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中国管理科学

中国管理科学 ›› 2011, Vol. 19 ›› Issue (4): 54-59.

• 论文 • 上一篇    下一篇

基于贝叶斯随机规划方法的养老保险基金投资策略研究

何大义1, 高建伟2   

  1. 1. 中国地质大学(北京)人文经管学院, 北京 100083;
    2. 华北电力大学工商管理学院, 北京 102206
  • 收稿日期:2010-01-19 修回日期:2011-06-06 出版日期:2011-08-30 发布日期:2011-08-30
  • 作者简介:何大义(1973- ),男(汉族),四川成都人,中国地质大学人文经管学院,博士,讲师,研究方向:风险决策理论与方法.
  • 基金资助:

    国家自然科学基金资助项目(70971039);中央高校基本科研业务费专项资金资助项目(09MR46)

Research of Investment Strategy of Pension Fund Based on the Bayesian Stochastic Programming Approach

HE Da-yi GAO Jian-wei1   

  1. 1. School of Humanities and Economics Management, China University of Geosciences(Beijing), Beijing 100083, China;
    2. School of Business Administration, North China Electronic Power University, Beijing 102206, China
  • Received:2010-01-19 Revised:2011-06-06 Online:2011-08-30 Published:2011-08-30

PDF (PC)

1380

被引次数

48

摘要： 结合中国养老保险基金投资现状,利用随机规划建立中国养老基金投资策略模型,依据Minnesota法则改进贝叶斯向量自回归参数分布的确定方法.根据改进的贝叶斯向量自回归模型生成资本市场未来收益情景,得到养老基金最优投资策略并给出模拟计算具体步骤.最后结合历史数据进行模拟分析,结果表明模型能够根据实际情况优化资产配置.

关键词: 随机规划, 投资策略, 贝叶斯向量自回归

Abstract: In this paper,according to the China pension fund situation,we develop the optimization dynamic investment strategy models based on the Bayesian stochastic programming approach,in which we improve the Bayesian vector autoregressive by using the Minnesota Prior.According to the improved model,we estimate the asset future returns and give the concreted calculation steps for solving the models.Finally and combining with the historical data,we conduct a simulation,the result shows that the optimal investment strategy can be solved according to the reality.

Key words: stochastic programming, investment strategy, Bayesian vector autoregressive

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