本文關(guān)鍵詞： 信用風(fēng)險(xiǎn) 巴塞爾協(xié)議 KMV模型　出處：《復(fù)旦大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：信用風(fēng)險(xiǎn)一直是我國(guó)商業(yè)銀行面臨的主要風(fēng)險(xiǎn),而就國(guó)內(nèi)的現(xiàn)狀來(lái)看,我國(guó)銀行業(yè)信用評(píng)級(jí)體系與高級(jí)內(nèi)部評(píng)級(jí)法的要求相差甚遠(yuǎn)。因而,我國(guó)銀行業(yè)若想提高自身實(shí)力及國(guó)際競(jìng)爭(zhēng)力,就必須要立足我國(guó)國(guó)情,開(kāi)發(fā)并應(yīng)用高級(jí)的內(nèi)部模型,進(jìn)而建立適合于我國(guó)經(jīng)濟(jì)環(huán)境的信用風(fēng)險(xiǎn)管理系統(tǒng)。在此背景下,本文以巴塞爾協(xié)議為導(dǎo)向,研究?jī)?nèi)部評(píng)級(jí)法下我國(guó)商業(yè)銀行如何完善信用風(fēng)險(xiǎn)的管理。首先,本文在緒論部分較為全面的介紹了信用風(fēng)險(xiǎn)管理的國(guó)內(nèi)外研究現(xiàn)狀以及我國(guó)商業(yè)銀行信用風(fēng)險(xiǎn)及管理的現(xiàn)狀。接著第二部分則介紹了信用風(fēng)險(xiǎn)的定義及特征、信用風(fēng)險(xiǎn)管理的內(nèi)涵及巴塞爾協(xié)議的內(nèi)容。然后第三部分概括的介紹了內(nèi)部評(píng)級(jí)法的相關(guān)內(nèi)容和四種現(xiàn)代信用風(fēng)險(xiǎn)度量模型,包括Credit Metrics、KMV、Credit Risk+和CPV模型。第四部分則在現(xiàn)狀分析的基礎(chǔ)上,結(jié)合四種度量模型各自的特點(diǎn),對(duì)四種度量模型在我國(guó)商業(yè)銀行信用風(fēng)險(xiǎn)管理中的適用性進(jìn)行了分析,得出KMV模型在我國(guó)銀行信用風(fēng)險(xiǎn)管理中具有比較優(yōu)勢(shì),進(jìn)而選擇對(duì)KMV模型的適用性進(jìn)行實(shí)證研究,并分析了實(shí)證的結(jié)果。第五部分是對(duì)我國(guó)商業(yè)銀行信用風(fēng)險(xiǎn)管理提出一些建議。文章首先介紹了信用風(fēng)險(xiǎn)及管理的相關(guān)理論、巴塞爾協(xié)議的內(nèi)容及四種現(xiàn)代的信用風(fēng)險(xiǎn)度量的模型。其次,結(jié)合我國(guó)銀行業(yè)信用風(fēng)險(xiǎn)及管理的現(xiàn)狀,分析四種度量方法在我國(guó)的適用性。再者,實(shí)證方面,本文選取了截至2013年12月31日,滬深兩市10個(gè)行業(yè)、共20家企業(yè)的財(cái)務(wù)數(shù)據(jù)和市場(chǎng)數(shù)據(jù),運(yùn)用KMV模型計(jì)算企業(yè)違約距離并比較其違約可能性。其中20家企業(yè)包括10家ST企業(yè)和10家非ST企業(yè),ST企業(yè)代表近幾年連續(xù)虧損、財(cái)務(wù)狀況較差、違約概率較大的不良企業(yè),非ST企業(yè)則是經(jīng)營(yíng)正常、違約概率較小的企業(yè)。通過(guò)對(duì)兩類企業(yè)的實(shí)證結(jié)果進(jìn)行比較分析,證明KMV模型能夠較為準(zhǔn)確的度量我國(guó)上市公司的信用風(fēng)險(xiǎn)。
[Abstract]:Credit risk has always been the main risk faced by commercial banks in China, and in terms of the domestic situation, the requirements of the credit rating system of China's banking industry are far from those of the advanced internal rating method. If China's banking industry wants to improve its own strength and international competitiveness, it must base itself on the situation of our country and develop and apply advanced internal models. Then establish a credit risk management system suitable for our country's economic environment. Under this background, this paper studies how to perfect the credit risk management of our commercial banks under the internal rating method. First of all, this paper takes the Basel Accord as the direction to study how to perfect the credit risk management. In the introduction part, this paper introduces the domestic and international research status of credit risk management and the current situation of credit risk and management of commercial banks in China. Then, the second part introduces the definition and characteristics of credit risk. The connotation of credit risk management and the content of Basel Accord. Then the third part summarizes the internal rating method and four modern credit risk measurement models. Including Credit Metrics KMV Risk and CPV model. 4th part based on the analysis of the current situation, combined with the characteristics of the four measurement models. This paper analyzes the applicability of four kinds of measurement models in credit risk management of commercial banks in China, and concludes that KMV model has comparative advantages in credit risk management of banks in China. Then choose the applicability of the KMV model for empirical research. And analyzed the empirical results. Part 5th is to put forward some suggestions on credit risk management of commercial banks in China. Firstly, the paper introduces the theory of credit risk and management. The content of Basel Accord and four modern credit risk measurement models. Secondly, combined with the current situation of banking credit risk and management in China, the applicability of the four measurement methods in China is analyzed. This paper selects the financial data and market data of 20 enterprises in 10 industries of Shanghai and Shenzhen Stock Exchange as of December 31st 2013. The KMV model is used to calculate the default distance and compare the possibility of default. Among them, 20 enterprises include 10 St enterprises and 10 non-St enterprises. Bad enterprises with poor financial situation and high probability of default, while non-St enterprises are those with normal operation and low probability of default. The empirical results of the two types of enterprises are compared and analyzed. It is proved that KMV model can accurately measure the credit risk of listed companies in China.
【學(xué)位授予單位】：復(fù)旦大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F832.4

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本文編號(hào)：1454980