發(fā)布時間：2018-02-05 22:38

  本文關鍵詞： 上市銀行 信用風險 KMV模型　出處：《山東大學》2012年碩士論文　論文類型：學位論文

【摘要】：引發(fā)國際性信用危機的往往是少數(shù)幾家存在信用風險的銀行,從美國在20世紀初由長期資本管理公司引發(fā)的華爾街危機,到雷曼兄弟引發(fā)的全球性金融危機,都是由于少數(shù)存在信用風險的金融機構導致的。信用違約風險的發(fā)生對整個金融系統(tǒng)產(chǎn)生巨大沖擊,從而導致了金融危機的發(fā)生,因此測算違約風險水平,防范信用違約風險對金融系統(tǒng)的穩(wěn)定至關重要。 在國外銀行業(yè)信用違約風險的測算方法已經(jīng)成熟,并建立了詳細和龐大的數(shù)據(jù)庫資料,對于從各個角度評價銀行信用風險提供了依據(jù)。而對我國的銀行業(yè)樣本的信用風險分析,不同學者采用了不同的方法嘗試對銀行違約風險的測算,主要集中于對幾大模型的有效性分析和適應性修正的研究上。評價指標主要是傳統(tǒng)的不良資產(chǎn)比率和資本充足率,對銀行業(yè)信用風險的評價主要采用五級分類法,相比新《巴塞爾協(xié)議》對全球銀行業(yè)信用評級體系的要求還有一定差距,如大多數(shù)發(fā)達國家所采用的KMV評級。 鑒于信用違約風險測算在金融系統(tǒng)的重要作用,本文運用了最新的計量模型KMV模型測算了我國銀行的違約風險,選擇信用違約距離、資產(chǎn)波動率、股權波動率等幾大指標評價信用風險,并對影響我國銀行違約風險的因素進行了分析。本文首先選擇了已經(jīng)上市的16家銀行4年的數(shù)據(jù)作為研究對象,并按照因子分類法對其進行分組,分為傳統(tǒng)國有商業(yè)銀行、股份制商業(yè)銀行及城市商業(yè)銀行,并在組內(nèi)根據(jù)打分結果做出對比,其次,本文對KMV模型做出幾點適應性修正,并提取樣本的股權數(shù)據(jù)和資產(chǎn)數(shù)據(jù),分別計算樣本的信用違約距離。最后本文結合因子的分組,對三組銀行的信用違約距離的計算結果、對銀行業(yè)的整體走勢、對組內(nèi)各個樣本的變化分別進行分析,并對其做出預測。 本文的研究結果表明,上市的16家銀行整體信用風險狀況良好,其中股份制商業(yè)銀行的信用風險最小,發(fā)展較穩(wěn)定,說明其信用風險機制已經(jīng)趨于成熟和完善,傳統(tǒng)國有銀行信用風險其次,但是各家銀行的信用風險變化較大,順周期波動的特征明顯。同時暴露出地方性商業(yè)銀行的信用風險整體較大,說明其信用風險控制機制還很不完善,這也為各地不斷成立的地方性金融機構敲響了警鐘。
[Abstract]:The international credit crisis is often triggered by a few banks with credit risks, from the Wall Street crisis triggered by long-term capital management companies in the United States in early 20th century to the global financial crisis triggered by Lehman Brothers. The occurrence of credit default risk has a huge impact on the entire financial system, resulting in the occurrence of financial crisis, so calculate the level of default risk. Preventing the risk of credit default is crucial to the stability of the financial system. In foreign banking credit default risk measurement method has been mature, and has established a detailed and huge database. For the evaluation of bank credit risk from various angles, the credit risk analysis of banking samples in China, different scholars have adopted different methods to try to measure the risk of bank default. It mainly focuses on the effectiveness analysis and adaptive modification of several models. The evaluation indicators are mainly the traditional non-performing assets ratio and capital adequacy ratio. The evaluation of banking credit risk mainly adopts the five-level classification method, compared with the requirements of the new Basel Accord on the global banking credit rating system, there is still a certain gap. Such as the KMV rating adopted by most developed countries. In view of the important role of credit default risk measurement in the financial system, this paper uses the latest measurement model KMV model to calculate the default risk of Chinese banks, choose the distance of credit default, asset volatility. Several indicators, such as equity volatility, evaluate credit risk, and analyze the factors that affect the default risk of Chinese banks. Firstly, this paper selects the data of 16 listed banks for 4 years as the research object. According to the classification of factors, it is divided into traditional state-owned commercial banks, joint-stock commercial banks and urban commercial banks. This paper makes several adaptive modifications to the KMV model and extracts the equity data and asset data of the sample to calculate the credit default distance of the sample. Finally this paper combines the grouping of factors. The calculation results of the credit default distance of the three groups of banks, the overall trend of the banking industry, the changes of each sample in the group are analyzed, and the prediction is made. The results of this paper show that the overall credit risk of the 16 listed banks is in good condition, in which the joint-stock commercial banks have the smallest credit risk and the development is relatively stable. It shows that its credit risk mechanism has become mature and perfect, the traditional state-owned bank credit risk is next, but the credit risk of each bank changes greatly. At the same time, the credit risk of the local commercial banks is relatively large, which indicates that the credit risk control mechanism is not perfect. This has also sounded the alarm bell for the local financial institutions that have been set up all over the world.
【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F832.33;F224

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