摘要
在假定证券市场为有效竞争均衡市场的条件下,研究了连续时间不完全信息的M-V组合投资问题.首先引入基于不完全信息的M-V组合投资模型,在贝尔曼动态规划意义下将目标函数等价转化为可分离结构的函数,利用卡尔曼最优滤波估计,将不完全信息进行滤波转化为完全信息,从而通过求解相应的随机线性二次控制问题得到了最优投资策略和有效前沿.
On the assumption that stock market is effectively balanced and competitive, a study is carried out on the continuous-time portfolio selection with incomplete information. Firstly, the model of portfolio selection based on incomplete information is introduced. In the meaning of the Bellman dynamic programming, the object function is transformed into a separable structure, by using Kalman optimal filter estimation then, the case of the incomplete information is transformed into the case of complete information and the continuous-time portfolio selection with incomplete information model is solved by stochastic linear quadratic control. Finally the optimal strategies of portfolio seleotion and the efficient frontier are obtained.
出处
《上海电力学院学报》
CAS
2010年第3期300-304,共5页
Journal of Shanghai University of Electric Power
关键词
连续时间
不完全信息
滤波估计
随机线性二次控制
continuous-time
incomplete information
filter estimate
stochastic linear quadratic control
