导　　师： 钟波

学科专业： 070103

授予学位： 硕士

作　　者： ;

机构地区： 重庆大学

摘　　要： 近年来,随着金融全球化和自由化的不断深入,金融风险管理技术得到了迅猛发展。而上世纪90年代初才提出来的VaR方法,由于本身具有良好的性质,使它很快成为风险管理中最重要、应用最广泛的风险度量方法。Copula函数可以将多个随机变量的边缘分布连接在一起形成联合分布。变量间的相关结构完全由Copula函数决定,而各变量的统计特征由其边缘分布确定。这样Copula函数在多元建模领域成为重要的工具。与描述变量间线性相关关系的常规方法相比,Copula描述的多元随机变量间的相关结构可以提供更准确的信息。鉴于此,越来越多的学者将Copula函数应用到VaR中,取得了不错的效果。 就目前来看,Copula函数在应用中存在的主要问题就是函数形式的选择。虽然一些文献就Copula函数的选择提出了相应的建议,但是这一问题并未得到很好的解决。论文针对这一情况,在充分总结现有选择方法的基础上,使用一种基于贝叶斯理论的Copula函数选择方法。该方法无需对Copula函数的参数进行估计,并能对待选Copula函数的拟合效果排序;结合图形选择方法对中国证券市场进行研究,得到了待选的Copula函数拟合效果顺序,确定最优Copula函数。另一方面,论文考虑到实际收益的“尖峰厚尾”的特点,选择Laplace分布对边缘分布进行拟合。同时,利用前面得到的结论,选取拟合效果最好的两个Copula函数,组合生成一个新的混合Copula函数,从形式上看能够有效降低误选风险,保证最优Copula函数要求。将它与边缘分布函数结合构成联合分布函数,最终得到投资组合的分布函数。利用VaR的定义,计算出一天持有期内投资组合的VaR。从之后的返回检验结果来看,通过这一方法选择生成的Copula函数模型能够较好的度量组合风险。 Recently, with gradual penetration of the financial globalization, the finance risk management technology has developed violently. The VaR method which has been raised in 1990s, as a result of its good nature, is the most important and widely applied method of risk measurement. The Copula function can put the marginal distributions together to form a joint distribution. The dependence relationship is entirely determined by the Copula function, while statistical descriptions of each variable are entirely determined by the marginal. Copulas have become a popular multivariate modeling tool in many fields where the multivariate dependence is of great interest and the usual multivariate normality is in question. Copula gives a model for the dependence structure that reflects more detailed knowledge of the random variables than Conventional methods. So more and more scholars use Copula function to measure VaR and get good result. So far, the key problem of the Copula function in application is the choice of function form. Although some cultural literature once put forward a homologous suggestion for the choice problem of Copula function, this problem is not solved. According to this, in this paper, on the basis of research method nowadays, a kind of Bayesian Copula selection method is chosen so that the Copula parameters do not have to be estimated and the order of fitting results of different Copulas is got. Combine it with graphic method, research has been done on the Chinese Stock Market so that the best Copula is got. Furthermore, in this paper, as a result of the closing price has the characteristic of“sharp peak, fat tail”, we choose the Laplace distribution to be the marginal. Meanwhile use the best two Copulas which are got from the order of the fitting results before to form a new Copula called“Mixed-Copula”as the best Copula to reduce the risk of getting the wrong Copula. Put it together with Laplace distribution to get a multivariate distribution function. At last we get the portfolio at differ

关 键 词： 风险价值 函数 贝叶斯理论 混合 函数

领　　域： [经济管理] [经济管理]