Commercial Bank Liquidity Risk Analysis

Under the trend of economical globalization, finance and economy have become two closely related major factors of a country. The global financial crisis led by the U.S. sub-prime mortgage quickly has spread all around the world, since then people have started to worry about liquidity risk of banks. The financial crisis produced a huge negative impact on global financial markets and national macroeconomics. Liquidity risk has accompanied the financial system all the way through since it was established and it has become one of the major courses for bank supervision. The conflict between Profitability and liquidity in the banking operations is the root cause of the commercial bank liquidity risk. Low liquidity is likely to induce liquidity crisis, threatening the bank's survival. After the financial crisis china has pay more attention on the supervision of the bank liquidity, taking it as a significant part of the banking supervision. Since there is a lack of in-depth quantitative research in the study of the commercial bank liquidity risk, the operation of controlling and preventing the liquidity risk of commercial banks has been hardly effective.This paper is divided into four parts to study the problems related to the liquidity risk of Commercial Banks in China, using the quantitative methods such as, AR model and regression analysis to calculate the liquidity risk status of the commercial bank and the effects of each generation in the equation. The first part introduces the research background, significance and the structure of this paper. The second part introduces the concepts of the commercial banks to liquidity risk management based on the reviews of existing literatures and research findings. Furthermore it also presents the major influencing factors, measurement indicators and the classification of the commercial bank liquidity risks. The third part tries to measure the current situation of commercial bank liquidity risk by using a set of quantitative method such as, AR model, lineal regression, and indicators etc. while the forth part of the paper presents some creative proposals for the management of the bank risks depended on the features of china's current economic situation.