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

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 sto...

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Veröffentlicht in:	International journal of theoretical and applied finance 2021-02, Vol.24 (1), p.2150003
Hauptverfasser:	BIELECKI, TOMASZ R., CHEN, TAO, CIALENCO, IGOR
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Discrete time Machine learning Markov analysis Portfolio management Stochastic control theory Uncertainty
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container_title	International journal of theoretical and applied finance
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description	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.
doi_str_mv	10.1142/S0219024921500035
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subjects	Algorithms Discrete time Machine learning Markov analysis Portfolio management Stochastic control theory Uncertainty
title	TIME-INCONSISTENT MARKOVIAN CONTROL PROBLEMS UNDER MODEL UNCERTAINTY WITH APPLICATION TO THE MEAN-VARIANCE PORTFOLIO SELECTION
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