本文關(guān)鍵詞：基于宏觀壓力測(cè)試的我國(guó)商業(yè)銀行信用風(fēng)險(xiǎn)研究　出處：《山西財(cái)經(jīng)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 信用風(fēng)險(xiǎn) 壓力測(cè)試 CPV模型

【摘要】：受到經(jīng)濟(jì)增速放緩等宏觀經(jīng)濟(jì)波動(dòng)的沖擊,我國(guó)商業(yè)銀行不良貸款率連續(xù)多個(gè)季度持續(xù)上升,銀行資產(chǎn)質(zhì)量有持續(xù)惡化的趨勢(shì),銀行面臨的信用風(fēng)險(xiǎn)持續(xù)上升。本文對(duì)我國(guó)商業(yè)銀行進(jìn)行了宏觀壓力測(cè)試,為建立適合我國(guó)國(guó)情的壓力測(cè)試模型提供了一些借鑒,也便于認(rèn)清商業(yè)銀行在可能發(fā)生的宏觀經(jīng)濟(jì)波動(dòng)下,金融系統(tǒng)的穩(wěn)定性以及銀行業(yè)的風(fēng)險(xiǎn)暴露水平,這對(duì)于我國(guó)現(xiàn)階段的銀行業(yè)具有現(xiàn)實(shí)意義。本文在介紹了國(guó)內(nèi)外相關(guān)研究成果的基礎(chǔ)上,給出了信用風(fēng)險(xiǎn)的相關(guān)定義和特征,在對(duì)比了四種現(xiàn)代化的信用風(fēng)險(xiǎn)度量模型之后,最終選取CPV模型進(jìn)行宏觀壓力測(cè)試,并分析了現(xiàn)階段我國(guó)商業(yè)銀行所面臨的信用風(fēng)險(xiǎn)情況。之后,本文介紹了壓力測(cè)試的定義、分類及操作流程。在實(shí)證部分,經(jīng)過對(duì)比后選取不良貸款率作為承壓指標(biāo)進(jìn)行壓力測(cè)試,隨后選取了GDP增長(zhǎng)率、固定資產(chǎn)投資完成總額、社會(huì)消費(fèi)品零售總額、進(jìn)出口總額、廣義貨幣供給量M2、CPI同比增長(zhǎng)率、五年以上貸款利率這些宏觀經(jīng)濟(jì)指標(biāo)作為解釋變量并結(jié)合CPV模型構(gòu)建信用風(fēng)險(xiǎn)傳導(dǎo)模型,通過多元線性回歸得出最終模型。結(jié)果顯示GDP增長(zhǎng)率和固定資產(chǎn)投資完成總額與商業(yè)銀行不良貸款率呈現(xiàn)負(fù)相關(guān)的關(guān)系,而CPI對(duì)不良貸款率的影響則是正向的。其他指標(biāo)對(duì)于不良貸款率并沒有顯著的影響。在壓力測(cè)試環(huán)節(jié),根據(jù)模型結(jié)果和相關(guān)指標(biāo)的變化趨勢(shì),分別設(shè)定了輕度、中度、重度三種壓力測(cè)試情景,結(jié)合信用風(fēng)險(xiǎn)傳導(dǎo)模型執(zhí)行壓力測(cè)試。結(jié)果表明一年以后,在輕度、中度、重度三種沖擊下,不良貸款率將分別上升至2.43%、3.37%、5.31%,同時(shí)撥備覆蓋率將會(huì)下降至128.07%、92.35%、58.61%。我國(guó)商業(yè)銀行的風(fēng)險(xiǎn)抵御能力明顯下降,甚至出現(xiàn)了風(fēng)險(xiǎn)無法被完全覆蓋的情況。為了提高我國(guó)壓力測(cè)試、降低商業(yè)銀行所面臨的信用風(fēng)險(xiǎn),文章最后提出六項(xiàng)政策建議:一、建立我國(guó)商業(yè)銀行業(yè)數(shù)據(jù)庫(kù),完善信用體系的建設(shè)。二、建立符合我國(guó)國(guó)情的壓力測(cè)試體系。三、政府應(yīng)該積極的穩(wěn)定物價(jià)水平,將通貨膨脹保持在適度的范圍。四、政府應(yīng)提高經(jīng)濟(jì)發(fā)展質(zhì)量,改善投資環(huán)境。五、引進(jìn)專業(yè)的風(fēng)險(xiǎn)管理人才,加大人才培養(yǎng)的力度。六、進(jìn)一步完善不良貸款處理體系。
[Abstract]:Under the impact of macroeconomic fluctuations such as economic slowdown, the non-performing loan ratio of commercial banks in China has been rising for several consecutive quarters, and the quality of bank assets has been deteriorating. The credit risk faced by banks continues to rise. This paper carries out macro stress tests on commercial banks in China, which provides some reference for the establishment of a stress test model suitable for the situation of our country. It is also convenient to recognize the stability of the financial system and the risk exposure level of the banking industry under the possible macroeconomic fluctuations of commercial banks. This is of practical significance for China's banking industry at this stage. Based on the introduction of relevant research results at home and abroad, this paper gives the relevant definition and characteristics of credit risk. After comparing four modern credit risk measurement models, CPV model is selected to carry out macro stress test, and the current situation of credit risk faced by commercial banks in China is analyzed. This paper introduces the definition, classification and operation flow of the stress test. In the empirical part, we select the non-performing loan ratio as the pressure index to test the pressure, and then select the growth rate of GDP. Total investment in fixed assets, total retail sales of consumer goods, total imports and exports, and broad money supply M2 / CPI growth rate. Loan interest rate of more than five years these macroeconomic indicators as an explanatory variable and combined with the CPV model to build credit risk transmission model. The final model is obtained by multiple linear regression. The results show that the growth rate of GDP and the total completion of fixed asset investment are negatively related to the non-performing loan rate of commercial banks. The influence of CPI on the non-performing loan rate is positive. Other indicators have no significant effect on the non-performing loan rate. In the stress test, according to the results of the model and the change trend of related indicators. Three stress test scenarios, mild, moderate and severe, were set up, and the results showed that one year later, under three kinds of shocks, mild, moderate and severe, combined with credit risk conduction model, the stress test was performed. The non-performing loan ratio will rise to 2.43% and 3.37% 5.31% respectively, while the coverage rate of provisions will fall to 128.07% or 92.35%. 58.61. in order to improve the stress test and reduce the credit risk faced by commercial banks, the risk resistance of commercial banks in China has obviously decreased, and even the risk can not be completely covered. Finally, the article puts forward six policy recommendations: first, to establish a commercial banking database in China, improve the construction of credit system; second, to establish a stress test system in accordance with the national conditions of our country. The government should actively stabilize the price level and keep inflation in a moderate range. Fourthly, the government should improve the quality of economic development and improve the investment environment. Fifth, the introduction of professional risk management personnel. Increase the strength of personnel training. Sixth, further improve the processing system of non-performing loans.
【學(xué)位授予單位】：山西財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F832.33

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