Abstract: Analysis and research on interbank market based on multi-layer network structure is conducive to avoiding or weakening the risk impact on financial market. Based on test data simulated by credit lending business scenario, combined with the multi-layer network structure and complex network analysis method of interbank market, the important nodes in interbank market were judged and identified from different angles, meanwhile Jaccard similarity coefficient between the layers and inter-institution Pearson similarity coefficient were calculated and the infectousness of risk contagion of interbank market was measured from macroscopic and microscopic perspectives. The experimental results show that large-scale state-owned financial institutions such as Bank of China and China Development Bank are of high importance in the system, and the greater the similarity between institutions, the greater the infectiousness of risk contagion. Therefore, by calculating the important node measure index in the network layer, comprehensive and complete analysis of the risk contagion of the entire system can help the regulators to achieve accurate monitoring of important institutions in the system. At the same time, from the perspectives of inter-layer analysis and intra-layer analysis, comprehensive measurement of the infectious degree of risk contagion between institutions after financial shock provides policy advice to regulators.

Key words: interbank market, risk contagion, complex network, network embedding

摘要： 基于多层网络结构对银行间市场进行分析研究，有利于规避或减弱对金融市场的风险冲击。基于信用拆借业务场景模拟的测试数据，结合银行间市场多层网络结构和复杂网络分析方法，从不同角度对银行间市场中重要节点进行判断识别，同时计算层间的Jaccard相似系数数和机构间皮尔逊相似性系数，从宏观和微观角度来衡量银行间市场的风险传染性。实验结果表明，中国银行、国家开发银行等大型国有金融机构系统重要性较高，且机构间的相似度越大，风险传染性就越大。因此，通过计算网络层内的重要性节点衡量指标，全面完整地对整个系统的风险传染情况进行分析，可协助监管部门实现对系统重要性机构的精准监测。同时，从层间分析与层内分析两个角度出发，全面衡量受到金融冲击后的机构间风险传染程度，可为监管机构提供政策上的建议。

关键词: 银行间市场, 风险传染, 复杂网络, 网络嵌入