基于GARCH-GPD-COPULA函数的资产组合风险研究
[Abstract]:With the continuous change of financial markets, the correlation between financial assets is becoming more and more complex, showing nonlinear, asymmetric and tail-related characteristics. The analysis method based on linear correlation sometimes can not accurately reflect the correlation of financial market. At the same time, in reality, the rate of return on financial assets has the characteristics of sharp peak and thick tail, which obviously has non-normal characteristics and nonlinear correlation. Therefore, sometimes it is unreasonable to use the traditional VaR calculation method, so it is necessary to use a reasonable method to describe the actual distribution and correlation of the rate of return. By using the COPULA function method, a flexible multivariate distribution function can be constructed to describe the real distribution and correlation of the rate of return on financial assets, so that a more effective risk measurement model can be established. Therefore, it is of great theoretical value and application significance to use COPULA function to study the risk value of financial assets. In this paper, the GARCH model family is introduced, and the residual distribution of GARCH model is studied, and two kinds of thick tail distribution t distribution and GED distribution are introduced, and then the definition of generalized Pareto distribution (GPD) and the selection method of threshold value are given. Then, the definition and properties of COPULA function and five kinds of COPULA functions are introduced in detail, and the estimation method of COPULA function and the selection method of optimal COPULA function are given. On this basis, three VaR models, GARCH-COPULA,GPD-COPULA and GARCH-GPD-COPULA, are introduced to calculate the risk value. In the empirical part, the risk value (VaR). Of asset portfolio under different quartile is calculated by using historical simulation method and analysis method. Then, the risk value (VaR). Corresponding to GARCH-COPULA,GPD-COPULA,GARCH-GPD-COPUL of three models is calculated by Monte Carlo simulation method. Finally, the failure frequency method was used to test and compare the five kinds of results in 1%, 2%, 3%, 4%, 5%, 10% of the quartile, and the failure frequency method was used to test and compare the five kinds of results at 1%, 2%, 3%, 4% and 5%, respectively. The empirical results show that the failure rate of VaR calculated by GARCH-GPD-COPULA method is the lowest in the sample, which indicates that the estimated risk value is the closest to the real risk value. The innovation of this paper is mainly reflected in the following aspects: (1) the definition, classification and estimation method of COPULA function are summarized systematically and comprehensively. (2) when the GARCH model is used to fit the edge distribution, the residual error in the normal distribution is considered. According to the difference between t distribution and generalized error distribution (GED), the optimal GARCH model is selected. (3) on the basis of previous research on COPULA function, CARCH-COPULA and GPD-COPULA are combined to propose GARCH-GPD-COPULA function. And the corresponding empirical analysis is carried out.
【学位授予单位】:天津财经大学
【学位级别】:硕士
【学位授予年份】:2012
【分类号】:F224;F830.9
【参考文献】
相关期刊论文 前10条
1 李锋;刘澄;;基于极值理论的金融风险研究[J];商业研究;2010年05期
2 欧阳资生,龚曙明;广义帕累托分布模型:风险管理的工具[J];财经理论与实践;2005年05期
3 余萍,龚金国;描述金融市场相关结构的一种新工具——Copula[J];东莞理工学院学报;2005年05期
4 韦艳华,张世英;金融市场的相关性分析——Copula-GARCH模型及其应用[J];系统工程;2004年04期
5 程炳岩;丁裕国;张金铃;江志红;;广义帕雷托分布在重庆暴雨强降水研究中的应用[J];高原气象;2008年05期
6 司继文,蒙坚玲,龚朴;国内外股票市场相关性的Copula分析[J];华中科技大学学报(自然科学版);2005年01期
7 任仙玲;张世英;;基于核估计及多元阿基米德Copula的投资组合风险分析[J];管理科学;2007年05期
8 韦艳华,张世英,孟利锋;Copula理论在金融上的应用[J];西北农林科技大学学报(社会科学版);2003年05期
9 单国莉,陈东峰;一种确定最优Copula的方法及应用[J];山东大学学报(理学版);2005年04期
10 桂文林;韩兆洲;潘庆年;;POT模型中GPD“厚尾”性及金融风险测度[J];数量经济技术经济研究;2010年01期
相关博士学位论文 前1条
1 花拥军;极值理论在中国股市风险度量中的应用研究[D];重庆大学;2009年
相关硕士学位论文 前2条
1 丁林荣;GPD模型与巨灾保险[D];华东师范大学;2008年
2 王皓;极值理论在测度中国股市VaR中的应用与比较[D];浙江大学;2008年
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