On optimal control of mean-field stochastic systems driven by Teugels martingales via derivative with respect to measures
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Date
2020
Authors
Mokhtar Hafayed
Shahlar Meherrem
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor and Francis Ltd. michael.wagreich@univie.ac.at
Open Access Color
Green Open Access
Yes
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Publicly Funded
No
Abstract
This paper deals with partial information stochastic optimal control problem for general controlled mean-field systems driven by Teugels martingales associated with some Lévy process having moments of all orders and an independent Brownian motion. The coefficients of the system depend on the state of the solution process as well as of its probability law and the control variable. We establish a set of necessary conditions in the form of Pontryagin maximum principle for the optimal control. We also give additional conditions under which the necessary optimality conditions turn out to be sufficient. The proof of our result is based on the derivative with respect to the probability law by applying Lions derivatives and a corresponding Itô formula. As an application conditional mean-variance portfolio selection problem in incomplete market where the system is governed by some Gamma process is studied to illustrate our theoretical results. © 2020 Elsevier B.V. All rights reserved.
Description
Keywords
Derivative With Respect To Measures, Lévy Process, Maximum Principle, Stochastic Control, Stochastic Differential Equations Of Mean-field Type, Teugels Martingales, Brownian Movement, Maximum Principle, Optimal Control Systems, Stochastic Systems, Conditional Means, Incomplete Markets, Mean Field, Necessary Optimality Condition, Partial Information, Stochastic Control, Stochastic Optimal Control Problem, Teugels Martingale, Stochastic Control Systems, Brownian movement, Maximum principle, Optimal control systems, Stochastic systems, Conditional means, Incomplete markets, Mean field, Necessary optimality condition, Partial information, Stochastic control, Stochastic optimal control problem, Teugels martingale, Stochastic control systems
Fields of Science
0209 industrial biotechnology, 02 engineering and technology
Citation
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OpenCitations Citation Count
5
Source
International Journal of Control
Volume
93
Issue
Start Page
1053
End Page
1062
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Scopus : 5
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Mendeley Readers : 2
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