TIME-INCONSISTENT MARKOVIAN CONTROL PROBLEMS UNDER MODEL UNCERTAINTY WITH APPLICATION TO THE MEAN-VARIANCE PORTFOLIO SELECTION
TIME-INCONSISTENT MARKOVIAN CONTROL PROBLEMS UNDER MODEL UNCERTAINTY WITH APPLICATION TO THE MEAN-VARIANCE PORTFOLIO SELECTION
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DOI：
10.1142/s0219024921500035
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发表时间：
2020-02
影响因子：
0.5
通讯作者：
T. Bielecki;Tao Chen;Igor Cialenco
中科院分区：
文献类型：
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作者：
T. Bielecki;Tao Chen;Igor Cialenco
本文研究了一类具有模型不确定性的离散时间不一致终端马尔可夫控制问题。我们结合联合收割机的子博弈完美策略的概念，自适应鲁棒随机控制方法来解决所考虑的随机控制问题的理论方面。因此，作为理论结果的一个重要应用，我们应用机器学习算法数值求解了模型不确定性下的均值-方差投资组合选择问题。
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.