本文選題：流動性風險　切入點：壓力測試　出處：《中國海洋大學》2013年碩士論文　論文類型：學位論文

【摘要】：自2008年金融危機爆發(fā)以來，全球金融機構(gòu)都加強了對流動性風險的管理。巴塞爾協(xié)議III的出臺，對流動性風險監(jiān)管提出了新的要求，我國銀監(jiān)會也于2009年10月發(fā)布了《商業(yè)銀行流動性風險管理指引》。在這種新的監(jiān)管背景下，我國商業(yè)銀行加強自身的流動性風險管理就顯得更為重要。壓力測試作為一種比較前沿的衡量商業(yè)銀行風險的方法，已在很多國家得到廣泛的應用。本文旨在研究在這種新監(jiān)管背景下，壓力測試在我國商業(yè)銀行流動性風險管理中的應用。 本文以資產(chǎn)總額20000億為標準，將國內(nèi)的商業(yè)銀行分為中資全國性大銀行和中資全國性中小銀行兩類，選取流動性風險監(jiān)管指標中的流動性比例作為因變量來衡量流動性的大小，并通過灰色關(guān)聯(lián)分析，對影響流動性比例的因素按照影響程度的大小進行排序，最終選取了法定存款準備金率、存貸比、同業(yè)拆借利率、GDP增長率等因素為自變量，建立了多元回歸模型。然后，通過風險因子沖擊分析了在各種不利條件下，這兩類商業(yè)銀行流動性風險的承壓能力。最終得出了目前這兩類商業(yè)銀行的流動性風險承壓能力較高，只有在重度壓力下才會面臨流動性風險的結(jié)論。 根據(jù)壓力測試的結(jié)果，，文章從監(jiān)管和商業(yè)銀行自身兩個角度給出了商業(yè)銀行流動性風險管理的對策。在監(jiān)管層面，要求管理層加強對四大指標的監(jiān)管，建立監(jiān)管指標體系；從商業(yè)銀行自身的角度而言，要求商業(yè)銀行通過建立內(nèi)部控制系統(tǒng)、內(nèi)部數(shù)據(jù)庫和培養(yǎng)流動性風險管理專門人才等措施來建立全面的流動性風險管理體系。文章最后還著重分析了當前壓力測試在流動性風險管理應用中的不足之處，主要有指標選取單一、沒有固定的模型和衡量標準、技術(shù)不成熟等，針對這些不足之處，提出了進一步強化流動性風險壓力測試的對策建議：一是從監(jiān)管角度、靜態(tài)角度和動態(tài)角度三個方面，構(gòu)建完整的流動性風險衡量指標體系；二是建議引入VaR模型、灰色系統(tǒng)模型、蒙特卡羅模擬等方法來完善商業(yè)銀行流動性風險壓力測試模型。
[Abstract]:Since the outbreak of the financial crisis in 2008, the global financial institutions have strengthened the management of liquidity risk. The introduction of Basel III has put forward new requirements for the regulation of liquidity risk. China's Banking Regulatory Commission also issued the "guidelines on liquidity risk Management of Commercial Banks" on October 2009. In this new regulatory context, It is more important for Chinese commercial banks to strengthen their own liquidity risk management. It has been widely used in many countries. This paper aims to study the application of stress testing in liquidity risk management of commercial banks in China under this new regulatory background. Based on the total assets of 2 trillion, this paper divides the domestic commercial banks into two categories: the large Chinese-funded national banks and the Chinese-funded national small and medium-sized banks. The liquidity ratio in the liquidity risk supervision index is selected as dependent variable to measure the liquidity, and the factors affecting liquidity ratio are ranked according to the degree of influence by grey relational analysis. Finally, the factors such as legal reserve ratio, deposit-loan ratio, interbank offered rate and GDP growth rate are selected as independent variables, and a multivariate regression model is established. Finally, the conclusion that the liquidity risk bearing capacity of these two kinds of commercial banks is relatively high, only under the severe pressure, will face the liquidity risk. According to the results of the stress test, the paper gives the countermeasures of liquidity risk management of commercial banks from the perspectives of supervision and commercial banks themselves. At the supervisory level, the management is required to strengthen the supervision of the four indicators and establish a regulatory index system. From the point of view of commercial banks themselves, commercial banks are required to establish internal control systems, The internal database and the training of specialized personnel in liquidity risk management are taken to establish a comprehensive liquidity risk management system. Finally, the paper analyzes the shortcomings of the current stress test in the application of liquidity risk management. There are single indicators, no fixed model and measurement standard, immature technology and so on. In view of these shortcomings, the countermeasures and suggestions to further strengthen the liquidity risk stress test are put forward: first, from the perspective of supervision, The static angle and the dynamic angle are three aspects to construct a complete liquidity risk measurement index system. Secondly, it is suggested to introduce VaR model, grey system model, Monte Carlo simulation and other methods to perfect the liquidity risk pressure test model of commercial banks.
【學位授予單位】：中國海洋大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F832.33

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