商业银行视角下的战略性新兴产业上市公司信用风险度量
发布时间：2018-07-20 09:33
【摘要】：近年来，战略性新兴产业在世界各国的经济和科技发展中起到重要作用，各个国家都十分重视战略性新兴产业的发展。提高对战略性新兴产业的关注与金融支持力度是促使我国经济更长远稳定发展的重要选择。当前，我国正积极筹备战略性新兴产业未来5年的发展规划，在“十三五”期间将继续重点扶持与发展包括新能源、节能环保、生物医药等在内的新兴产业领域，并逐步将其提升为我国国民经济的支柱产业。同时，我国央行亦发布公告要求银行业等金融机构加快信贷结构优化进度，加大节能减排的支持力度，从而促使资源更加有效的配置，进一步推进我国经济结构的调整和发展方式的转变。因此，开发出战略性新兴产业的相关金融产品、抢占其市场份额将成为未来我国银行体系发展的方向决定了未来银行业的主要竞争力，具有重大的战略意义，从而，我国商业银行体系加大对战略性新兴产业的关注度也是大势所趋。 研究的路径首先从文献研究出发，通过对战略性新兴产业、KMV模型度量企业信用风险的国内外研究文献的梳理，为进一步的理论和实践探讨做铺垫。结合战略性新兴产业企业在我国的发展特征，总结出其信用风险不同于传统产业企业的成因，并客观阐述了我国银行对战略性新兴产业信用风险的管理现状；其次，运用理论与现实分析相结合的方法分析了商业银行为战略性新兴产业提供金融支持的必要性，及信贷过程信用风险度量的重要性；最后利用实证分析法，从商业银行的视角，运用KMV模型对战略性新兴产业上市公司信用风险进行度量研究。 将KMV模型引入到战略性新兴产业中，利用数学推导和MATLAB编程输出模型在一定假设条件下的违约距离，采用对比研究法设置与正常战略性新兴产业上市公司的对照组，分别通过对比组间违约距离的描述性统计分析、违约距离对各参数的敏感性多元线性回归分析以及组间上市公司理论预期违约率EDF的信用评级比较这三个实证过程，逐步加强对实证结论的验证，即之于商业银行，正常战略性新兴产业公司的潜在信用风险要小于ST公司的信用风险。针对上述结论，为商业银行与战略性新兴产业企业信贷业务往来中产生的信用风险提供了有效地度量指标，在一定程度上为商业银行提供了企业信用评级参考，，从而银行在考虑对战略性新兴产业这几大行业中的企业进行信贷支持时，能够有的放矢的选择信用风险较小的投资对象，降低银行的信用风险。
[Abstract]:In recent years, strategic emerging industries play an important role in the development of economy and science and technology all over the world, and all countries attach great importance to the development of strategic emerging industries. Increasing attention to strategic emerging industries and financial support is an important choice to promote the long-term and stable development of China's economy. At present, China is actively preparing plans for the development of strategic emerging industries in the next five years. During the 13th Five-Year Plan period, China will continue to focus on supporting and developing new industries, including new energy sources, energy conservation, environmental protection, biomedicine, and so on. And gradually promote it as the pillar industry of our national economy. At the same time, the people's Bank of China has also issued a notice urging banking and other financial institutions to accelerate the progress of credit structure optimization and increase support for energy conservation and emission reduction, thus promoting more effective allocation of resources. We will further promote the readjustment of China's economic structure and the transformation of its mode of development. Therefore, developing related financial products of strategic emerging industries and seizing market share of them will become the direction of the development of our banking system in the future, which will determine the main competitiveness of the banking industry in the future, which is of great strategic significance. It is also the trend of our commercial banking system to pay more attention to the strategic emerging industries. The path of the research is based on the literature research, through combing the domestic and foreign research literature on the KMV model of strategic emerging industry to measure the credit risk of enterprises, so as to pave the way for further theoretical and practical discussion. Combined with the characteristics of the development of strategic emerging industry enterprises in China, this paper summarizes the causes of its credit risk being different from the traditional industrial enterprises, and objectively expounds the current situation of the management of the credit risk of strategic emerging industries in China's banks. Secondly, This paper analyzes the necessity of commercial banks to provide financial support for strategic emerging industries, and the importance of credit risk measurement in the credit process by combining theory with practical analysis, finally, using empirical analysis, from the perspective of commercial banks. Using KMV model to measure the credit risk of listed companies in strategic emerging industries. The KMV model is introduced into the strategic emerging industry, and the default distance of mathematical derivation and MATLAB programming output model under certain hypothetical conditions is used to set the control group of the listed company of the normal strategic emerging industry by using the comparative research method. By comparing the descriptive statistical analysis of default distance between groups, the multivariate linear regression analysis of the sensitivity of default distance to each parameter, and the credit rating comparison of EDF of theoretical expected default rate of listed companies among groups, the empirical processes are analyzed. Gradually strengthen the verification of empirical conclusions that is to commercial banks the potential credit risk of normal strategic emerging industry companies is smaller than that of St companies. In view of the above conclusions, it provides an effective measurement index for the credit risk arising from the credit transactions between the commercial banks and the strategic emerging industry enterprises, and to a certain extent provides the commercial banks with a reference to the credit rating of the enterprises. Therefore, when the banks consider the credit support to the enterprises in the strategic emerging industries, they can choose the investment object with small credit risk and reduce the credit risk of the banks.
【学位授予单位】：东华大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F276.44;F832.4
本文编号：2133116
[Abstract]:In recent years, strategic emerging industries play an important role in the development of economy and science and technology all over the world, and all countries attach great importance to the development of strategic emerging industries. Increasing attention to strategic emerging industries and financial support is an important choice to promote the long-term and stable development of China's economy. At present, China is actively preparing plans for the development of strategic emerging industries in the next five years. During the 13th Five-Year Plan period, China will continue to focus on supporting and developing new industries, including new energy sources, energy conservation, environmental protection, biomedicine, and so on. And gradually promote it as the pillar industry of our national economy. At the same time, the people's Bank of China has also issued a notice urging banking and other financial institutions to accelerate the progress of credit structure optimization and increase support for energy conservation and emission reduction, thus promoting more effective allocation of resources. We will further promote the readjustment of China's economic structure and the transformation of its mode of development. Therefore, developing related financial products of strategic emerging industries and seizing market share of them will become the direction of the development of our banking system in the future, which will determine the main competitiveness of the banking industry in the future, which is of great strategic significance. It is also the trend of our commercial banking system to pay more attention to the strategic emerging industries. The path of the research is based on the literature research, through combing the domestic and foreign research literature on the KMV model of strategic emerging industry to measure the credit risk of enterprises, so as to pave the way for further theoretical and practical discussion. Combined with the characteristics of the development of strategic emerging industry enterprises in China, this paper summarizes the causes of its credit risk being different from the traditional industrial enterprises, and objectively expounds the current situation of the management of the credit risk of strategic emerging industries in China's banks. Secondly, This paper analyzes the necessity of commercial banks to provide financial support for strategic emerging industries, and the importance of credit risk measurement in the credit process by combining theory with practical analysis, finally, using empirical analysis, from the perspective of commercial banks. Using KMV model to measure the credit risk of listed companies in strategic emerging industries. The KMV model is introduced into the strategic emerging industry, and the default distance of mathematical derivation and MATLAB programming output model under certain hypothetical conditions is used to set the control group of the listed company of the normal strategic emerging industry by using the comparative research method. By comparing the descriptive statistical analysis of default distance between groups, the multivariate linear regression analysis of the sensitivity of default distance to each parameter, and the credit rating comparison of EDF of theoretical expected default rate of listed companies among groups, the empirical processes are analyzed. Gradually strengthen the verification of empirical conclusions that is to commercial banks the potential credit risk of normal strategic emerging industry companies is smaller than that of St companies. In view of the above conclusions, it provides an effective measurement index for the credit risk arising from the credit transactions between the commercial banks and the strategic emerging industry enterprises, and to a certain extent provides the commercial banks with a reference to the credit rating of the enterprises. Therefore, when the banks consider the credit support to the enterprises in the strategic emerging industries, they can choose the investment object with small credit risk and reduce the credit risk of the banks.
【学位授予单位】：东华大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F276.44;F832.4
【参考文献】
相关期刊论文 前10条
1 闫海峰;华雯君;;基于KMV模型的中国上市公司信用风险研究[J];产业经济研究;2009年03期
2 张玲,杨贞柿,陈收;KMV模型在上市公司信用风险评价中的应用研究[J];系统工程;2004年11期
3 薛锋,关伟,乔卓;上市公司信用风险度量的一种新方法——KMV[J];西北工业大学学报(社会科学版);2003年03期
4 翟东升;张娟;曹运发;;KMV模型在上市公司信用风险管理中的应用[J];工业技术经济;2007年01期
5 都红雯,杨威;我国对KMV模型实证研究中存在的若干问题及对策思考[J];国际金融研究;2004年11期
6 熊广勤;罗方珍;;金融支持战略性新兴产业发展的现状及其作用机制研究[J];商业经济;2012年03期
7 顾海峰;;战略性新兴产业演进的金融支持体系及政策研究——基于市场性金融的支持视角[J];经济问题探索;2011年11期
8 叶庆祥,景乃权,徐凌峰;基于资本市场理论的上市公司信用风险度量研究[J];经济学家;2005年02期
9 郑江淮;;理解战略性新兴产业的发展——概念、可能的市场失灵与发展定位[J];上海金融学院学报;2010年04期
10 李磊宁;张凯;;KMV模型的修正及在我国上市公司信用风险度量中的应用[J];金融纵横;2007年13期
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