The Measurement Of Liquidity Risk Of Commercial Banks Based On The Copula Theory

In recent years,China's economic society has undergone some major new changes in its continuous development.The interest rate marketization reform that lasted nearly 10 years is slowly drawing to a close,innovation in financial science and technology is constantly deepening,the banking industry that dominates the financial industry in China began to actively seek its own breakthrough development.Although there have been different development trends in the asset and liability structure,the diversity and the complexity of business types,but the degree of correlation between peers is continuously deepening,which makes the liquidity in commercial banks is more and more obvious due to the fluctuation of the financial market,and liquidity risks caused by the shortage of liquidity are more likely to be transmitted within the banking system.Therefore,this paper takes the liquidity risk of commercial banks as the research object Based on the analysis of relevant theories and the analysis of the inadequacies of the existing liquidity risk monitoring indicators,the paper uses factor analysis to construct comprehensive measure of liquidity risk factor.At the same time,the Copula theory and non-parametric kernel density estimation methods were introduced to construct the Copula-Kernel model,and the Monte Carlo simulation technique was used to simulate the future distribution of the liquidity risk combined value Z(Z=?*MLR+(1-?)*FLR),and then realized the VaR measurement of the liquidity risk of China's commercial banks,and drew some valuable conclusions.This article starts with the background of the topic and explains the research significance of this topic.Secondly,we summarize and review the research status at home and abroad from the two parts of liquidity risk and Copula theory.After sorting out the relevant theories,this paper reviews and reviews the transition history of liquidity risk supervision in China's banking industry.Based on this,it summarizes the current monitoring methods and related indicators of liquidity risk in China's commercial banks.By analyzing the inadequacies of the existing liquidity risk supervision indicators,a actor analysis method is proposed to construct the liquidity risk factor measurement index.Taking the constructed index as a variable,the risk factor data of the overall banking industry is sampled to construct the Copula-Kernel model.The validity test was performed.Finally,Monte Carlo simulation technology was used to realize the VaR measurement of liquidity risk of major commercial banks.According to the empirical results,some conclusions have been drawn:the liquidity risk VaR estimated under the Copula-Kernel model is the risk value measured by taking the dependency structure between the risk factors into account,and compared with the traditional historical simulation method,it can more accurately measure the liquidity risk of commercial banks;at the same time,the empirical results show that the liquidity risk among banks in the current banking system is quite different,and the pressure on liquidity risks faced by large state-owned banks is greater than that of joint-stock commercial banks;The banking system is greatly affected by the fluctuation of the financing market and many more.Finally,based on the research conclusions,we propose some targeted countermeasures from improving the monitoring indicators of liquid ity risks,vigorously developing and applying advanced mathematical techniques,and establishing a unified data warehouse and management information system as soon as possible and many more to improve current liquidity risk monitoring and management of commercial banks in China,analyzes and forecasts the deficiencies in this article.