关于开放式基金VaR风险的比较——基于半参数与非参数法
发布时间：2018-11-21 07:06
【摘要】：在刻画和估计资产联合损失分布函数的基础上对开放式基金VaR风险进行比较分析。在极值情况下有两种算法:一种是半参数法,采用GPD分布来拟合损失分布的尾部和核密度分布拟合损失分布的中间部分,运用copula函数来刻画资产损失的相依结构;另一种是非参数法,用Bootstrapping和FHS方法对收益率进行抽样和模拟。经过实证分析发现在较低置信水平下,宜于采用非参数法;而在较高置信水平下,采用半参数法则更合适,这也充分说明半参数法适合在更极值情形下对开放式基金估计VaR风险。
[Abstract]:On the basis of characterizing and estimating the joint loss distribution function of assets, this paper makes a comparative analysis on the VaR risk of open-end funds. There are two algorithms under extreme value: one is semi-parametric method, which uses GPD distribution to fit the tail of loss distribution and kernel density distribution to fit the middle part of loss distribution, and uses copula function to describe the dependent structure of asset loss; The other is non-parametric method, which uses Bootstrapping and FHS to sample and simulate the return rate. Through the empirical analysis, it is found that the nonparametric method is suitable for the lower confidence level. In the case of higher confidence level, it is more appropriate to adopt the semi-parametric rule, which fully shows that the semi-parametric method is suitable for estimating the VaR risk of open-end funds under the condition of more extreme value.
【作者单位】： 四川大学经济学院;华侨大学经济与金融学院;
【基金】：教育部人文社科基金资助项目(09XJC90007)
【分类号】：F224;F830.9
[Abstract]:On the basis of characterizing and estimating the joint loss distribution function of assets, this paper makes a comparative analysis on the VaR risk of open-end funds. There are two algorithms under extreme value: one is semi-parametric method, which uses GPD distribution to fit the tail of loss distribution and kernel density distribution to fit the middle part of loss distribution, and uses copula function to describe the dependent structure of asset loss; The other is non-parametric method, which uses Bootstrapping and FHS to sample and simulate the return rate. Through the empirical analysis, it is found that the nonparametric method is suitable for the lower confidence level. In the case of higher confidence level, it is more appropriate to adopt the semi-parametric rule, which fully shows that the semi-parametric method is suitable for estimating the VaR risk of open-end funds under the condition of more extreme value.
【作者单位】： 四川大学经济学院;华侨大学经济与金融学院;
【基金】：教育部人文社科基金资助项目(09XJC90007)
【分类号】：F224;F830.9
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相关期刊论文 前1条
1 陈小红;何浩;;开放式基金的VaR值测算与评估——基于GARCH模型的实证分析[J];武汉金融;2006年08期
【共引文献】
相关硕士学位论文 前5条
1 朱s搕，
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