发行公司债券的上市公司信用风险度量研究

发布时间：2018-01-06 22:00

本文关键词：发行公司债券的上市公司信用风险度量研究　出处：《上海交通大学》2013年硕士论文　论文类型：学位论文

【摘要】：近年来，中国公司债券发行规模逐年递增，这就意味着其信用风险的识别和控制将会是金融市场面临的重要问题。而我国信用风险度量的方法和理念相对于国际发达国家的水平仍然存在很大的差距。现今信用评级结果一般来讲是衡量信用风险的重要工具，在中国却没有发挥其真正的意义，被社会公众过度依赖。KMV模型，作为一种在国外成熟市场备受肯定的结构化信用风险度量和预测工具，能够提供动态和及时的信用风险监控。为了适合中国发行公司债券的上市公司信用风险度量，本文对KMV模型进行参数上的修正。对修正后的KMV模型，通过MATLAB软件算出制造业中发行公司债券的债券主体信用级别“高”和“低”两组的违约距离，结果信用级别“高”的一组违约距离均值显著大于“低”的一组，表明该KMV模型能较好地区分发行公司债券的上市公司的信用风险。在证明KMV模型适用性之后，本文通过比较单纯考虑信用评级对债券收益率的解释力和将信用评级与违约距离相结合对债券收益率的解释力，得出传统信用评级结果和修正的违约距离相结合的效果更好，从而肯定了KMV模型的应用意义。文章同时对债券主体按行业分析，可得房地产行业违约距离均值相对低，信用风险较高。最后对违约距离进行敏感性分析，可得股权价值波动率对违约距离最敏感。中国评级机构对公司债券和债券主体的评级成本高，历时长，不能及时准确地反映公司债券相应的信用风险情况。所以本文提出修正的KMV模型能达到较好度量发行公司债券的上市公司信用风险的效果，有助于改进信用评级技术方法，，完善中国信用评级体系，从而促进中国资本市场更加科学、健康的发展，同时利用修正KMV模型的结果也可为投资者提供参考。
[Abstract]:In recent years, the issuance scale of Chinese corporate bonds has been increasing year by year. This means that the identification and control of credit risk will be an important problem facing the financial market, and there is still a big gap between the methods and concepts of credit risk measurement in China compared with the level of developed countries. Generally speaking, credit rating results are an important tool to measure credit risk. However, it has not played its true significance in China, and has been over-dependent by the public. KMV model is regarded as a well-established structured credit risk measurement and forecasting tool in foreign mature markets. Ability to provide dynamic and timely credit risk monitoring. In order to measure the credit risk of listed companies which issue corporate bonds in China, this paper modifies the parameters of the KMV model and the modified KMV model. Through the MATLAB software, the default distance of the main credit level of the corporate bond issuers in the manufacturing industry is calculated in the two groups of "high" and "low". As a result, the average default distance between the "high" group and the "low" group was significantly higher than that of the "low" group. The results show that the KMV model can better distinguish the credit risk of listed companies issuing corporate bonds. After proving the applicability of the KMV model. This paper compares the explanatory power of credit rating on bond yield and the combination of credit rating and default distance on bond yield. It is concluded that the combination of the traditional credit rating results and the modified default distance is better, and the application significance of the KMV model is confirmed. At the same time, the paper analyzes the bond subject according to the industry. Finally, the sensitivity analysis of default distance is carried out, and the volatility of equity value is the most sensitive to default distance. Chinese rating agencies have a high cost and a long history of rating corporate bonds and bond subjects. The credit risk of corporate bonds can not be accurately reflected in time. Therefore, this paper proposes a modified KMV model to measure the credit risk of listed companies issuing corporate bonds. It is helpful to improve the technical method of credit rating, perfect the credit rating system of China, and promote the development of Chinese capital market more scientifically and healthily. At the same time, the modified KMV model can also be used as a reference for investors.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F275;F832.51;F224

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