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Effective Approximation Methods for Constrained Utility Maximization with Drift Uncertainty

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  • Dongmei Zhu

    (Southeast University)

  • Harry Zheng

    (Imperial College)

Abstract

In this paper, we propose a novel and effective approximation method for finding the value function for general utility maximization with closed convex control constraints and partial information. Using the separation principle and the weak duality relation, we transform the stochastic maximum principle of the fully observable dual control problem into an equivalent error minimization stochastic control problem and find the tight lower and upper bounds of the value function and its approximate value. Numerical examples show the goodness and usefulness of the proposed method.

Suggested Citation

  • Dongmei Zhu & Harry Zheng, 2022. "Effective Approximation Methods for Constrained Utility Maximization with Drift Uncertainty," Journal of Optimization Theory and Applications, Springer, vol. 194(1), pages 191-219, July.
    • Handle: RePEc:spr:joptap:v:194:y:2022:i:1:d:10.1007_s10957-022-02015-0
    DOI: 10.1007/s10957-022-02015-0
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    References listed on IDEAS

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    Cited by:

    1. Engel John C. Dela Vega & Harry Zheng, 2023. "Duality Method for Multidimensional Nonsmooth Constrained Linear Convex Stochastic Control," Journal of Optimization Theory and Applications, Springer, vol. 199(1), pages 80-111, October.

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