基于CPV模型的我國商業(yè)銀行信用風險度量
發(fā)布時間：2018-11-13 14:46
【摘要】：在2008年全球金融危機中,美國國內(nèi)多家銀行遭遇了倒閉的厄運。信用風險的管理缺陷為這次金融危機埋下了種子。目前,我國商業(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源,貸款資金在總資產(chǎn)中占有很大的比重。雖然我國的不良貸款率曾大幅度下降,近些年來一直保持在較低的水平。但這并非表示我國商業(yè)銀行對于風險管理水平較高。由于歷史因素,我國的不良貸款的結(jié)構(gòu)存在很大的問題,風險管理水平較西方發(fā)達國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。對于我國商業(yè)銀行來說,加強信用風險的管理刻不容緩。強化信用風險的管理首先要以恰當?shù)姆绞絹矶攘匡L險,才能有的放矢,制定對應的風險管理對策。這是本文研究的主旨所在。在信用風險度量的研究方面,定性的風險測量方式在早期的風險測算中占據(jù)主體地位,近些年來更多地采用定量分析方式,較多采用的是現(xiàn)代風險度量模型。CPV模型是其中的一種,該模型以一個國家或地區(qū)的宏觀經(jīng)濟因素為測算依據(jù),充分考慮到了宏觀經(jīng)濟因素對于商業(yè)銀行信用風險的影響。不僅可以對信用風險進行測算,還可以找出影響信用風險的因素以及各因素對于信用風險的影響程度。這對于風險管控部門預測風險、預防風險提供了充分的決策依據(jù)。就目前的我國商業(yè)銀行來講,以宏觀經(jīng)濟因素為依據(jù)的CPV風險度量方式更加適用于我國資本市場不完善的金融大環(huán)境。現(xiàn)代的信用風險度量模型分為四種。在對四種模型進行簡要分析之后,我們可以發(fā)現(xiàn)各個模型各具優(yōu)缺點,也具有不同的適用性。KMV模型在資本市場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險度量；Credit Metrics模型對于數(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、準確性強等特點。就這四個模型而言,CPV模型更加適用于我國商業(yè)銀行信用風險的測度。在實證研究部分,本文首先簡要說明CPV模型的原理以及建模步驟。隨后,選用了相關(guān)宏觀經(jīng)濟指標利用CPV模型進行實證分析。根據(jù)全面性、代表性、易得性的原則同時參考了前人的研究經(jīng)驗選取了七個宏觀經(jīng)濟指標。分別為國內(nèi)生產(chǎn)總值(GDP)、消費者價格指數(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)、社會消費品零售總額(SXL)、狹義貨幣供應量(M1)、財政支出總額(CZ)。數(shù)據(jù)均來源于中國統(tǒng)計年鑒公布的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樣本。然后,進行了指標篩選與數(shù)據(jù)的預處理。采用SPSS的逐步進入的方式進行了指標篩選。利用CPI指數(shù)法消除了通貨膨脹因素,利用十二步移動平均法消除了季節(jié)因素,利用指標的對數(shù)化處理消除了異方差。通過所得模型發(fā)現(xiàn),財政支出總額(CZ)、狹義貨幣供應量(M1)與我國商業(yè)銀行的不良貸款率呈現(xiàn)負向相關(guān)關(guān)系,固定資產(chǎn)投資總額(GD)、消費者價格指數(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.
【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：F832.33
本文編號：2329478
[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.
【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：F832.33
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