我国商业银行对制造业企业信用风险评价的实证研究

发布时间：2018-02-02 14:44

本文关键词： 商业银行信用风险 logistic模型主成分分析　出处：《山东大学》2017年硕士论文　论文类型：学位论文

【摘要】：商业银行,是我国金融体系中必不可少、十分重要的一个组成部分。全球金融经济危机以来,受到全球经济复苏缓慢的影响,我国也放慢了经济发展速度。目前我国整体经济发展状况为实体经济总体呈现较为疲弱的状态,破产的中小型企业的数量也日益增加。另一方面,在各国经济发展联系愈加紧密的经济全球化的大背景下,我国金融市场和各个国家的金融市场之间相互融合,联系也愈加紧密。金融市场不断推出各类金融创新产品,金融机构的混业经营模式已经慢慢开始形成。"十三五"以来,我国继续强调,深化全面的金融体制改革将作为下一步经济改革的重点。因此,我国的商业银行所要面对的竞争与挑战也在日益加大。所以,商业银行要增强自身抵抗防御各类风险的能力。目前,商业银行面临的威胁主要有操作风险、利率风险、市场风险、信用风险、市场风险、流动性风险等。其中,信用风险对商业银行的健康可持续发展有着巨大的影响作用。信用风险的传统含义是指债务人由于没有能力或者自身无意愿向银行还款,造成违约而对银行所造成的资产损失。更广泛的信用风险,即现代意义上的含义,是指商业银行因为借款人或市场交易对手发生违约行为从而导致自身损失的可能性;也就是说,现在的信用风险即包含了传统含义,还包含由于借款人的信用评级发生变化和履约能力产生变动而导致其债务的市场价值变动,从而引起商业银行产生损失的可能性。一直以来,我国制造业大国。近年来,我国的GDP增长速度较之前的增长速度放缓,经济高速增长的状况转变为现在的中高速增长。与此同时,我国的制作业由于受到不论是来自内部经济宏观环境因素,还是外部世界经济形势与发展格局改变的影响,也开始迈入一个新的阶段。与各类高科技新兴产业的风头正劲相比,我国制造业的现状可谓是风雨飘摇,在困难重重中艰难前行。本文先就信用风险的概念及产生原因进行了简单的介绍,并概括性对国内外关于商业银行信用风险的研究做出了描述;然后对现有的信用风险的度量方法进行简单介绍,做出比较与评价,最终选用了最适合我国现状的Logistics模型,对我国的制造企业的信用风险进行了实证分析。在实证分析部分,本文分别选取了 83家高风险企业和83家低风险企业,以及各自30项财务指标和7项非财务指标。在对各项指标进行数据处理,即显著性检验和主成分分析后,最终确定了构建模型的5个主成分,利用这5个主成分建立了最终的Logistic回归模型。通过检验,发现该模型有着较为准确的预测率。这表明本文所构建的回归模型对于商业银行预测制造业企业信用风险有着一定现实意义。文章最后,就我国商业银行对于信用风险的防范和控制方面提出了相关对策建议。
[Abstract]:Commercial banks are an indispensable and very important part of our financial system. Since the global financial and economic crisis, it has been affected by the slow recovery of the global economy. China has also slowed down the pace of economic development. At present, the overall economic development of our country is the real economy as a whole showing a relatively weak state, the number of bankrupt small and medium-sized enterprises is also increasing day by day. On the other hand. Under the background of the economic globalization, the financial market of our country and the financial market of each country converge with each other. The financial market has continuously introduced various kinds of financial innovation products, and the mixed operation mode of financial institutions has gradually begun to form. Since the 13th Five-Year Plan, China has continued to emphasize. Deepening the comprehensive reform of the financial system will be the focus of the next step of economic reform. Therefore, the competition and challenges that the commercial banks of our country have to face are also increasing day by day. Commercial banks should strengthen their ability to resist and defend all kinds of risks. At present, commercial banks are faced with the main threats are operational risk, interest rate risk, market risk, credit risk, market risk. Among them, credit risk has a great impact on the healthy and sustainable development of commercial banks. The traditional meaning of credit risk is that the debtor is unable to pay back to the bank because of his inability or his own will. The loss of assets to banks caused by default. Broader credit risk, meaning in the modern sense. It refers to the possibility that the commercial bank will lose itself because of the breach of contract by the borrower or the market counterparty. That is to say, the current credit risk includes the traditional meaning, but also includes the change in the market value of the debt due to the change of the borrower's credit rating and the change of the performance ability. In recent years, the growth rate of GDP in China has slowed down compared with the previous growth rate. The situation of rapid economic growth has changed into the present medium and high speed growth. At the same time, the manufacturing industry in our country has been subjected to both internal macroeconomic and macroeconomic environmental factors. Or the impact of the external world economic situation and the change of development pattern, also began to enter a new stage. Compared with all kinds of high-tech emerging industries, the status quo of China's manufacturing industry is shaky. In this paper, the concept of credit risk and its causes are briefly introduced, and the domestic and foreign research on the credit risk of commercial banks is described. Then the existing measures of credit risk are simply introduced, compared and evaluated, and finally selected the most suitable for the current situation of China's Logistics model. In the part of empirical analysis, 83 high-risk enterprises and 83 low-risk enterprises are selected. And each of 30 financial indicators and 7 non-financial indicators. After the data processing of each index, namely significance test and principal component analysis, the five principal components of the model were finally determined. The final Logistic regression model was established by using these five principal components. It is found that the model has a more accurate prediction rate, which indicates that the regression model constructed in this paper has a certain practical significance for commercial banks to predict the credit risk of manufacturing enterprises. This paper puts forward some countermeasures and suggestions on the prevention and control of credit risk in Chinese commercial banks.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F832.33;F424

【参考文献】