本文關(guān)鍵詞：商業(yè)銀行基于KMV模型對(duì)上市公司客戶(hù)信用風(fēng)險(xiǎn)度量研究　出處：《西南政法大學(xué)》2012年碩士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 商業(yè)銀行 信用風(fēng)險(xiǎn) 違約點(diǎn) 行業(yè)分析 KMV模型

【摘要】：防范信用風(fēng)險(xiǎn)一直是商業(yè)銀行經(jīng)營(yíng)管理過(guò)程中面臨的核心問(wèn)題。目前國(guó)際上“歐債危機(jī)”的惡化，美國(guó)經(jīng)濟(jì)的持續(xù)低迷以及“阿拉伯之春”引起的阿拉伯世界各國(guó)的政治動(dòng)蕩等不利因素進(jìn)一步加劇了世界經(jīng)濟(jì)的不確定性，這種不確定性將會(huì)惡化銀行信用的外部環(huán)境，使商業(yè)銀行業(yè)面臨的信用風(fēng)險(xiǎn)進(jìn)一步加大。國(guó)內(nèi)通脹引起的原材料與勞動(dòng)力價(jià)格的普遍上漲，增加了企業(yè)的成本，進(jìn)而擠壓了企業(yè)的利潤(rùn)空間。加之國(guó)內(nèi)利率的市場(chǎng)化以及市場(chǎng)流動(dòng)性的短缺等諸多因素的影響加大了企業(yè)的違約風(fēng)險(xiǎn)。嚴(yán)峻的信用風(fēng)險(xiǎn)形勢(shì)對(duì)我國(guó)商業(yè)銀行信用風(fēng)險(xiǎn)的防范提出了更高的要求。 本文以商業(yè)銀行面臨的上市公司信用風(fēng)險(xiǎn)為研究對(duì)象，通過(guò)改進(jìn)KMV模型違約點(diǎn)選取的參數(shù)，使之更適用于我國(guó)金融市場(chǎng)現(xiàn)狀以及使銀行更準(zhǔn)確的對(duì)上市公司客戶(hù)的信用風(fēng)險(xiǎn)進(jìn)行度量。本文對(duì)國(guó)內(nèi)外有關(guān)KMV模型以及信用風(fēng)險(xiǎn)度量研究的文獻(xiàn)進(jìn)行歸類(lèi)分析的基礎(chǔ)上，介紹了信用風(fēng)險(xiǎn)的度量由定性分析向定量模型發(fā)展的過(guò)程，通過(guò)對(duì)比國(guó)際上最有代表性的四大信用度量模型，確定KMV模型較為適合中國(guó)的金融市場(chǎng)環(huán)境。鑒于KMV模型在國(guó)外應(yīng)用的經(jīng)濟(jì)環(huán)境與我國(guó)現(xiàn)行經(jīng)濟(jì)狀況存在很大的差異，本文對(duì)模型違約點(diǎn)的選取及股權(quán)市場(chǎng)價(jià)值的計(jì)算進(jìn)行了一定的修正，使之適合我國(guó)的金融市場(chǎng)現(xiàn)狀以及我國(guó)信用風(fēng)險(xiǎn)管理現(xiàn)狀。然后利用修正后的KMV模型對(duì)我國(guó)4個(gè)行業(yè)中的32家上市公司的數(shù)據(jù)進(jìn)行實(shí)證研究，得出以下幾個(gè)結(jié)論： 1.通過(guò)對(duì)ST公司與非ST公司三組違約點(diǎn)下的違約距離均值差的比較發(fā)現(xiàn)，違約點(diǎn)選取的參數(shù)為0.75時(shí)，即違約點(diǎn)DP=流動(dòng)負(fù)債+0.75*長(zhǎng)期負(fù)債時(shí)，KMV模型預(yù)測(cè)效果最顯著。 2.文章對(duì)兩組樣本即ST上市公司與非ST上市公司的違約距離進(jìn)行對(duì)比分析，發(fā)現(xiàn)非ST上市公司的違約距離要顯著的大于ST的上市公司的違約距離，說(shuō)明經(jīng)過(guò)修正后的模型能夠較好的區(qū)分ST公司與非ST公司的違約風(fēng)險(xiǎn)。 3.四個(gè)行業(yè)的違約距離存在明顯差異，按違約風(fēng)險(xiǎn)由大到小依次排序?yàn)椋悍康禺a(chǎn)行業(yè)、生物制藥行業(yè)、汽車(chē)行業(yè)、電力行業(yè)。 最后結(jié)合實(shí)證結(jié)果，對(duì)四個(gè)行業(yè)整體違約風(fēng)險(xiǎn)大小及風(fēng)險(xiǎn)產(chǎn)生的原因作出分析，并為商業(yè)銀行信貸管理提出建議。 全文大致分為六個(gè)部分： 第一部分為緒論，主要闡述了論文選題的背景、意義以及文章的研究思路、研究?jī)?nèi)容、研究方法和可能的創(chuàng)新之處。 第二部分是國(guó)內(nèi)外相關(guān)研究現(xiàn)狀綜述，對(duì)國(guó)內(nèi)外關(guān)于信用風(fēng)險(xiǎn)度量和管理的理論研究成果進(jìn)行梳理，并對(duì)優(yōu)秀文獻(xiàn)進(jìn)行簡(jiǎn)單評(píng)述。 第三部分是分別對(duì)幾種信用風(fēng)險(xiǎn)度量方法進(jìn)行優(yōu)缺點(diǎn)的分析，重點(diǎn)對(duì)KMV模型作了詳細(xì)介紹，包括模型所依據(jù)的理論基礎(chǔ)，研究框架和計(jì)算步驟。通過(guò)比較分析突出了KMV模型的優(yōu)勢(shì)。 第四部分是模型的修正及實(shí)證分析。該部分首先根據(jù)中國(guó)經(jīng)濟(jì)的實(shí)際狀況對(duì)模型進(jìn)行合理的修正。然后從上市公司中選取32家具有代表性的上市公司（包含ST與非ST公司）作為樣本，，運(yùn)用修正后的KMV模型對(duì)樣本進(jìn)行實(shí)證分析，并根據(jù)實(shí)證結(jié)果進(jìn)行比較分析，分析結(jié)果表明，KMV模型能較好的識(shí)別上市公司的風(fēng)險(xiǎn)。既能夠較好的區(qū)分ST公司與非ST公司的違約風(fēng)險(xiǎn)，又能夠識(shí)別不同行業(yè)的違約風(fēng)險(xiǎn)，以此說(shuō)明我國(guó)應(yīng)用KMV模型的可行性。 第五部分根據(jù)實(shí)證結(jié)果分析對(duì)商業(yè)銀行信用風(fēng)險(xiǎn)管理提供對(duì)策建議。 論文最后部分是總結(jié)與展望，對(duì)全文內(nèi)容進(jìn)行總結(jié)概括，指出了研究的局限性，并對(duì)后續(xù)的研究工作提出展望。
[Abstract]:To prevent the credit risk has been the core issue facing the management of commercial banks. The current international debt crisis worsened, political unrest and other unfavorable factors continued downturn in the US economy and the "Arabia spring" by Arabia world further exacerbated the world economic uncertainty, this uncertainty will deteriorate bank credit in the external environment, the credit risk faced by commercial banks. To further increase domestic inflation caused by raw materials and labor costs generally rose, increasing the cost of enterprises, and then squeeze corporate profit margins. Coupled with the impact of the domestic interest rate marketization and market liquidity shortage and other factors increase the enterprise default risk. Put forward higher requirements for credit risk situation of Chinese commercial bank credit risk prevention.
The credit risk of listed companies are taking commercial banks as the research object, through the parameters of the improved KMV model default point is selected, which is more suitable for China's financial market situation and make banks more accurate to the listed company credit risk measurement. The basis of the classified analysis in the literature on relevant research at home and abroad to measure KMV model and credit risk, introduces the measurement of credit risk from qualitative analysis to quantitative model of the development process, through the international comparison of the most representative of the four major credit measure model, the KMV model is more suitable for China financial market environment. In view of the KMV model, there is a big difference in foreign economic environment and I in the current economic situation, this paper made some amendments to the model default point selection and stock market value calculation, which is suitable for China's financial market The status quo and the current situation of credit risk management in China are analyzed. Then the data of 32 listed companies in 4 industries in China are empirically studied by using the revised KMV model.
1., by comparing the distance difference between the three groups of default points of ST company and non ST company, it is found that when the default point selection parameter is 0.75, that is, the default point DP=, the +0.75* liability is the most significant.
The 2. pairs of two samples of ST and non ST listed companies default distance for comparative analysis, found that non ST listed companies default distance are significantly greater than ST distance to default of listed companies, the modified model can distinguish between ST companies and non ST companies default risk.
3., there are obvious differences between the four industries' default distance. According to the risk of default, they are ranked as follows: the real estate industry, the biopharmaceutical industry, the automotive industry, the electric power industry.
Finally, based on the empirical results, this paper makes an analysis of the size of the four industries as a whole and the causes of the risk, and puts forward some suggestions for the credit management of the commercial banks.
The full text is roughly divided into six parts:
The first part is the introduction, which mainly expounds the background, significance and research ideas, research contents, research methods and possible innovations of the thesis.
The second part is the summary of the related research at home and abroad, and the theoretical research results of credit risk measurement and management at home and abroad are reviewed, and the excellent literature is simply commented.
The third part is the analysis of the advantages and disadvantages of several credit risk measurement methods. The KMV model is introduced in detail, including the theoretical basis, research framework and calculation steps based on the model. Through comparative analysis, the advantages of KMV model are highlighted.
The fourth part is the empirical analysis and correction model. Firstly, according to the actual situation of the economic Chinese madereasonable amendment to the model. Then from the listed companies in the selection of 32 representative listed companies (including ST and non ST companies) as a sample, using the modified KMV model to analyze the samples, and according to comparative analysis of the empirical results, the analysis results show that the KMV model can better identify the risk of listed companies. It can distinguish between ST companies and non ST companies default risk, and to identify the different sectors of the risk of default, in order to show the feasibility of the application of KMV model in China.
The fifth part provides countermeasures and suggestions on the credit risk management of commercial banks according to the empirical results.
The last part of the paper is the summary and prospect, summarizes the content of the full text, points out the limitations of the research, and puts forward the prospect of the follow-up research work.

【學(xué)位授予單位】：西南政法大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類(lèi)號(hào)】：F832.33

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