Copula函数在金融风险度量中的应用研究
发布时间：2018-10-19 08:42
【摘要】：金融危机频发,金融机构面临的风险日益增多,现有的风险度量方法存在不足,金融风险分布形态各异,现有的相关性度量方法无法描述复杂金融市场的相关模式等等,基于以上这些原因,需要一种既能灵活的构造多元风险分布、又能反映变量间的相关模式的技术出现。Copula函数就是这样一种新的、更加稳健的、灵活的相关性分析技术。它是一个函数,它主要用来描述随机变量之间的相关性。最早提出Copula理论的是Sklar(1959),他指出连续的k(k2)元联合分布函数能分解为一个Copula函数和k个边际分布两部分信息,其中Copula函数描述了随机变量间的相关模式。这样可以选取代表不同相关模式的Copula函数形式来描述金融市场的相关模式,并结合数据的边际分布形式,利用Sklar定理构造出能充分反映数据特征的联合分布形式,最后再根据分布形态得到风险度量指标。所以本文从应用的角度全面系统地探讨了Copula函数在各种金融风险度量中的应用。 在全球金融危机频发的情况下,各国金融机构必须采取措施防范各种风险,以保障金融安全。要保障金融安全,首先需要了解在金融活动中可能会出现哪些风险,以便有针对性地防范和化解风险。根据金融风险的性质和来源不同,金融风险主要面临四种风险：市场风险、信用风险、操作风险和整体风险。 Copula理论在实际应用中有许多优点。Copula函数是很好的描述相关结构的工具,可以非常好地度量金融市场的各种复杂相关模式和相关程度。所以本文从应用的角度全面系统地探讨了Copula函数在各种金融风险度量中的应用。 文章第一章主要介绍了选题背景、研究意义及国内外研究现状。文章第二部分主要介绍了Copula理论,包括其定义、性质、种类等。文章第三章主要介绍了copula理论在金融风险度量中的应用。包括copula理论在金融风险度两种的优势及应用方式。文章第四章介绍了基于copula方法的组合信用风险度量模型,第五章介绍了基于copula方法的投资组合风险测量模型,在此基础上,文章第六章则是基于copula方法的投资组合风险测量的实证研究。 文章归纳整理了国内外关于Copula函数在主要金融风险中的研究现状,指出Copula函数的应用价值。在详细总结Copula函数的基本理论和特点基础上,对由Copula函数导出的相关性度量指标进行深入的分析。文章研究的重点是Copula函数在金融风险、信用风险度量和投资组合风险测量模型的应用。
[Abstract]:With the frequent occurrence of financial crises, the risks faced by financial institutions are increasing day by day, the existing risk measurement methods are insufficient, the financial risk distribution is different, the existing correlation measurement methods can not describe the related models of complex financial markets, and so on. For these reasons, a new, more robust and flexible correlation analysis technique is needed to construct the multivariate risk distribution and reflect the correlation pattern between variables. The Copula function is such a new, more robust and flexible correlation analysis technique. It is a function that describes the correlation between random variables. Sklar (1959) was the first to put forward the Copula theory. He pointed out that the continuous joint distribution function of k (k2) can be decomposed into two parts: a Copula function and k marginal distribution, in which the Copula function describes the correlation model between random variables. In this way, we can select the Copula function which represents different related patterns to describe the related patterns of the financial market, and combine the marginal distribution form of the data, and use the Sklar theorem to construct the joint distribution form, which can fully reflect the characteristics of the data. Finally, the risk measurement index is obtained according to the distribution form. Therefore, this paper discusses the application of Copula function in various financial risk measurement from the perspective of application. Under the situation of frequent global financial crisis, financial institutions in various countries must take measures to prevent all kinds of risks in order to ensure financial security. In order to ensure financial security, it is necessary to know what risks may appear in financial activities, so as to prevent and defuse risks. According to the nature and source of financial risk, financial risk mainly faces four kinds of risks: market risk, credit risk, Operational risk and overall risk. Copula theory has many advantages in practical application. Copula function is a good tool to describe the related structure, and it can measure all kinds of complex correlation models and correlation degree of financial market very well. Therefore, this paper discusses the application of Copula function in various financial risk measurement from the perspective of application. The first chapter mainly introduces the background, research significance and domestic and foreign research status. The second part mainly introduces the theory of Copula, including its definition, properties, types and so on. Chapter three introduces the application of copula theory in financial risk measurement. Including the advantages and application of copula theory in financial risk. The fourth chapter introduces the portfolio credit risk measurement model based on copula method, and the fifth chapter introduces the portfolio risk measurement model based on copula method. Chapter 6 is an empirical study of portfolio risk measurement based on copula method. This paper summarizes the research status of Copula function in main financial risks at home and abroad, and points out the application value of Copula function. On the basis of summarizing the basic theory and characteristics of Copula function in detail, the correlation metric derived from Copula function is analyzed deeply. This paper focuses on the application of Copula function in financial risk, credit risk measurement and portfolio risk measurement.
【学位授予单位】：长江大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F224;F830
本文编号：2280659
[Abstract]:With the frequent occurrence of financial crises, the risks faced by financial institutions are increasing day by day, the existing risk measurement methods are insufficient, the financial risk distribution is different, the existing correlation measurement methods can not describe the related models of complex financial markets, and so on. For these reasons, a new, more robust and flexible correlation analysis technique is needed to construct the multivariate risk distribution and reflect the correlation pattern between variables. The Copula function is such a new, more robust and flexible correlation analysis technique. It is a function that describes the correlation between random variables. Sklar (1959) was the first to put forward the Copula theory. He pointed out that the continuous joint distribution function of k (k2) can be decomposed into two parts: a Copula function and k marginal distribution, in which the Copula function describes the correlation model between random variables. In this way, we can select the Copula function which represents different related patterns to describe the related patterns of the financial market, and combine the marginal distribution form of the data, and use the Sklar theorem to construct the joint distribution form, which can fully reflect the characteristics of the data. Finally, the risk measurement index is obtained according to the distribution form. Therefore, this paper discusses the application of Copula function in various financial risk measurement from the perspective of application. Under the situation of frequent global financial crisis, financial institutions in various countries must take measures to prevent all kinds of risks in order to ensure financial security. In order to ensure financial security, it is necessary to know what risks may appear in financial activities, so as to prevent and defuse risks. According to the nature and source of financial risk, financial risk mainly faces four kinds of risks: market risk, credit risk, Operational risk and overall risk. Copula theory has many advantages in practical application. Copula function is a good tool to describe the related structure, and it can measure all kinds of complex correlation models and correlation degree of financial market very well. Therefore, this paper discusses the application of Copula function in various financial risk measurement from the perspective of application. The first chapter mainly introduces the background, research significance and domestic and foreign research status. The second part mainly introduces the theory of Copula, including its definition, properties, types and so on. Chapter three introduces the application of copula theory in financial risk measurement. Including the advantages and application of copula theory in financial risk. The fourth chapter introduces the portfolio credit risk measurement model based on copula method, and the fifth chapter introduces the portfolio risk measurement model based on copula method. Chapter 6 is an empirical study of portfolio risk measurement based on copula method. This paper summarizes the research status of Copula function in main financial risks at home and abroad, and points out the application value of Copula function. On the basis of summarizing the basic theory and characteristics of Copula function in detail, the correlation metric derived from Copula function is analyzed deeply. This paper focuses on the application of Copula function in financial risk, credit risk measurement and portfolio risk measurement.
【学位授予单位】：长江大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F224;F830
【参考文献】
相关期刊论文 前7条
1 许小勇;钟太勇;;三次样条插值函数的构造与Matlab实现[J];兵工自动化;2006年11期
2 薄纯林;王宗军;;基于贝叶斯网络的商业银行操作风险管理[J];金融理论与实践;2008年01期
3 阎庆民;我国商业银行信用风险VaR的实证分析[J];金融研究;2004年10期
4 刘家鹏;詹原瑞;刘睿;;基于贝叶斯网络的银行操作风险管理系统[J];计算机工程;2008年18期
5 刘小莉;;信用风险与市场风险相关性的度量研究[J];世界经济情况;2006年07期
6 刘大伟;杜子平;;Copula方法在投资组合选择与VaR计量中的应用[J];统计与决策;2006年05期
7 王春峰,李刚,赵欣;基于模拟退火算法的VaR-GARCH模型[J];系统工程学报;2003年01期
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