商業(yè)銀行流動性風險集成式評價模型及實現(xiàn)研究.pdf

1、華中科技大學碩士學位論文商業(yè)銀行流動性風險集成式評價模型及實現(xiàn)研究姓名：吳金星申請學位級別：碩士專業(yè)：企業(yè)管理指導教師：王宗軍20040428IIAbstract Development with the mixed business of financial industry and entrance of foreign banks, the financial industry of China is facing the au

2、stere competing situation. In order to adapt to the situation the bank industry as the main force of the financial industry of China must strengthen the consciousness of risk management, improve the

3、level of risk management and upgrade the comprehensive competitiveness. Therefore, as the effective means of upgrading the comprehensive competitiveness, the liquidity risk management becomes more and more important

4、 in commercial banks’ operation management. In order to research and evaluate the liquidity risk of commercial banks in China, this paper lucubrated the liquidity risk step by step. The main cont

5、ents of research in this paper are the following: Firstly this paper expounded the concepts and characters of risk and bank risk. Then it brought forward the concept and characters of the liquidi

6、ty risk and analyzed the objectives and significance of liquidity risk management especially in the electric and networked condition. Secondly it reviewed the domestic and foreign theories of liquidity risk

7、 management, analyzing their times background and the advantages and shortcomings of each theory. Next it summed up various methods of liquidity risk management, providing the basic for establishing the integrate

8、d evaluation model for liquidity risk management. Thirdly it qualitatively analyzed the liquidity risk management situation and its causes in commercial banks of China and brought forward the reconsti

9、tute conceive of liquidity risk management according to liquidity risk management practice overseas. Fourthly it designed the structure of the liquidity risk management system and established two indexes

10、systems: one for monitoring the liquidity demand and supply and the other for evaluating the asset allocation, to establish the integrated evaluation model for liquidity risk management based on G

11、M(1,1) and Back-Propagation Neural Network by utilizing the concepts and characters of liquidity risk and catching the essence of liquidity risk management liquidity gap management and asset allocation. Fifthly it carrie