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  本文選題：中國商業(yè)銀行　切入點：信用風(fēng)險　出處：《華東師范大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

【摘要】：銀行經(jīng)營的核心是平衡風(fēng)險與收益之間的關(guān)系,謀求在較低的風(fēng)險基礎(chǔ)上取得較高的收益,因此,風(fēng)險管理是銀行永恒的核心內(nèi)容。國際上,信用風(fēng)險的管理正在經(jīng)歷著一場變革,大量的信用風(fēng)險度量模型涌現(xiàn)了出來,而我國商業(yè)銀行在信用風(fēng)險管理方面的發(fā)展卻非常有限,雖然各主要銀行建立了銀行內(nèi)部的企業(yè)信用評級制度,開發(fā)了自己的風(fēng)險控制系統(tǒng),但是它們較少地涉及企業(yè)財務(wù)比率之外的風(fēng)險量化技術(shù)。由于缺乏系統(tǒng)科學(xué)的量化分析技術(shù),就難以利于模型進(jìn)行量化管理,難以按照巴塞爾新資本協(xié)議的要求評估風(fēng)險暴露和提取貸款損失準(zhǔn)備金。 本研究致力于從量化角度對我國商業(yè)銀行信用風(fēng)險管理進(jìn)行研究,首先討論了信用風(fēng)險的成因,巴塞爾新資本協(xié)議的要求,分析了我國商業(yè)銀行信用風(fēng)險管理的現(xiàn)狀和存在的問題。接著對目前廣泛應(yīng)用的信用風(fēng)險度量的KMV模型、Credit Metrics模型、Credit Risk+模型、CPV模型進(jìn)行比較和分析,定性地得出KMV模型是目前適合我國商業(yè)銀行信用風(fēng)險管理的工具。該模型基于B-S-M期權(quán)定價理論,利用股權(quán)價值、股權(quán)價值的波動率和企業(yè)違約點估算出企業(yè)的資產(chǎn)價值和資產(chǎn)價值的波動率,求出違約距離,從而得到企業(yè)的預(yù)期違約率。 在實證部分,本文選取了滬深交易所中2010年被宣告特別處理的17家ST上市公司和與之配對的17家非ST上市公司作為研究對象。根據(jù)2009年樣本公司的財務(wù)數(shù)據(jù)和股票數(shù)據(jù),運用KMV模型最終求出了各樣本公司的違約距離。實證結(jié)果表明ST公司的違約距離遠(yuǎn)遠(yuǎn)小于非ST公司的違約距離,違約距離作為一個度量上市公司違約可能性的指標(biāo),其值越大,表明上市公司違約的可能性就越小,反之則表明上市公司違約的可能性越大。由此可見,KMV模型能夠較好地度量出ST公司和非ST公司的信用風(fēng)險,這在一定程度上反映了我國上市公司真實的信用風(fēng)險狀況。論文最后在前述分析的基礎(chǔ)上,給出了提高我國商業(yè)銀行信用風(fēng)險量化管理水平的建議,并闡述了研究的不足之處。
[Abstract]:The core of bank management is to balance the relationship between risk and income, and seek to obtain higher income on the basis of lower risk. Therefore, risk management is the eternal core content of bank. Credit risk management is undergoing a revolution, a large number of credit risk measurement models have emerged, but the development of our commercial banks in credit risk management is very limited. Although major banks have established their own internal enterprise credit rating systems and developed their own risk control systems, However, they rarely involve risk quantification techniques other than the financial ratios of enterprises. Due to the lack of systematic and scientific quantitative analysis techniques, it is difficult to facilitate the quantitative management of the models. It is difficult to assess risk exposure and draw up loan loss reserves as required by the new Basel Capital Accord. This study is devoted to the study of credit risk management of commercial banks in China from a quantitative perspective. Firstly, it discusses the causes of credit risk and the requirements of the Basel New Capital Accord. This paper analyzes the present situation and existing problems of credit risk management of commercial banks in China, and then compares and analyzes the credit Metrics model and credit Risk model, which are widely used in credit risk measurement. It is concluded qualitatively that KMV model is a suitable tool for credit risk management of commercial banks in China at present. This model is based on B-S-M option pricing theory and utilizes equity value. The volatility of equity value and the default point of enterprise estimate the volatility of asset value and asset value, and calculate the distance of default, and then get the expected default rate of enterprise. In the empirical part, 17 ST-listed companies and 17 non-ST-listed companies in Shanghai and Shenzhen Stock Exchange on 2010 were selected as the research objects. Based on the financial data and stock data of the sample companies in 2009, The empirical results show that the default distance of St company is much smaller than that of non-St company. As an index to measure the possibility of default of listed company, the value of default distance is greater. It shows that the possibility of default of listed company is smaller, and the possibility of default of listed company is higher. It can be seen that KMV model can measure the credit risk of St company and non-St company. This reflects to a certain extent the real credit risk situation of listed companies in China. Finally, based on the above analysis, the paper gives some suggestions to improve the quantitative management level of credit risk of commercial banks in China, and expounds the deficiencies of the research.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：F832.33;F224

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本文編號：1596485