摘要翻译：
经典的基于动态规划的最优随机控制方法无法处理不可分离的动态优化问题，因为最优性原理在这种情况下不再适用。在这些众所周知的不可分离问题中，动态均值-方差组合选择公式直到最近才给我们的研究界带来了巨大的挑战。在过去的十年里，包括嵌入方案在内的几种求解方法已经成功地解决了动态均值-方差组合选择公式。本文提出了一种新的均值场框架，为直接解决多期均值-方差型投资组合问题的不可分离性问题和解析推导最优策略提供了一种更有效的建模工具和更精确的求解方案。
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英文标题：
《Unified Framework of Mean-Field Formulations for Optimal Multi-period
  Mean-Variance Portfolio Selection》
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作者：
Xiangyu Cui, Xun Li, Duan Li
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最新提交年份：
2013
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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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英文摘要：
  The classical dynamic programming-based optimal stochastic control methods fail to cope with nonseparable dynamic optimization problems as the principle of optimality no longer applies in such situations. Among these notorious nonseparable problems, the dynamic mean-variance portfolio selection formulation had posted a great challenge to our research community until recently. A few solution methods, including the embedding scheme, have been developed in the last decade to solve the dynamic mean-variance portfolio selection formulation successfully. We propose in this paper a novel mean-field framework that offers a more efficient modeling tool and a more accurate solution scheme in tackling directly the issue of nonseparability and deriving the optimal policies analytically for the multi-period mean-variance-type portfolio selection problems.
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PDF链接：
https://arxiv.org/pdf/1303.1064