Research On Optimization Of Liquidity Risk Measurement Method Of A Village Bank Based On SVAR Model

In recent years,affected by the development and innovation of financial technology,the introduction of new regulations on asset management and other policies,as well as the impact of the epidemic,the differences between commercial banks in their business model,asset liability structure and scale have gradually emerged,the bank operation ecology has become more and more complex,and financial risk events have occurred frequently.In 2021,due to the liquidity crisis of the subcontractor bank once rated as the "best urban commercial bank",it was finally declared bankrupt,resulting in the liquidity risk of small and medium-sized banks receiving much attention.How to monitor the liquidity level of banks and strengthen liquidity management has always been the focus of analysis and research of the banking industry and scholars.Generally,before the liquidity crisis occurs,the corresponding indicators will be reflected.Therefore,by monitoring the indicators,risks can be found and intervened in advance.Liquidity risk stress test helps banks to manage liquidity risk in advance and measure the maximum potential risk of banks in extreme situations.However,at present,the application of banks,especially small and medium-sized banks,in this regard is too simple to achieve the effect.This paper takes A village bank as an example and optimizes liquidity risk measurement methods of A village bank from the perspective of risk identification and measurement based on relevant data from the first quarter of2013 to the second quarter of 2021,so as to improve liquidity risk management and resistance of banks.Firstly,this paper introduces the basic situation of village bank a,then selects seven indicators to describe the liquidity risk of village bank a in recent five years,and introduces the four liquidity risk measurement methods currently used by village bank a and their shortcomings,Then optimize the liquidity risk stress test.Optimized for the specific content of the liquidity ratio as a measure of the liquidity situation from macro to micro level selected six indicators as the influencing factors of liquidity risk index,conduction model is established by multivariate linear model,then SVAR model is set up,the medium and long term forecast,the factors which influence the final scene simulation using monte carlo method,The impact intensity of pressure factor was determined by some method and then substituted into the conduction model for liquidity risk pressure test.Based on the empirical research results,this paper draws the following conclusions:first,the liquidity risk of a village bank comes from the macroeconomic environment and the bank itself;Secondly,SVAR model can accurately analyze the interaction between various pressure factors and be used in data prediction;Third,when the liquidity ratio is slightly impacted or above by the non-performing loan ratio or moderately impacted or above by internal micro factors,it will fall to the minimum regulatory requirements and even break through the regulatory red line.According to the analysis and empirical conclusions of the current situation of A village bank,in order to better prevent and defuse liquidity risks,this paper puts forward several suggestions: strengthen the liquidity risk early warning management,promote diversification of the assets and liabilities structure,rationalization,improve profitability,improve the stability of deposits,the top design,perfect the liquidity risk management to strengthen the construction of talent team.