Analysis Of The Stability Of China's Financial System Based On The Financial Network Method

Systemic financial risk is not only related to external economic environment,but also closely related to the internal structure of the financial system.It is not advisable to consider only external macroeconomic factors but not the pro-cyclical and contagious nature of the financial system.There are obstacles in using representative financial institution method to simulate the interaction between finance and economy in traditional economic methods,that is,the transmission process of financial risks among financial institutions cannot be depicted.One unavoidable question is: since every financial institution meets regulatory requirements beforehand,why does the combined financial system experience periodic crises? In order to describe and analyze this contagion process,this paper describes the mechanism and process of financial risk transmission among heterogeneous institutions from the perspective of systematic theory using financial network method.As we all know,network method is a natural way to describe heterogeneity and transmission mechanism.The interconnection between financial institutions may come from either the asset side(holding the same type of assets)or the liability side(interbank lending market).In the second chapter of this paper,the loan and non-loan assets held in the listed bank statements are mapped into 16 industries to form the so-called generalized credit sub-industry data.Thereafter,this paper generates nine generalized credit asset bipartite networks of listed commercial banks covering from 2013 to 2017 semiannually,with every network constituted by 38(listed banks)multipled by 16(asset)nodes.By introducing external shock variable and network contagion parameter(referring to the DBNM-BA model),the author finds that the network stability due to most asset shocks,such as manufacturing and real estate industries is improving,but the network sensitivity to personal housing loans,finance,leasing and business services industries is also increasing.From this point of view,in order to reduce the contagion effect of systemic financial risks,it is imperative to control the growth of personal housing loans etc.It should be noted that in order to simplify the difficulty of analysis,the default condition of a single financial institution is insolvency.The network effect is reflected in the fact that once an institution defaults,the assets it holds will be sold in the secondary market,which will lead to the corresponding asset prices falling,and the decline of asset prices will lead to more institutions facing bankruptcy risk.Therefore,in essence,in the above asset-institution bipartite network model,the transmission and amplification of systemic risks among financial institutions depend on the asset side interconnection of financial institutions and the herding behavior of them.Of course,the starting point of describing systemic risk with the above-mentioned model is to use balance sheet data.Describing systemic risk by using balance sheet data has shortcomings,such as weak timeliness and lack of forward-looking.The interconnections between financial institutions are not limited to balance sheets,financial markets are also important channels of contagion.For this reason,the third,fourth and fifth chapters of this paper generate systemic risk indicators SRISK and Net-SRISK,which represent the capital gap of the whole banking industry,taking stock market fluctuations into consideration.The so-called SRISK measures how big the capital gap in the banking sector is when the Shanghai Composite Index falls by 10% in less than a month,compared with the minimum regulatory requirement(8% capital adequacy ratio).The reasons for choosing SRISK is that firstly,SRISK satisfies additivity compared with other common used measures of systemic risk,such as CoVaR.Secondly,there is no mature CDS market in China,so it is difficult to use DIP and SCCA methods directly.Therefore,the author believes that SRISK is more appropriate than CoVaR etc.In the third chapter of this paper,the calculation of SRISK and other systemic risk measures are introducted and analyzed for reference only.Thereafter,in order to distinguish the sources of the capital gap measured by SRISK,the fourth and fifth chapters of this paper introduce the partial correlation network to further explore.Specifically,the fourth chapter mainly examines the partial correlation network between the share prices of A-share listed banks and CITIC I non-financial industries,and the topological statistical characteristics of the partial correlation network between the share prices of A-share listed banks and the Shanghai Composite Index;the fifth chapter calculates the Net-SRISK based on the partial correlation coefficients.The results show that the large fluctuations of SRISK can be reflected in the statistical characteristics of the partial correlation network.The introduction of partial correlation coefficients reduces the value of(aggregated)SRISK,but does not significantly affect the trend and turning points.In other words,since Net-SRISK measures the capital gap caused only by single factor of the Shanghai Composite Index,the partial correlation between the Shanghai Composite Index and the fluctuation of bank stock prices can determine the general trend of SRISK.The interaction between banks will only magnify the size of SRISK,but will not affect the trend of SRISK.This conclusion actually tells us that SRISK can be divided into two parts: Net-SRISK and nonNet-SRISK.Among them,non-Net-SRISK can represent the systemic risk brought by inter-bank linkages(partial correlation),although the linkages are not completely consistent with the balance sheet-based linkages.In summary,by combing relevant research methods and conclusions at home and abroad,this paper generates three financial networks and analyzes the stability of domestic listed banks from two perspectives of joint-holding asset model and stock market risk spillover.Compared with the existing literature,this paper is close to China's macro-financial background reality(by introducting the influence of China's shadow banking system)and has some innovations in the network generation rules(partial correlation network).The shortcomings of this paper are as follows: it only considers the situation of listed banks,but does not consider non-listed banks;it only considers the spread,transmission and contagion process of exogenous financial risks in the listed banking system but does not establish a logical and unified economy-finance interaction framework;thirdly,the partial correlation networks are sometimes not well understood.Therefore,it should be pointed out that this paper is only a preliminary attempt to apply financial network analysis to the measurement of systemic risk in China's financial system.There are still many pending issues in the following aspects,such as the construction of endogenous and semiendogenous network models,the acquisition of relevant data and empirical testing.Due to limited space,the author will continue relevant work in the follow-up study.