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arXiv · 2002.02604

Time-inconsistent Markovian control problems under model uncertainty with application to the mean-variance portfolio selection

Tomasz R. Bielecki·Tao Chen·Igor Cialenco
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Abstract

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 to tackle the theoretical aspects of the considered stochastic control problem. Consequently, as an important application of the theoretical results, by applying a machine learning algorithm we solve numerically the mean-variance portfolio selection problem under the model uncertainty.

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Tomasz R. Bielecki, Tao Chen, Igor Cialenco. 2020-02-07. Time-inconsistent Markovian control problems under model uncertainty with application to the mean-variance portfolio selection. https://arxiv.org/abs/2002.02604

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