Research On Systemic Financial Risk Based On Cross-shareholding Network

The National Fourteenth Five-Year Plan clearly proposed to accelerate the construction of a new development pattern,continue to deepen the reform of financial supply,focus on improving the qual-ity and efficiency of financial services in the real economy,effectively prevent and resolve systemic financial risks,and make effort to ensure economic and financial security and stable development.However,in recent years,extreme weather phenomena have surged,and climate change has caused economic losses and related financial risks.Among that,the value of energy industry assets is most sensitive to the transition risks brought about by climate change.On the one hand,the rising pro-duction costs of energy companies will affect many affiliated companies,at the same time,a large number of financial institutions have equity connections with energy companies and their affiliated enterprises,so financial institutions may face risk losses.On the other hand,the innovative develop-ment of the energy industry and the promotion of new energy research and development will reduce the value of traditional energy assets,so that the assets and liabilities of financial institutions associ-ated with energy companies may be out of balance.This means that when there is a cross shareholding relationship between energy companies and financial institutions,there is a risk contagion mechanism between the real economy and the financial system,and the related risks caused by climate change may be amplified in the complex cross correlation,resulting in a systematic impact on the entire fi-nancial system.Therefore,this article studies the systemic financial risks of the cross-shareholding relationship between energy companies and financial institutions,so as to provide theoretical and practical references for maintaining the stability of China financial system.This article started from the perspective of equity associations between listed companies and financial institutions in China energy industry,and used complex network theory to construct a cross-shareholding network between listed energy companies and financial institutions.Furthermore,based on the cross-shareholding network,combined with the debt level algorithm,a systemic risk measure-ment model was constructed,and with the help of numerical simulation,the systemic financial risk contribution of the nodes in the cross-shareholding network was analyzed with the change of exoge-nous pressure level.Finally,by setting up a multiple regression model and using panel data,this paper empirically tested the influencing factors of systemic financial risk based on cross shareholding network.Based on the data of cross shareholding between energy companies and shareholders of finan-cial institutions from June 2012 to June 2019,the results show that: first,the cross-shareholding network had a scale-free feature and presented a high degree of complexity: on the one hand,the cross-shareholding network presented dynamic changes,and different indicators at different time points had different performance characteristics,which required specific analysis at specific time?on the other hand,a small number of nodes were located in the central position,the ranking of de-gree,betweenness centrality,closeness centrality and eigenvector centrality of these nodes are in the front row.Such nodes were core nodes in the network and were extremely important for the stable of the network system.Second,debtrank of the energy company nodes at the financial institution level were relatively high,and debtrank of the financial institution nodes at the energy company level were relatively high? total debtrank of the financial institution nodes were generally higher than that of the energy company nodes.In addition,under the same pressure level,there were a small num-ber of nodes in the network that suffer large risk losses.Once these nodes fell into bankruptcy,they would seriously threaten the overall stability of the system? changes in the pressure level caused nodes to suffer different degrees of risk losses.And the node risk loss was closely related to the network topology index and asset scale.Finally,the node’s asset status and network structure indicators had a significant impact on the debtank.Among them,the node’s net assets and degree indicators were more stable,and both were positively correlated with the node’s debtrank.