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VaR方法的一种改进模型
供稿: 岳瑞峰;邵伟文 时间: 2019-05-06 次数:

作者:岳瑞峰;邵伟文

作者单位:北京林业大学中国科学院国家科学图书馆

摘要:VaR方法度量了在一定置信水平下资产可能的最大损失,指出了投资组合所面临的风险程度,但VaR方法并没有指出在何种比例下配置资产可以使得投资组合的VaR值最小.针对此问题,在德尔塔正态方法和蒙特卡罗模拟方法的基础上,提出了搜索化德尔塔方法,并利用证券市场的真实数据,与德尔塔正态方法的结论进行了对比分析.结果表明,搜索化德尔塔方法能够确定最优的投资比例,在此比例下,投资组合的VaR值达到最优.搜索化德尔塔方法可以帮助投资者合理地配置资产.

关键词:VaR方法;德尔塔正态方法;蒙特卡罗模拟;搜索化德尔塔方法;

DOI:10.16186/j.cnki.1673-9787.2006.06.023

分类号:F830;F224

Improved Model of VaR

Abstract:The method of VaR measurec the most loss of asset under a certain confidence level, and points out the risk that the investment portfolio faces, but it doesn't tell the rate under which the VaR value of investment portfolio is the least.To this problem, we post Delta-Search Method, on the basis of Delta-Normal Method and Monte Carlo Simulation Method, and apply the real data of security market to compare with the results of Delta-Normal Method.The results show that Delta-Search Method can identify the best investment rate.Under this rate, VaR value of investment portfolio is the best.Delta-Search Method can help investors to asset allocation appropriately.

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