英文标题：
《Mean-variance portfolio selection under partial information with drift
uncertainty》
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作者：
Jie Xiong, Zuo quan Xu and Jiayu Zheng
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最新提交年份：
2020
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英文摘要：
In this paper, we study the mean-variance portfolio selection problem under partial information with drift uncertainty. First we show that the market model is complete even in this case while the information is not complete and the drift is uncertain. Then, the optimal strategy based on partial information is derived, which reduces to solving a related backward stochastic differential equation (BSDE). Finally, we propose an efficient numerical scheme to approximate the optimal portfolio that is the solution of the BSDE mentioned above. Malliavin calculus and the particle representation play important roles in this scheme.
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中文摘要：
本文研究了具有漂移不确定性的部分信息下的均值-方差投资组合选择问题。首先，我们证明了即使在这种情况下，当信息不完整且漂移不确定时，市场模型也是完整的。然后，导出了基于部分信息的最优策略，该策略归结为求解相关的倒向随机微分方程（BSDE）。最后，我们提出了一种有效的数值格式来逼近最优投资组合，即上述BSDE的解。Malliavin微积分和粒子表示在该方案中起着重要作用。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Portfolio Management 项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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一级分类：Mathematics 数学
二级分类：Optimization and Control 优化与控制
分类描述：Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学，线性规划，控制论，系统论，最优控制，博弈论
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一级分类：Mathematics 数学
二级分类：Probability 概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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