本文選題：商業(yè)銀行 + 信用風(fēng)險(xiǎn)��； 參考：《湖南大學(xué)》2012年碩士論文

【摘要】：已有的商業(yè)銀行信用風(fēng)險(xiǎn)壓力測(cè)試模型存在設(shè)計(jì)缺陷，變量選取上受到諸多限制，只能選取較少的變量，對(duì)于影響商業(yè)銀行信用風(fēng)險(xiǎn)的宏觀因素考慮不足。事實(shí)上，商業(yè)銀行的信用風(fēng)險(xiǎn)通常受多個(gè)變量共同影響，為突破原有模型對(duì)選取變量的限制，本文采用偏最小二乘法替代了原似無(wú)關(guān)回歸法，對(duì)信用風(fēng)險(xiǎn)壓力測(cè)試模型中的傳導(dǎo)模型進(jìn)行了改進(jìn)。 本文將我國(guó)股份制商業(yè)銀行2005~2010年季度不良貸款率作為信用風(fēng)險(xiǎn)壓力測(cè)試模型的承壓指標(biāo)，選取了國(guó)內(nèi)生產(chǎn)總值增長(zhǎng)率、固定投資增長(zhǎng)率、進(jìn)出口貿(mào)易總額增長(zhǎng)率等十個(gè)宏觀因素作為壓力指標(biāo)。利用統(tǒng)計(jì)分析等方法對(duì)這些指標(biāo)進(jìn)行處理，構(gòu)建不良貸款率與宏觀因素之間的壓力傳導(dǎo)模型。分別利用似無(wú)關(guān)回歸法與偏最小二乘法對(duì)傳導(dǎo)模型進(jìn)行估計(jì)，對(duì)比結(jié)果發(fā)現(xiàn)：在變量間存在相關(guān)性時(shí)，使用似無(wú)關(guān)回歸法會(huì)出現(xiàn)系數(shù)檢驗(yàn)無(wú)法通過(guò)、符號(hào)異常等問(wèn)題，而選用偏最小二乘法則很好地解決了這一問(wèn)題。 傳導(dǎo)模型構(gòu)建完成后，本文采用蒙特卡洛模擬法，模擬宏觀經(jīng)濟(jì)變量自回歸方程的殘差項(xiàng)變動(dòng)，通過(guò)殘差項(xiàng)求得壓力沖擊情景，構(gòu)建商業(yè)銀行信用風(fēng)險(xiǎn)壓力測(cè)試情景模型。模型結(jié)果顯示，在實(shí)際國(guó)民生產(chǎn)總值下降的沖擊情景下，銀行不良貸款率顯著上升。 我國(guó)商業(yè)銀行運(yùn)用基于偏最小二乘法的壓力測(cè)試模型開(kāi)展信用風(fēng)險(xiǎn)壓力測(cè)試，，需要加強(qiáng)對(duì)相關(guān)宏觀經(jīng)濟(jì)變量的監(jiān)測(cè)，建立及時(shí)有效的反饋報(bào)告機(jī)制。
[Abstract]:The existing commercial bank credit risk stress test model has the design flaw, the variable selection is subjected to many restrictions, can only select the relatively few variables, for the commercial bank credit risk macroscopic factor consideration is insufficient. In fact, the credit risk of commercial banks is usually affected by multiple variables. In order to break through the limitation of the original model on the selection of variables, the partial least square method is used to replace the prima facie independent regression method. The conduction model of credit risk stress test model is improved. In this paper, the non-performing loan ratio of China's joint-stock commercial banks during the period of 2005 ~ 2010 is regarded as the bearing index of credit risk stress test model, and the GDP growth rate and the fixed investment growth rate are selected. Total growth rate of import and export trade and other ten macro factors as pressure indicators. By means of statistical analysis and other methods, the pressure conduction model between non-performing loan rate and macro factors is constructed. The conduction model is estimated by using the method of quasi-independent regression and partial least square, respectively. The comparison results show that when there is correlation between variables, the coefficient test can not pass by using the method of seemingly independent regression, the sign is abnormal, and so on. The partial least square method is a good solution to this problem. After the construction of the conduction model, Monte Carlo simulation method is used to simulate the variation of residual terms in the autoregressive equation of macroeconomic variables. Through the residual terms, the pressure impact scenarios are obtained, and the credit risk pressure test scenario model of commercial banks is constructed. The results show that the ratio of non-performing loans (NPLs) of banks increases significantly under the impact of the decline of real gross national product (GNP). In order to carry out credit risk stress testing by using the stress test model based on partial least square method, commercial banks in China need to strengthen the monitoring of relevant macroeconomic variables and establish a timely and effective feedback reporting mechanism.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F832.33;O241.5

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