TIME-INCONSISTENT MARKOVIAN CONTROL PROBLEMS UNDER MODEL UNCERTAINTY WITH APPLICATION TO THE MEAN-VARIANCE PORTFOLIO SELECTION

Bielecki Tomasz R.; Chen Tao; Cialenco Igor

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TIME-INCONSISTENT MARKOVIAN CONTROL PROBLEMS UNDER MODEL UNCERTAINTY WITH APPLICATION TO THE MEAN-VARIANCE PORTFOLIO SELECTION

机译：模型不确定性下的时间 - 不一致的马尔可夫控制问题与应用于平均方差组合选择

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摘要

In this paper, we study a class of time-inconsistent terminal Markovian control problems in discrete time subject to model uncertainty. We combine the concept of the sub-game perfect strategies with the adaptive robust stochastic control method to tackle the theoretical aspects of the considered stochastic control problem. Consequently, as an important application of the theoretical results and by applying a machine learning algorithm we solve numerically the mean-variance portfolio selection problem under the model uncertainty.

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来源
《International journal of theoretical and applied finance》 |2021年第1期|共28页
作者
Bielecki Tomasz R.; Chen Tao; Cialenco Igor;
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作者单位

IIT Dept Appl Math 10 W 32nd St Bldg RE Room 220 Chicago IL 60616 USA;

Univ Michigan Dept Math 530 Church St East Hall Room 2859 Ann Arbor MI 48109 USA;

IIT Dept Appl Math 10 W 32nd St Bldg RE Room 220 Chicago IL 60616 USA;

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原文格式 PDF
正文语种 eng
中图分类财政、金融;
关键词
Adaptive robust control; model uncertainty; stochastic control; adaptive robust dynamic programming; recursive confidence regions; time-inconsistent Markovian control problem; optimal portfolio allocation; mean-variance portfolio selection; terminal criteria; machine learning; Gaussian surrogate processes; regression Monte Carlo;

机译：自适应鲁棒控制;模型不确定度;随机控制;自适应稳健的动态规划;递归置信区;时间不一致的马尔可夫控制问题;最优投资组合分配;平均值 - 方差组合选择;终端标准;机器学习;高斯替代工艺;回归蒙特卡洛;

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4. A Nonlinear Interval Portfolio Selection Model and Its Application in Banks [J] . YAN Dawen, HU Yaxing, LAI Kin Keung 系统科学与复杂性：英文版 . 2018,第003期
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9. Estimation of expected returns, time consistency of a stock return model, and their application to portfolio selection. [D] . Ma, Huaqiang. 2010

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TIME-INCONSISTENT MARKOVIAN CONTROL PROBLEMS UNDER MODEL UNCERTAINTY WITH APPLICATION TO THE MEAN-VARIANCE PORTFOLIO SELECTION

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