Research On The Structure And Stability Of Interbank Borrowing Network In China

Banks in the banking system form a complex network.As the network structure of banks provides a channel for risk communication,this paper studies the complex network structure of China's banking system and identifies the important nodes of network.It is necessary to further analyze the stability of China's banking network.This article introduces the definition of network,type of network,degree,betweenness,clustering coefficient,centrality and k-core.The above is a theoretical preparation for the empirical analysis of the structure of China's interbank borrowing network.Based on this,we conduct visual analysis of China's interbank borrowing network from 2014 to 2016.Firstly,according to the Bank Focus database,the sample bank is screened,the data selection basis is introduced,and the descriptive statistics are made.Then,the entropy optimization,the matrix method and the threshold method are used to construct the borrowing matrix that meets the actual conditions;Finally,PAJEK software is used to make a visual analysis of the 2014-2016 China's interbank borrowing network model.The analysis shows that a small number of important nodes bear most of the responsibility for interbank borrowing.Most city commercial banks,rural commercial banks and foreign-funded banks show less weight in the sidelines.This shows that China's interbank borrowing network has a high concentration of capital flows.Based on this,this article makes structure analysis of the borrowing network to identify important nodes.On the one hand,the empirical results show that the status of different banks in the network is not static.Some banks with a small proportion of capital flows have higher betweenness and can still be classified as important nodes.On the other hand,it indicates that our country's interbank borrowing network has a higher average clustering coefficient,that is,the banking network group adjacent to the bank has relatively complete connectivity.K-core analysis shows that banks with higher degree of nodes are aggregated into sub-clusters,and the nodes are highly correlated with each other.In the case of a risk event,it is highly probable that the largest k-core group will spread risk to other k-core groups.Finally,we conduct stability analysis of China's interbank borrowing network.Some nodes are selectively deleted in this paper to analyze the changeof the number of nodes included in the largest connected sub-network,to describe the stability of the interbank borrowing network.The empirical results show that the banks in China's interbank borrowing network have serious inhomogeneity.The influence of a few important nodes on network stability is much higher than that of most nodes.In 2016,the imbalance among banks was eased.