| Liquidity is the basic guarantee for the normal operation of commercial banks.Liquidity risk is also the most complicated and deadly risk in the operation of commercial banks.It plays an important role in bank failures and financial crisis.As a result,liquidity risk management has always played an important role in the history of banking and banking supervision.The existing researches on the liquidity risk of commercial banks are mainly studied by representative banks or individual banks,and there is little research on the liquidity risk of the banking system.The banking system liquidity risk refers to multiple banks are unable to borrow from the short-term funding markets or obtain a new short-term funding difficulties occurring in the course of risk,influence scope is greater than a single bank liquidity risk.Therefore,the research on the system liquidity risk is of great theoretical and practical significance.In this article,China’s listed commercial banks are regarded as a system.Based on the research on the liquidity risk of individual banks,this article selects the listed commercial banks in China as the research object,and emphasizes the research on the liquidity risk of the banking system.The article focuses on the following work: Firstly,the existing relevant literatures at home and abroad are reviewed.Secondly,based on the calculation of the net stable financing ratio of listed commercial banks in China,the model is established to calculate the liquidity risk of China’s listed commercial banking system.Thirdly,the network model is used to study the transmission structure of the liquidity risk in the bank.Fourthly,on the basis of combing the financial crisis and the banking sector in China in 2013,this paper empirically studies the transmission of liquidity risk of the listed commercial banks in China outside the banking system.The main conclusions include:Firstly,the general observation on liquidity of listed commercial banks in China.(a)The overall level of liquidity in China’s banking sector has continued to decline.In 2011,the overall level of liquidity of listed commercial banks in China was higher.Except for the net stable financing ratio of bank of Ning bo,only industrial bank,Ping an bank and Nan jing bank have a net stable financing ratio of less than 1.The net stable financing ratios of the remaining 12 listed commercial banks are all greater than 1.In 2016,only CCB,agricultural bank,industrial and commercial bank of China,bank of China,bank of communications and China merchants bank,the net stable financing ratio of the six listed commercial banks was greater than 1.The remaining 10 listed commercial banks have a net stable financing ratio of less than 1.The above data reflects the challenges to long-term financing stability of most listed commercial banks in China.From 2011 to 2016,from China’s listed commercial banks net stable funding ratio of the mean,the average net stable funding ratio of Shanghai pudong development bank,Ping an bank,everbright bank,industrial bank,Nanjing bank and Ning bo bank are less than 1.It is clear that these banks’ long-term stable assets will not fully cover their long-term liabilities.(b)There are significant differences in liquidity of different types of listed commercial banks in China.The long-term financing stability of listed state-owned commercial banks is higher than that of other listed commercial banks.From 2011 to 2016,the net stable financing ratio of listed state-owned commercial banks has gradually declined,but they are all greater than 1.The net stable financing ratio of listed joint-stock commercial banks has decreased from less than 1,2016 to below 0.95 in 2015.The net stable financing ratio of listed city commercial banks has been less than 1 for 4 consecutive years since 2013.Shows that the long-term and stable assets of the listed state-owned commercial banks can be completely cover its long-term debt,listed listed city commercial banks and joint-stock commercial banks assets is difficult to completely cover the long-term stability of the long-term debt.From 2012 to 2016,the annual growth rate of the net stable financing ratio of China’s listed commercial banks is negative.Compared with the listed state-owned commercial banks and listed city commercial banks,the net stable financing ratio of the listed joint-stock commercial banks has declined on average.In addition,the decline in the net stable financing ratio of listed joint-stock commercial banks has been increasing since 2013.The net stable financing ratio of listed city commercial banks fell far more sharply in 2013 than in the net stable financing ratio of other banks from 2011 to 2016.The net stable financing ratio of listed city commercial banks fell far more in 2015 than the net stable financing ratio of other listed commercial banks in the same period.Secondly,SRL model can be used as a tool to measure the liquidity risk of China’s listed commercial banking system.Jobst(2014)established SRL model to measure the system liquidity risk of listed commercial Banks in the United States by using option pricing theory,combined with bank balance sheet information and securities market information.The empirical results show that SRL model is a good measure of the systemic liquidity risk of listed commercial Banks in the United States,and indicates that the SRL model can be used as a tool to measure the liquidity risk of the banking system.Based on Jobst(2014),this paper combines the Copula function with the SRL model to calculate the risk value of the one-year potential loss of Chinese listed commercial banks under the scenario of long-term extreme pressure.At the same time,it calculates the risk value of the overall expected loss of all listed commercial banks in the context of continuous extreme pressure.The empirical results show that the liquidity risk of China’s listed commercial Banks shows a strong fluctuation in the second half of 2012.It was not until early May 2013 that the maximum of the sample area was reached,just before the outbreak of periodic liquidity crisis in China’s banking sector in 2013.It shows that SRL model is a good measure of liquidity risk in China’s banking system.Thirdly,the network structure of liquidity risk in China’s listed commercial banking system.Based on the SVAR network model based on DAG,this paper conducts an empirical study on the network structure of the liquidity risk of China’s listed commercial banking system and draws the following conclusions:(a)The net effect of liquidity risk of listed commercial banks.The net effect of the all of China’s listed commercial Banks liquidity risk from big to small order are: China merchants bank,bank of Beijing,Ning bo bank,Hua xia bank,everbright bank,Nan jing bank,industrial and commercial bank,construction bank,agricultural bank,industrial bank,China bank,Min sheng bank,bank of communications,Shanghai pudong development bank,China citic bank.Among them,the net effect of the eight banks before the construction bank is positive,and the net effect of the ranking in the construction bank and the subsequent eight banks is negative.(b)The listed city commercial banks have relatively large influence on the liquidity risk of other listed commercial banks.According to the nature of the banks,the net effect of Chinese city commercial banks on the liquidity risk of other listed commercial banks is far greater than that of state-owned commercial banks and joint-stock commercial banks.The net effect of liquidity risk on state-owned commercial banks is minimal.China’s joint-stock commercial banks are more vulnerable to the liquidity risk of other commercial banks from the impact of other banks.From the influence of other banks,the impact of China’s urban commercial banks on other banks is greater than that of state-owned commercial banks and joint-stock commercial banks combined with other banks.The liquidity risk of state-owned commercial banks has minimal impact on other commercial banks.From the average asset size of various listed commercial banks,the liquidity risk of the state-owned commercial banks with the largest average assets has the least impact on the liquidity risk of other listed commercial banks.The liquidity risk of the listed city commercial banks with the smallest average assets has the greatest impact on the liquidity risk of other listed commercial banks.On average,the listed joint-stock commercial banks with average asset size are centered on the liquidity risk of other listed commercial banks.Therefore,it is not difficult to find that the average asset size of the three listed commercial banks in China is negatively correlated with the impact on liquidity risk of other listed commercial banks.(c)The network structure of liquidity risk of listed state-owned commercial banks.Considering the large scale of state-owned commercial banks’ assets in listed commercial banks in China,this paper further explores the network structure of liquidity risk among listed state-owned commercial banks.The empirical results show that icbc,construction bank and bank of communications have great influence on liquidity risk of other listed state-owned commercial banks.Bank of communications is affected by the liquidity risk of other listed stateowned commercial banks.Comparing the state-owned commercial bank’s assets in state-owned commercial banks with liquidity risk in the network performance,the state-owned assets of commercial banks and state-owned commercial banks to impact on the rest of the state-owned commercial banks liquidity risk are positively correlated.Fourthly,empirical study on the liquidity risk of China’s listed commercial banking system.Based on the transmission channels of the banking system liquidity risk and the study of the liquidity risk development process,to establish the VAR model to measure the dynamic transmission among the money supply,real estate prices,securities market,the banking system liquidity risk and macroeconomic.The conclusions are as follows:(a)The dynamic impact of money supply on liquidity risk in the banking system.As the source of social mobility,money supply directly affects the system liquidity of Banks,so there exists the influence of money supply on the liquidity risk of the banking system.Therefore,this paper introduces the monetary supply into the empirical research on the transmission of liquidity risk in the banking system.The variance decomposition results of VAR model show that the money supply has a significant influence on the liquidity risk of the banking system.The result of impulse response shows that although the increase of money supply can temporarily reduce the liquidity risk of Banks,there is a lag risk accumulation.The liquidity risk of the banking system has declined significantly in the period of lag of the positive impact of the money supply.The positive impact of money supply lag phase 3,the banking system liquidity risk increased significantly,and increase the amplitude of two times more than the money supply to increase caused by the decline in the banking system liquidity risk.To sum up,the increase of money supply can temporarily alleviate the liquidity shortage in the banking system,but accumulate more risks.(b)The dynamic impact of the real estate market and the securities market on the liquidity risk of the banking system.According to the logical analysis of this paper,it can be seen that: 1.The decline of real estate price and the decline of stock market price will lead to the increase of liquidity risk in the banking system.2.The increase of liquidity risk in the banking system led to the decline in the expectation of the bank,which in turn led to the decline of bank stock prices,which led to the decline of stock prices.3.Increased liquidity risk in the banking system leads to increased demand for liquidity in the market.Higher liquidity requirements have led to lower prices for illiquid real estate assets.The prediction variance decomposition and impulse response function of VAR model basically confirm the first two logic analysis,but the impulse response result is inconsistent with the third logical analysis.The empirical results show that the increase of liquidity risk in the banking system causes the real estate price to rise rather than decrease.The possible explanation for this phenomenon is that it has to do with the fact that real estate is still regarded as a safe asset in China.That is,when the liquidity risk of the banking system increases,the demand for safe assets rises in the market,and the rise in demand leads to the rise in the real estate price as a safe asset.This paper argues that the phenomenon of empirical results contradicts the results of the third logical analysis,which deserves the vigilance and in-depth study of relevant departments and researchers.(c)The dynamic impact of the macro economy and the liquidity risk of the banking system.The variance decomposition results of VAR model show that there is a significant influence on the liquidity risk of the banking system.The result of impulse response indicates that the positive shock of macro economy increases the liquidity risk of the banking system significantly.It indicates that the liquidity risk of the banking system is pro-cyclical,that is,the liquidity risk of the banking system increases with the prosperity of the macro economy.The positive impact of the liquidity risk of the banking system makes the macro economy generally lower and then rise,and the decline is greater than the increase.It indicates that the increase of liquidity risk in the banking system can cause the macroeconomic decline.Fifthly,policy suggestions.In this paper,based on the banking system liquidity risk measure and the conduction of research results,respectively from the following three aspects to guard against the advice of the banking system liquidity risk:(1)the construction of the banking system liquidity risk measure;(2)strengthen the risk supervision of banks with large influence on the liquidity risk network and prevent the internal transmission of liquidity risk of the banking system;(3)strengthen the supervision of external shocks that affect the liquidity risk of the banking system and prevent the external transmission of the liquidity risk of the banking system.Sixthly,innovation points of this paper.The main innovation points of this paper are embodied in the following four aspects:Firstly,through the analysis of the liquidity risk transmission of the banking system,the transmission path of the liquidity risk in the banking system and the outside of the banking system is given.Secondly,combining with the high-dimensional dynamic Copula function and SRL model,the liquidity risk of China’s listed commercial banking system is calculated.Thirdly,the network model is used to depict the liquidity risk network structure of all listed commercial Banks in China,reflecting the role of various banks in the liquidity risk network of the banking system.Fourthly,empirical research on the dynamic impact of liquidity risk and money supply,real estate market price,securities market price and China macro economy in China’s banking system. |
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