基于修正的KMV模型的制造业上市公司信用风险实证研究

发布时间：2018-05-30 22:49

本文选题：制造业 + 上市公司　；参考：《湘潭大学》2013年硕士论文

【摘要】：我国作为世界上发展最迅速的发展中国家，在世界贸易分工的格局下充分发挥了劳动力和资源上的比较优势，在全球的经济地位日益强盛，逐步成为世界上的制造业大国。然而我国制造业以出口为导向、缺乏核心竞争力、风险抵御能力差的特性，使得该行业在2008年的金融危机中遭受重创。正确评价制造业上市公司信用风险，有助于加快该行业的产业结构调整和升级。同时，制造业上市公司作为我国商业银行重要的信贷客户，其信用状况直接影响着商业银行的信贷资产质量，因此对制造业信用风险进行有效度量也有助于商业银行防范信用风险。以我国商业银行的角度度量制造业上市公司信用风险，立足于我国的现实环境，结合制造业上市公司信用风险的特点，通过比较分析四种现代信用风险度量模型得出结论：KMV模型是最适合度量我国制造业上市公司信用风险的模型。然后，运用KMV模型对我国制造业上市公司进行实证研究，在调整了KMV模型的两个参数——违约点和预期资产增长率后，，对实证效果进行检验发现：修正后的KMV模型比未修正的模型能更好地区分正常公司和违约公司之间的信用风险。最后，应用修正后的KMV模型对我国中证100指数中12家具有代表性的大型制造业上市公司的信用风险进行分析，发现这些制造业上市公司从2011到2013年三年间的信用状况都在持续恶化。主要完成了三个方面的创新工作：第一，考虑分行业研究上市公司信用风险，仅以制造业行业为研究对象，通过实证探索适合我国制造业上市公司信用风险研究的违约点。第二，比较三种不同的计算预期资产增长率的方法，确立了历史平均资产增长率为计算资产增长率的最佳方法。第三，选用中证100指数中的12家具有代表性的制造业上市公司作为研究对象，应用修正后的KMV模型分析近三年这些公司的信用风险变化情况，通过实证了解到我国制造业信用状况在恶化。
[Abstract]:China, as the most rapidly developing country in the world, has brought into full play the comparative advantages of labor force and resources under the pattern of world trade division, and has gradually become a big manufacturing country in the world because of its increasingly strong economic position in the world. However, China's manufacturing industry is export-oriented, lack of core competitiveness, and poor risk resistance, which made the industry suffered a heavy blow in the financial crisis in 2008. Evaluating the credit risk of listed manufacturing companies is helpful to speed up the adjustment and upgrading of the industry structure. At the same time, as an important credit customer of commercial banks in China, listed manufacturing companies have a direct impact on the credit assets quality of commercial banks. Therefore, effective measurement of manufacturing credit risk is also helpful for commercial banks to guard against credit risk. To measure the credit risk of listed manufacturing companies from the perspective of commercial banks in China, based on the reality of our country, combined with the characteristics of the credit risk of listed manufacturing companies, Through the comparative analysis of four modern credit risk measurement models, it is concluded that the "KMV" model is the most suitable model for measuring the credit risk of listed manufacturing companies in China. Then, we use the KMV model to make an empirical study on the listed manufacturing companies in our country. After adjusting the two parameters of the KMV model, the default point and the expected growth rate of assets, The empirical results show that the modified KMV model can distinguish the credit risk between the normal company and the defaulting company better than the unmodified model. Finally, using the modified KMV model, this paper analyzes the credit risk of the representative large manufacturing listed companies in China's CSI 100 index. These listed manufacturing companies were found to have continued to deteriorate their credit standing between 2011 and 2013. It mainly completes the innovation work in three aspects: first, considering the research of credit risk of listed companies in different industries, only taking the manufacturing industry as the research object, this paper explores the breach points suitable for the study of credit risk of listed companies in manufacturing industry in China. Secondly, by comparing three different methods of calculating the expected growth rate of assets, we establish that the historical average growth rate of assets is the best way to calculate the growth rate of assets. Thirdly, using 12 representative manufacturing listed companies in the CSI 100 index as the research object, using the modified KMV model to analyze the credit risk changes of these companies in the past three years. Through empirical understanding of China's manufacturing credit situation is deteriorating.
【学位授予单位】：湘潭大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F832.4;F425

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