基于KMV模型对非金融企业债务融资工具的研究分析

发布时间：2018-03-17 11:08

本文选题：KMV模型　切入点：信用风险　出处：《首都经济贸易大学》2017年硕士论文　论文类型：学位论文

【摘要】：近年来,我国经济总量稳步增长,科技水平快速提高,在国际中的地位也越来越显著,许多企业响应国家的“走出去”战略,增加自身实力,纷纷进行了改革与创新。而从企业战略发展的角度来看,为满足提高竞争力的需求,融资是必不可少的一个环节。随着融资规模的不断增加,金融业也呈现一片欣欣向荣的态势,同时,为了给实体经济铺路,满足融资需求,政府对国内金融市场进行改革,在国家政策的引领下下,金融市场上推出了越来越多灵活、方便的金融产品。其中,近些年,中国银行间交易商协会推出的以注册制发行的非金融企业债务融资工具备受关注,2016年全年发行规模超过5万亿。但是随着发行量与发行企业数量的增加,债券市场中的信用风险也在逐步扩大,违约事件频繁发生,极大的损害了投资者的利益,扰乱了市场秩序。因此,当务之急是加强债券市场信用风险防控能力,减少信用违约带来的损失。目前,我国信用评级体系不够完备,随着中国银行间市场债券发行规模的逐年增加,对债券信用风险识别的要求也水涨船高。而同时我国在风险控制和度量领域的理论和方法研究相较一些发达国家有所欠缺。因此,本文为探究出合适于中国市场的风险评估方法,将运用KMV模型对非金融企业债务融资工具进行研究分析。考虑到KMV模型是来自美国的舶来品,本文根据我国债券市场的实际情况对KMV模型的参数进行改良。首先,本文采用ARMA模型、GARCH模型计算股权价值波动率。接着本文选用2014年至2016年期间的70家发生债券违约的上市公司,截取它们的财务数据,对其进行OLS估计,确定出最适合我国债券市场的违约点计算公式,得了最贴合我国银行间债券市场的KMV模型。最后,使用KMV模型研究我国银行间市场上市公司发行的非金融企业债务融资工具,求出平均违约距离,并对上市公司进行区分,其结果与传统评级互相印证,证明修正后的KMV模型能够较好的评估发行债券的上市公司信用风险,有利于完善中国信用评级机制,防范信用风险的发生的同时又可以促进有关信用评级改革。
[Abstract]:In recent years, China's total economic volume has steadily increased, the level of science and technology has improved rapidly, and its position in the international community has become more and more prominent. Many enterprises have responded to the "going out" strategy of the country and increased their own strength. Reform and innovation have been carried out one after another. In view of the strategic development of enterprises, financing is an indispensable link in order to meet the needs of improving competitiveness. At the same time, in order to pave the way for the real economy and meet the financing needs, the government has reformed the domestic financial market. Under the guidance of national policies, more and more flexibility has been introduced in the financial market. Convenient financial products. Among them, in recent years, The debt financing instrument of non-financial enterprises issued by the China Association of Interbank Dealers, issued on a registered basis, attracted much attention. In 2016, the size of the issue exceeded 5 trillion. But as the number of issuers and issuers increased, The credit risk in the bond market is also gradually expanding, and the frequent occurrence of default events has greatly damaged the interests of investors and disturbed the market order. Therefore, it is imperative to strengthen the ability of preventing and controlling credit risks in the bond market. At present, China's credit rating system is not complete. With the increase in the size of bond issuance in China's inter-bank market, At the same time, the research on the theory and method in the field of risk control and measurement in China is less than that in some developed countries. In order to explore a risk assessment method suitable for the Chinese market, this paper will use KMV model to study and analyze the debt financing tools of non-financial enterprises, considering that the KMV model is imported from the United States. This paper improves the parameters of KMV model according to the actual situation of China's bond market. In this paper, ARMA model is used to calculate the volatility of equity value. Then, 70 listed companies with bond defaults from 2014 to 2016 are selected to intercept their financial data and estimate them by OLS. The best formula for calculating the default point of China's bond market is determined, and the KMV model is obtained, which is most suitable for China's interbank bond market. Finally, the KMV model is used to study the non-financial enterprise debt financing tools issued by the listed companies in the interbank market of our country. To find out the average default distance and distinguish the listed companies, the results are confirmed with the traditional rating, which proves that the modified KMV model can better evaluate the credit risk of the listed companies issuing bonds, which is helpful to improve the credit rating mechanism of China. Preventing the occurrence of credit risk can also promote the credit rating reform.
【学位授予单位】：首都经济贸易大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F832.51

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