【摘要】：在2008年全球金融危機(jī)中,美國(guó)國(guó)內(nèi)多家銀行遭遇了倒閉的厄運(yùn)。信用風(fēng)險(xiǎn)的管理缺陷為這次金融危機(jī)埋下了種子。目前,我國(guó)商業(yè)銀行中間業(yè)務(wù)占比較小,主要以賺取凈息差收入為主要盈利來(lái)源,貸款資金在總資產(chǎn)中占有很大的比重。雖然我國(guó)的不良貸款率曾大幅度下降,近些年來(lái)一直保持在較低的水平。但這并非表示我國(guó)商業(yè)銀行對(duì)于風(fēng)險(xiǎn)管理水平較高。由于歷史因素,我國(guó)的不良貸款的結(jié)構(gòu)存在很大的問題,風(fēng)險(xiǎn)管理水平較西方發(fā)達(dá)國(guó)家相比也存在很大差距。且近幾年,不良貸款率有不斷上升的趨勢(shì)。對(duì)于我國(guó)商業(yè)銀行來(lái)說,加強(qiáng)信用風(fēng)險(xiǎn)的管理刻不容緩。強(qiáng)化信用風(fēng)險(xiǎn)的管理首先要以恰當(dāng)?shù)姆绞絹?lái)度量風(fēng)險(xiǎn),才能有的放矢,制定對(duì)應(yīng)的風(fēng)險(xiǎn)管理對(duì)策。這是本文研究的主旨所在。在信用風(fēng)險(xiǎn)度量的研究方面,定性的風(fēng)險(xiǎn)測(cè)量方式在早期的風(fēng)險(xiǎn)測(cè)算中占據(jù)主體地位,近些年來(lái)更多地采用定量分析方式,較多采用的是現(xiàn)代風(fēng)險(xiǎn)度量模型。CPV模型是其中的一種,該模型以一個(gè)國(guó)家或地區(qū)的宏觀經(jīng)濟(jì)因素為測(cè)算依據(jù),充分考慮到了宏觀經(jīng)濟(jì)因素對(duì)于商業(yè)銀行信用風(fēng)險(xiǎn)的影響。不僅可以對(duì)信用風(fēng)險(xiǎn)進(jìn)行測(cè)算,還可以找出影響信用風(fēng)險(xiǎn)的因素以及各因素對(duì)于信用風(fēng)險(xiǎn)的影響程度。這對(duì)于風(fēng)險(xiǎn)管控部門預(yù)測(cè)風(fēng)險(xiǎn)、預(yù)防風(fēng)險(xiǎn)提供了充分的決策依據(jù)。就目前的我國(guó)商業(yè)銀行來(lái)講,以宏觀經(jīng)濟(jì)因素為依據(jù)的CPV風(fēng)險(xiǎn)度量方式更加適用于我國(guó)資本市場(chǎng)不完善的金融大環(huán)境�，F(xiàn)代的信用風(fēng)險(xiǎn)度量模型分為四種。在對(duì)四種模型進(jìn)行簡(jiǎn)要分析之后,我們可以發(fā)現(xiàn)各個(gè)模型各具優(yōu)缺點(diǎn),也具有不同的適用性。KMV模型在資本市場(chǎng)以及信用管理水平較高的地區(qū)更具適用性；Credit Risk+模型較適用于貸款組合的風(fēng)險(xiǎn)度量；Credit Metrics模型對(duì)于數(shù)據(jù)的要求較高；而CPV模型可以有效地解決上述模型存在的這些問題,具有數(shù)據(jù)易于獲取、考慮全面、準(zhǔn)確性強(qiáng)等特點(diǎn)。就這四個(gè)模型而言,CPV模型更加適用于我國(guó)商業(yè)銀行信用風(fēng)險(xiǎn)的測(cè)度。在實(shí)證研究部分,本文首先簡(jiǎn)要說明CPV模型的原理以及建模步驟。隨后,選用了相關(guān)宏觀經(jīng)濟(jì)指標(biāo)利用CPV模型進(jìn)行實(shí)證分析。根據(jù)全面性、代表性、易得性的原則同時(shí)參考了前人的研究經(jīng)驗(yàn)選取了七個(gè)宏觀經(jīng)濟(jì)指標(biāo)。分別為國(guó)內(nèi)生產(chǎn)總值(GDP)、消費(fèi)者價(jià)格指數(shù)(CPI)、城鎮(zhèn)居民人均可支配收入(SR)、固定資產(chǎn)投資總額(GD)、社會(huì)消費(fèi)品零售總額(SXL)、狹義貨幣供應(yīng)量(M1)、財(cái)政支出總額(CZ)。數(shù)據(jù)均來(lái)源于中國(guó)統(tǒng)計(jì)年鑒公布的2005年第一季度到2015年第三季度的季度數(shù)據(jù)。其中,2005年第一季度至2015年第二季度組成的樣本作為建模樣本,2015年第三季度的樣本作為檢驗(yàn)樣本。然后,進(jìn)行了指標(biāo)篩選與數(shù)據(jù)的預(yù)處理。采用SPSS的逐步進(jìn)入的方式進(jìn)行了指標(biāo)篩選。利用CPI指數(shù)法消除了通貨膨脹因素,利用十二步移動(dòng)平均法消除了季節(jié)因素,利用指標(biāo)的對(duì)數(shù)化處理消除了異方差。通過所得模型發(fā)現(xiàn),財(cái)政支出總額(CZ)、狹義貨幣供應(yīng)量(M1)與我國(guó)商業(yè)銀行的不良貸款率呈現(xiàn)負(fù)向相關(guān)關(guān)系,固定資產(chǎn)投資總額(GD)、消費(fèi)者價(jià)格指數(shù)(CPI)、城鎮(zhèn)居民人均可支配收入(SR)與不良貸款率呈現(xiàn)正向相關(guān)關(guān)系。
[Abstract]:In the global financial crisis of 2008, many of the banks in the United States have suffered from failure. The management of credit risk buried the seed in the financial crisis. At present, the middle business of the commercial bank of our country is relatively small, mainly to earn net interest income as the main profit source, the loan fund has a large proportion in the total assets. Although the rate of non-performing loans in our country has declined substantially, it has been at a lower level in recent years. But it does not mean that China's commercial banks are relatively high in risk management. Due to the historical factors, the structure of the non-performing loans in China has a big problem, and the risk management level also has a great gap compared with the western developed countries. In recent years, the rate of non-performing loans has a rising trend. It is urgent to strengthen the management of credit risk for commercial banks of our country. To strengthen the management of credit risk, the risk can be measured in an appropriate way, and the corresponding risk management countermeasures can be set up. This is the main subject of this study. In the aspect of the research of the credit risk measure, the qualitative risk measurement method takes the status of the main body in the early risk measurement, and the quantitative analysis method is adopted in recent years, and the modern risk measurement model is more adopted in recent years. The CPV model is one of them, which is based on the macro-economic factors of a country or region, and takes fully into account the impact of the macro-economic factors on the credit risk of commercial banks. Not only can the credit risk be measured, but also the factors that affect the credit risk and the degree of influence of each factor on the credit risk can be found. This provides a sufficient basis for decision-making for risk control, risk prevention and risk prevention. In terms of the current Chinese commercial banks, the measure of CPV risk based on the macro-economic factors is more applicable to the imperfect financial environment of our country's capital market. The modern credit risk measurement model is divided into four categories. After a brief analysis of the four models, we can find the advantages and disadvantages of each model, and also have different applicability. The KMV model is more applicable in the capital market and the higher credit management level; the Credit Risk + model is more applicable to the risk measure of the loan combination; the Credit Metrics model is higher for data; and the CPV model can effectively solve the problems existing in the model. The method has the characteristics of easy acquisition of data, comprehensive consideration, strong accuracy and the like. For these four models, the CPV model is more suitable for the measurement of the credit risk of commercial banks in China. In the part of the empirical research, this paper first briefly describes the principle of CPV model and the modeling steps. Then, the relevant macroeconomic indicators were selected to use the CPV model to carry out the empirical analysis. According to the principle of comprehensiveness, representativeness and availability, seven macroeconomic indicators have been selected by reference to the previous experience. It is the gross domestic product (GDP), the consumer price index (CPI), the per capita disposable income (SR) of the urban residents, the total investment of fixed assets (GD), the total retail sales of the social consumer goods (SXL), the narrow money supply (M1) and the total expenditure (CZ). The data is derived from the quarterly data from the first quarter of 2005 to the third quarter of 2015 published by the China Statistical Yearbook. The samples made up from the first quarter of 2005 to the second quarter of 2015 were used as the sample of construction, and the samples in the third quarter of 2015 were used as test samples. then, the pre-processing of the index screening and the data is carried out. The index selection was carried out by the step-by-step approach of SPSS. The factors of inflation are eliminated by the CPI index method, the seasonal factors are eliminated by means of the 12-step moving average method, and the variance is eliminated by the logarithmic processing of the index. Through the obtained model, the total expenditure (CZ), the narrow money supply (M1) and the non-performing loan ratio of the commercial banks in China are negatively related, the total investment (GD) and the consumer price index (CPI) of the fixed assets, The per capita disposable income (SR) of urban residents is positively related to the rate of non-performing loans.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：F832.33

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