本文選題：信用風(fēng)險(xiǎn) + 巴塞爾協(xié)議��； 參考：《安徽大學(xué)》2013年碩士論文

【摘要】：作為現(xiàn)代經(jīng)濟(jì)生活中最為重要的金融主體,商業(yè)銀行在經(jīng)營(yíng)過(guò)程中面臨的最主要風(fēng)險(xiǎn)是信用風(fēng)險(xiǎn)。如何有效防范和化解信用風(fēng)險(xiǎn)成為各國(guó)監(jiān)管機(jī)構(gòu)和銀行從業(yè)者最為關(guān)心的問(wèn)題。巴塞爾新資本協(xié)議提出了以最低資本要求、監(jiān)督檢查以及市場(chǎng)約束為三大支柱的銀行業(yè)監(jiān)管制度框架,為各國(guó)金融監(jiān)管機(jī)構(gòu)如何規(guī)范銀行經(jīng)營(yíng)活動(dòng),控制銀行風(fēng)險(xiǎn)提供有效的指導(dǎo)。在新資本協(xié)議中更為突出風(fēng)險(xiǎn)量化管理的作用并倡導(dǎo)各國(guó)商業(yè)銀行使用現(xiàn)代化信用風(fēng)險(xiǎn)度量模型加強(qiáng)對(duì)信用風(fēng)險(xiǎn)的管理。借助于計(jì)算機(jī)的發(fā)展,國(guó)外諸多銀行對(duì)信用風(fēng)險(xiǎn)的管理均已完成了由定性分析到量化分析的轉(zhuǎn)變。風(fēng)險(xiǎn)管理技術(shù)日趨成熟,產(chǎn)生了以Credit Metrics模型、Credit Risk+模型、Credit Portfolio View模型和KMV模型為代表的現(xiàn)代信用風(fēng)險(xiǎn)度量模型。 我國(guó)商業(yè)銀行在信用風(fēng)險(xiǎn)度量方法上與國(guó)際先進(jìn)銀行存在較大差距,目前仍定性分析為主,缺乏定量分析,無(wú)法有效衡量銀行信用風(fēng)險(xiǎn)大小,不符合巴塞爾委員會(huì)對(duì)銀行監(jiān)管的要求。伴隨著我國(guó)銀行業(yè)的高速發(fā)展,我國(guó)商業(yè)銀行應(yīng)該結(jié)合自身信用風(fēng)險(xiǎn)管理現(xiàn)狀,借鑒現(xiàn)代信用風(fēng)險(xiǎn)計(jì)量模型,推進(jìn)信用風(fēng)險(xiǎn)的量化管理。 本文主要研究信用風(fēng)險(xiǎn)度量模型在我國(guó)應(yīng)用,在對(duì)信用風(fēng)險(xiǎn)及信用風(fēng)險(xiǎn)管理概念進(jìn)行闡述的基礎(chǔ)上,從巴塞爾新資本協(xié)議視角提出信用風(fēng)險(xiǎn)的量化管理,并對(duì)傳統(tǒng)信用風(fēng)險(xiǎn)度量方法以及現(xiàn)代信用風(fēng)險(xiǎn)度量模型進(jìn)行了簡(jiǎn)要介紹；而后詳細(xì)分析了我國(guó)信用風(fēng)險(xiǎn)管理現(xiàn)狀和應(yīng)用現(xiàn)代化度量模型的必要性,通過(guò)對(duì)Credit Metrics模型、Credit Risk+模型、CPV模型和KMV模型在我國(guó)應(yīng)用的可行性分析,得出現(xiàn)階段KMV模型相對(duì)在我國(guó)具有一定的應(yīng)用基礎(chǔ)和條件；隨后通過(guò)KMV模型對(duì)我國(guó)上市公司的實(shí)證分析,驗(yàn)證了該模型預(yù)測(cè)違約的有效性；最后根據(jù)實(shí)證結(jié)論提出相關(guān)對(duì)策和建議。 本文在研究過(guò)程中使用了定性和定量結(jié)合的方法,在對(duì)現(xiàn)代信用風(fēng)險(xiǎn)度量模型進(jìn)行定性分析比較的基礎(chǔ)上選用KMV模型進(jìn)行實(shí)證分析。實(shí)證過(guò)程中,對(duì)相關(guān)參數(shù)進(jìn)行了適當(dāng)?shù)男抻?對(duì)違約臨界點(diǎn)(DP)的確定結(jié)合已有學(xué)者的研究進(jìn)行了如下的修訂：違約臨界點(diǎn)(DP)＝流動(dòng)負(fù)債(STD)＋10%長(zhǎng)期負(fù)債(LTD)。由于缺乏上市企業(yè)違約歷史資料,違約距DD到預(yù)期違約概率EDF的映射采用較為傳統(tǒng)的理論計(jì)算進(jìn)行估計(jì)。另外本文還采用理論和實(shí)踐結(jié)合的方法,從理論上對(duì)信用風(fēng)險(xiǎn)度量進(jìn)行了深入研究,得出我國(guó)商業(yè)銀行需要加強(qiáng)對(duì)信用風(fēng)險(xiǎn)的量化管理；從實(shí)踐上使用KMV模型對(duì)我國(guó)上市公司的違約進(jìn)行預(yù)測(cè)和驗(yàn)證,為我國(guó)商業(yè)銀行進(jìn)行量化風(fēng)險(xiǎn)管理提供借鑒和指導(dǎo)。
[Abstract]:As the most important financial subject in modern economic life, the main risk faced by commercial banks in the course of operation is credit risk. How to effectively prevent and resolve credit risk has become the most concerned problem for regulators and bank practitioners in various countries. The Basel New Capital Accord provides a framework of banking regulatory systems with minimum capital requirements, supervision and inspection, and market constraints as the three pillars. To provide effective guidance in controlling bank risk. In the new capital agreement, the role of risk quantification management is more emphasized and commercial banks of various countries are advocated to use modern credit risk measurement model to strengthen the management of credit risk. With the development of computer, the management of credit risk in many foreign banks has changed from qualitative analysis to quantitative analysis. Risk management technology is becoming more and more mature, and a modern credit risk measurement model, represented by Credit Metrics model, credit Risk model, credit Portfolio View model and KMV model, has emerged. There is a big gap between China's commercial banks and international advanced banks in the measurement of credit risk. At present, the qualitative analysis is still dominant and the quantitative analysis is lacking, which can not effectively measure the size of the bank's credit risk. It does not meet the Basel Committee's requirements for bank supervision. With the rapid development of China's banking industry, Chinese commercial banks should use the modern credit risk measurement model for reference in order to promote the quantitative management of credit risk. This paper mainly studies the application of credit risk measurement model in China. On the basis of expatiating the concept of credit risk and credit risk management, the paper puts forward the quantitative management of credit risk from the perspective of Basel New Capital Accord. The traditional credit risk measurement method and the modern credit risk measurement model are briefly introduced, and then the present situation of credit risk management and the necessity of applying modern measurement model in China are analyzed in detail. Based on the feasibility analysis of the application of Credit Metrics Risk model and KMV model in China, it is concluded that the current KMV model has a certain application foundation and conditions in China, and then the empirical analysis of listed companies in China is made through KMV model. The validity of the model in predicting default is verified, and the relevant countermeasures and suggestions are put forward according to the empirical conclusions. In this paper, the qualitative and quantitative methods are used in the research process, and the KMV model is selected for empirical analysis on the basis of qualitative analysis and comparison of the modern credit risk measurement model. In the empirical process, the relevant parameters have been revised appropriately, and the determination of the default critical point (DPN) has been revised as follows: the default critical point is DPN = the current debt is 10% STD + 10% long term debt (LTD + 10%). Due to the lack of historical data of default of listed enterprises, the mapping from DD to expected default probability (EDF) is estimated by traditional theoretical calculation. In addition, this paper also uses the method of combining theory and practice to study the measurement of credit risk in theory, and draws the conclusion that our commercial banks need to strengthen the quantitative management of credit risk. In practice, the KMV model is used to predict and verify the default of listed companies in China, which provides reference and guidance for Chinese commercial banks to carry out quantitative risk management.
【學(xué)位授予單位】：安徽大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.4

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