中文摘要：
信用风险是目前金融机构以及各类企业出现流动性危机的重要根源之一,同时也是引发区域性乃至世界性金融危机的关键因素。它的产生在一定程度上会危害企业的业务经营,增加经营管理成本,降低预期收益,影响资金利用效率,增大交易成本;从全社会的角度来看,其也会造成社会消费力下降、投资者投资意愿降低,进而影响经济发展,若不能对此进行及时治理和管控,最终极有可能发展成金融危机。在目前的信息时代下,我国金融业的发展也已经驶入快车道,于此背景中,金融管制也呈现逐步放松态势,产品与业务的创新备受各金融机构所重视。面对规模日益增长的信用交易,建立精确而完善的风险管理体系已是各企业或金融机构的一大任务,而在完成这一任务的道路中,还面临诸多挑战,这其中,不同信用风险计量模型在不同业务背景下的适用性问题,是目前学界较为热门的话题。KMV模型是建立于期权理论以及公司财务理论上的一类信用风险监测模型,它所利用的数据来自股票市场,而不是企业的历史数据,所以其预测能力较为及时、准确。同时,其结果提供的预期违约率指标实际上是对风险的定量分析,不仅可以用来比较不同公司的风险水平,也可以用来反应风险水平的差异程度,所以其可利用性更高,这些优点使得KMV模型成为目前被业界广泛使用的信用风险计量模型。然而,几乎所有数学模型都会因其理论框架或前提假设等因素的限制,而导致其在某些业务场景中不适用,这里提到的KMV模型当然也不例外,本文正是基于此类思考,在对我国上市公司进行信用风险计量的背景下,探讨了KMV模型的适用性。本文首先对各类金融机构管控信用风险的重要性进行了概述,同时也介绍了新巴塞尔协议中关于信用风险的相关规定以及其针对各类金融机构信用风险管理所倡导的内部评级法。接着,对各类信用风险模型的发展以及研究成果作了简要归纳,而后主要从实证场景、参数修正等方面对KMV模型的相关成果作了总结综述。然后从金融市场中的各类风险入手,探讨了信用风险的特征以及其背后的经济学原理。接着,本文从原理、基本假设、计算步骤、优缺点等方面对KMV模型作了较为详尽的论述。在此基础上,展开对KMV模型适用性的实证研究。对于适用性这一问题,本文所思考的角度始于对公司规模的划分,即具体探索KMV模型对我国不同规模上市企业信用风险计量的适用性如何。因此在实证阶段,本文借鉴国家统计局相关文件,先将我国上市公司以一定的规模标准划分为“甲级规模”和“乙级规模”两类,在此基础上分别在这两类上市公司中随机抽取35家ST类企业,并同时选取在营收规模和行业类别上与之一一配对的非ST类企业,从而形成对照关系。然后运用KMV模型依次对这两种规模类型下的共计140家公司进行信用风险的计量。最后通过多种检验方法研究在不同规模类型下ST类企业与非ST类企业在违约距离上的差异如何,进而以此分别考察KMV模型是否适用于这两种不同规模类型下的上市公司。实证结果显示,当使用KMV模型对甲级规模公司的信用风险进行计量时,ST类公司的违约距离在统计上显著低于非ST类公司,因此可以认为KMV模型对甲级规模上市企业的风险计量具有良好的适用性。而当KMV模型使用在乙级规模的上市企业中时,ST与非ST类公司的违约距离在统计上没有显著的差异,因此可以认为KMV模型不适用于乙级规模上市公司。由于本文对上市企业规模的分类实际上是基于其规模大小的分类,故可以推知,使用KMV模型度量信用风险时,其对规模较大的上市企业适用性较好,而不适用于规模较小的上市公司。基于此结论,本文提出了适合KMV模型进行信用风险度量的具体场景,以期能够帮助我国各金融机构完善其信用风险管理体系,进而提高风险管理能力。
英文摘要：
At present,credit risk is one of the important sources of liquidity crisis in many financial institutions and enterprises,and it is also a key factor that triggers the regional financial crisis and the global financial crisis.Credit risk will harm the business operations of enterprises,increase management costs,reduce expected returns,affect the efficiency of capital use,and increase transaction costs;from a macro perspective,credit risk will also reduce the level of social consumption and investors' investment willingness It will affect economic development.If credit risk cannot be managed and controlled in a timely manner,it may eventually develop into a financial crisis.Now is the information age.China's financial industry is developing rapidly.Under this environment,China's financial control has gradually relaxed,and financial institutions have paid more attention to product and business innovation.Because the scale of credit transactions has grown rapidly,establishing an accurate and complete risk management system has become an important task for many companies and financial institutions.However,in the process of completing this task,it still faces many challenges.The applicability of different measurement models in different business contexts is a hot topic in the academic world.The KMV model is a type of credit risk monitoring model based on option pricing theory and company financial theory.The data it uses comes from the stock market,not the historical data of the enterprise,so its prediction is more accurate.At the same time,the expected default rate provided by the KMV model is a quantitative analysis indicator of risk.It can be used not only to compare the risk levels of different companies,but also to reflect the degree of difference in risk levels,so the KMV model is more available.These advantages make the KMV model a credit risk measurement model widely used in the industry.However,almost all measurement models have some theoretical or premise limitations,which may cause it to be unsuitable in some scenarios,and the KMV model mentioned here is of course no exception.In this kind of thinking,this article uses the KMV model to measure the credit risk of China's listed companies.Based on this,the applicability of the KMV model is discussed.This Thesis first provides an overview of the importance of various financial institutions in managing credit risk.It also introduces the relevant provisions of the New Basel Accord on credit risk and its internal rating-based approach for credit risk management of various financial institutions.Then,the development and research results of various credit risk models are briefly summarized,and then the relevant achievements of the KMV model are summarized mainly from empirical scenarios and parameter corrections.Then,starting with various risks in the financial market,the characteristics of credit risk and the economic principles behind it are discussed.Next,this article makes a more detailed discussion of the KMV model from the aspects of principles,basic assumptions,calculation steps,advantages and disadvantages.On this basis,empirical research on the applicability of the KMV model is launched.Regarding the issue of applicability,the angle of thinking in this article begins with the division of company size,that is,the specific exploration of the applicability of the KMV model to the credit risk measurement of listed companies of different sizes in China.Therefore,in the empirical stage,this thesis draws on the relevant documents from the National Bureau of Statistics and first classifies China's listed companies into two categories:"Class A scale" and "Class B scale" based on a certain scale standard.We randomly selected 35 ST-type companies,and at the same time selected non-ST-type companies that matched one by one in terms of revenue scale and industry category,thus forming a comparison relationship.Then use the KMV model to measure the credit risk of a total of 140 companies in these two scale types in turn.Finally,through a variety of test methods to study the difference between the default distance of ST companies and non-ST companies under different scale types,and then use this to examine whether the KMV model is suitable for listed companies of these two different scale types.The empirical results show that when using the KMV model to measure the credit risk of Class A companies,the default distance of ST companies is statistically significantly lower than that of non-ST companies,so it can be considered that the KMV model is suitable for listed companies of Class A.However,when the KMV model is used in a Class B listed company,there is no statistically significant difference in the default distance between ST and non-ST companies.Therefore,it can be considered that the KMV model is not applicable to the Class B listed company.Since the classification of the size of listed companies in this article is actually based on their size,it can be inferred that when the KMV model is used to measure credit risk,its applicability to large-scale listed companies is better,but it is not suitable for small-scale listings.Based on this conclusion,this article proposes a specific scenario suitable for KMV model for credit risk measurement,in order to help various financial institutions in China to improve their credit risk management system,thereby improving risk management capabilities.
