconnectivity of the banks to systemic risk in time-dependent networks. Additionally, we propose an institutional systemic importance ranking, BankRank, for the financial institutions analyzed in this study to assess the contribution of individual banks to the overall systemic risk.
我们提出了一个使用银行和资产的双边网络的系统风险动态模型，其中链接的权重和节点属性随时间变化。利用市场数据和银行资产持有量，我们能够估计一个单一的参数作为金融体系稳定性的指标。我们将模型应用于欧洲主权债务危机，并观察到结果与实际事件非常吻合（例如，希腊主权债券的高风险和希腊银行的困境）。我们的模型可以与现有的压力测试互补，将银行之间的互联性对时变网络中系统风险的贡献纳入其中。此外，我们为这项研究中分析的金融机构提出了一个机构系统重要性排名，BankRank，以评估单个银行对整体系统风险的贡献。
