供应链金融中企业组合信用风险度量问题研究

发布时间：2018-11-20 13:50

【摘要】：近年来，供应链金融作为一个全新的融资形式，引起了实业界以及学术界的广泛关注。它是商业银行针对产业供应链管理的发展所开拓的崭新业务领域。区别于简单的贸易融资产品，供应链金融是商业银行与其公司大客户间达成的，以向其提供融资和其他结算、理财服务为基础，，同时向其上游供应商提供货款及时收达便利，或同时向其下游分销商提供预付款代付及存货融资的服务。可以说，供应链金融是一种同时面向供应链中所有成员企业的系统性融资安排。良好的发展前景与丰厚的利润促使各国有及外资银行纷纷加入到了供应链金融业务的竞争之中。目前，国内外针对供应链金融信用风险的相关研究才刚起步，主要依据的是单一企业信用风险的评估方法。然而，供应链金融中的融资企业信用风险度量，不同于一般单一融资企业信用风险度量问题。它的主要特征正是在于债务之间具有高度的关联性，而导致债务相互之间的违约依赖性较强，存在违约传染。因此，对供应链金融中融资企业间违约依赖性的度量就成为解决上述问题的关键。鉴于此，本文从商业银行角度出发，以供应链金融业务中的供应链融资企业为研究对象，围绕供应链融资企业间违约依赖的度量问题展开，利用我国汽车产业链中的上市公司样本，并以样本公司的股票价格及相关财务数据为基础，结合KMV模型、Copula函数理论及风险值技术，构建基于违约依赖的组合信用风险定量分析框架，并借助Matlab（R2011a）计算工具软件，对供应链金融中企业组合信用风险的度量进行实证研究。首先，较系统地归纳了供应链金融中融资企业间违约传染的系列路径，作为后续研究的铺垫。其次，运用KMV模型，并结合整理得到的样本数据，度量了单一供应链融资企业的预期违约距离等相关违约风险度量指标。第三，运用基于Copula函数的违约依赖分析方法，在供应链金融的信用风险度量过程中引入核心企业与其他供应链融资企业之间的违约依赖结构，并优化选择度量函数。最后，根据所选最优Copula函数来描述供应链融资企业间的违约依赖结构，度量供应链融资企业组合的联合违约概率和组合信用风险值。从而更加合理地度量供应链金融中企业组合信用风险，补充现有研究缺失。同时，给商业银行开展供应链金融业务提供量化分析决策参考。研究结果表明，利用Copula函数描述供应链融资企业间的违约依赖关系，并与结构化信用风险度量模型及风险值技术相结合，实现由单一供应链融资企业信用风险度量向组合信用风险度量转变，能捕捉到供应链关联融资企业违约依赖中的传染性违约依赖部分，能更好地确定供应链金融中融资企业的组合信用风险大小，从而使商业银行更准确、灵活地规避相关风险。
[Abstract]:In recent years, supply chain finance, as a new form of financing, has attracted wide attention in industry and academia. It is a new business field developed by commercial banks for the development of industrial supply chain management. Unlike simple trade finance products, supply chain finance is reached between commercial banks and their company's major clients, based on providing them with financing and other settlement, financial services, and providing timely payment facilities to their upstream suppliers. Or at the same time to its downstream distributors to provide advance payment and inventory financing services. It can be said that supply chain finance is a systematic financing arrangement for all members of the supply chain at the same time. The good development prospect and the rich profit urge the state-owned and foreign banks to join in the competition of the supply chain finance business one after another. At present, the research on credit risk of supply chain finance at home and abroad has just started, mainly based on the evaluation method of single enterprise credit risk. However, the credit risk measurement of financing enterprises in supply chain finance is different from that of single financing enterprises. Its main feature is that debt has a high degree of correlation, which leads to the debt default dependence is strong, there is default contagion. Therefore, the measurement of default dependence among financing enterprises in supply chain finance becomes the key to solve the above problems. In view of this, from the perspective of commercial banks, this paper takes the supply chain financing enterprises in the supply chain finance business as the research object, focusing on the measurement of default dependence among supply chain financing enterprises. Using the sample of listed companies in China's automobile industry chain, and based on the sample company's stock price and related financial data, combined with KMV model, Copula function theory and risk value technology, The quantitative analysis framework of portfolio credit risk based on default dependence is constructed. With the help of Matlab (R2011a) calculation tool software, the measurement of portfolio credit risk in supply chain finance is studied empirically. Firstly, a series of paths of default contagion among financing enterprises in supply chain finance are systematically summarized, which is used as the basis for further research. Secondly, using the KMV model and the collected sample data, the paper measures the relative default risk metrics such as the expected default distance of the single supply chain financing enterprises. Thirdly, the default dependence structure between the core enterprise and other supply chain financing enterprises is introduced in the credit risk measurement process of supply chain finance by using the default dependence analysis method based on Copula function, and the selection metric function is optimized. Finally, according to the selected optimal Copula function, the default dependency structure among supply chain financing enterprises is described, and the joint default probability and portfolio credit risk value of supply chain financing enterprises are measured. Thus, the credit risk of enterprise portfolio in supply chain finance can be measured more reasonably, and the existing research will be supplemented. At the same time, it provides quantitative analysis and decision reference for commercial banks to carry out supply chain financial business. The results show that Copula function is used to describe the default dependence among supply chain financing enterprises, and combined with structured credit risk measurement model and risk value technology. In order to realize the transformation from single supply chain financing enterprise credit risk measurement to portfolio credit risk measurement, it can capture the infectious default dependence part of the supply chain associated financing enterprise default dependence. It can better determine the size of portfolio credit risk of financing enterprises in supply chain finance, so that commercial banks can avoid the related risks more accurately and flexibly.
【学位授予单位】：上海师范大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F832;F274;F224

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