基于KMV模型的信息技术业上市公司信用风险度量研究

发布时间：2018-03-18 03:05

本文选题：信用风险　切入点：KMV模型　出处：《哈尔滨商业大学》2017年硕士论文　论文类型：学位论文

【摘要】：信用风险是金融市场上存在的一种最古老最基本的风险类型,同时也是我国金融市场中最重要的风险类型之一,所以其管理水平的高低对我国整个金融业,甚至整个社会经济生活都存在着重要的影响。随着金融环境的日益复杂,传统的、静态的、历史的财务比率度量信用风险的方法已经无法满足银行等金融机构和企业自身对信用风险进行科学度量和管理的需求。信息技术业作为新兴产业发展迅速,对国民经济的发展具有巨大的推动作用,但是其信用风险相比传统行业具有更大的不确定性和波动性,信用风险更高,所以对其信用风险的准确度量尤为重要。运用在国际上得到广泛认可和使用的KMV模型,并根据我国的具体经济环境和数据的可获得性对相关参数进行计量方式的确定,最后将模型运用到我国特定的信息技术业的信用风险度量之中,这对提高我国信息技术业的信用风险度量和管理水平有重要的现实意义。首先,运用文献分析法,在查阅大量相关文献的基础上对本文的研究背景及现状进行详细的介绍,总结前人研究的优点和不足,提出本文研究的主要内容;介绍信用风险和信用风险度量的相关基本理论,运用比较分析的方法对信用风险度量模型进行比较,发现各主要度量模型的优缺点,选择KMV信用风险度量模型作为研究模型。其次,对要用到的KMV信用风险度量模型进行详细的介绍,包括模型的来源、理论基础和计算原理。再次,运用实证研究的方法将KMV模型运用于信息技术业上市公司的信用风险度量中,计算得出信息技术业上市公司的违约距离,并用统计检验方法对结果进行适应性检验,得出KMV模型可以准确的度量出我国信息技术业上市公司的信用风险的结论;最后在研究过程中发现模型在度量信息技术业上市公司信用风险方面还存在一些问题,基于研究发现从宏观国家政策层面、中级企业层面和微观模型本身三个层面提出改进和完善的建议,以期提高模型度量信用风险的适用性,提高信息技术业上市公司的信用风险管理水平,促进行业的健康发展。
[Abstract]:Credit risk is one of the oldest and most basic risk types in the financial market, and it is also one of the most important risk types in our financial market. Even the entire social and economic life has an important impact. As the financial environment becomes increasingly complex, traditional and static, The method of measuring credit risk by historical financial ratio has been unable to meet the needs of banks and other financial institutions and enterprises to measure and manage credit risk scientifically. Information technology industry has developed rapidly as a new industry. It has great impetus to the development of national economy, but its credit risk is more uncertain and volatile than the traditional industry, and the credit risk is higher. Therefore, the accuracy of its credit risk is particularly important. Using the KMV model, which has been widely accepted and used in the world, and according to the specific economic environment and the availability of data in our country, the relevant parameters are determined. Finally, the model is applied to the credit risk measurement of the specific information technology industry in China, which has important practical significance for improving the credit risk measurement and management level of the information technology industry in China. On the basis of consulting a large number of related literature, this paper introduces the research background and current situation in detail, summarizes the advantages and disadvantages of previous studies, and puts forward the main contents of this paper. This paper introduces the basic theories of credit risk and credit risk measurement, compares the credit risk measurement models with the method of comparative analysis, and finds out the advantages and disadvantages of the main measurement models. KMV credit risk measurement model is selected as the research model. Secondly, the KMV credit risk measurement model is introduced in detail, including the source of the model, theoretical basis and calculation principle. The KMV model is applied to the measurement of credit risk of listed companies in information technology industry by using the method of empirical research. The distance of default of listed companies in information technology industry is calculated, and the adaptability of the results is tested by statistical test method. The conclusion is that KMV model can accurately measure the credit risk of listed companies in information technology industry in China. Finally, it is found that there are still some problems in measuring the credit risk of listed companies in information technology industry. Based on the findings of the study, the author puts forward suggestions for improvement and perfection from the macro national policy level, the intermediate enterprise level and the micro model itself, in order to improve the applicability of the model in measuring credit risk. Improve the credit risk management level of IT listed companies and promote the healthy development of the industry.
【学位授予单位】：哈尔滨商业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F224;F49;F832.51

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