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On stochastic maximum principle for risk-sensitive of fully coupled forward-backward stochastic control of mean-field type with application

  • * Corresponding author: Adel Chala

    * Corresponding author: Adel Chala 

The first author is supported by PRFU project N: C00L03UN070120180002

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  • In this paper, we are concerned with an optimal control problem where the system is driven by fully coupled forward-backward stochastic differential equation of mean-field type with risk-sensitive performance functional. We study the risk-neutral model for which an optimal solution exists as a preliminary step. This is an extension of the initial stochastic control problem in this type of risk-sensitive performance problem, where an admissible set of controls are convex. We establish necessary as well as sufficient optimality conditions for the risk-sensitive performance functional control problem. Finally, we illustrate our main result of this paper by giving two examples of risk-sensitive control problem under linear stochastic dynamics with exponential quadratic cost function, the second example will be a mean-variance portfolio with a recursive utility functional optimization problem involving optimal control. The explicit expression of the optimal portfolio selection strategy is obtained in the state feedback.

    Mathematics Subject Classification: Primary: 93E20, 60H30; Secondary: 60H10, 91B28.


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  • [1] D. Andersson and B. Djehiche, A maximum principle for SDEs of mean-field type, Appl. Math. Optim., 63 (2011), 341-356.  doi: 10.1007/s00245-010-9123-8.
    [2] F. Armerin, Aspects of cash flow valuation, Ph.D thesis, Kungliga Tekniska Hogskolan (Sweden), 2004,116 pp.
    [3] R. BuckdahnB. Djehiche and J. Li, A general stochastic maximum principle for SDEs of mean-field type, Appl. Math. Optim., 64 (2011), 197-216.  doi: 10.1007/s00245-011-9136-y.
    [4] R. BuckdahnJ. Li and S. Peng, Mean-field backward stochastic differential equations and related partial differential equations, Stochastic Process. Appl., 119 (2009), 3133-3154.  doi: 10.1016/j.spa.2009.05.002.
    [5] R. BuckdahnB. DjehicheJ. Li and S. Peng, Mean-field backward stochastic differential equations: A limit approach, Ann. Probab., 37 (2009), 1524-1565.  doi: 10.1214/08-AOP442.
    [6] R. Carmona and F. Delarue, Mean-field forward-backward stochastic differential equations, Electron. Commun. Probab., 18 (2013), 15pp. doi: 10.1214/ECP.v18-2446.
    [7] A. Chala, Pontryagin's risk-sensitive stochastic maximum principle for backward stochastic differential equations with application, Bull. Braz. Math. Soc. (N. S.), 48 (2017), 399-411.  doi: 10.1007/s00574-017-0031-2.
    [8] A. Chala, Sufficient optimality condition for a risk-sensitive control problem for backward stochastic differential equations and an application, J. Numer. Math. Stoch., 09 (2017), 48-60. 
    [9] A. Chala, D. Hafayed and R. Khallout, The use of Girsanov's theorem to describe the risk-sensitive problem and application to optimal control, in Stochastic Differential Equation-Basics and Applications, Nova Science Publishers, Inc., 2018,111–142.
    [10] B. DjehicheH. Tembine and R. Tempone, A stochastic maximum principle for risk-sensitive mean-field type control, IEEE Trans. Automat. Control, 60 (2015), 2640-2649.  doi: 10.1109/TAC.2015.2406973.
    [11] N. El-Karoui and S. Hamadène, BSDEs and risk-sensitive control, zero-sum and nonzero-sum game problems of stochastic functional differential equations, Stochastic Process. Appl., 107 (2003), 145-169.  doi: 10.1016/S0304-4149(03)00059-0.
    [12] D. Hafayed and A. Chala, An optimal control of a risk-sensitive problem for backward doubly stochastic differential equations with applications, Random Operators and Stochastic Equation, published online, (2020). doi: 10.1515/rose-2020-2024.
    [13] Y. Hu, B. Øksendal and A. Sulem, Singular mean-field control games with applications to optimal harvesting and investment problems, preprint, arXiv: 1406.1863, (2014).
    [14] J. M. Lasry and P. L. Lions, Mean-field games, Jpn. J. Math., 02 (2007), 229-260.  doi: 10.1007/s11537-007-0657-8.
    [15] J. Li, Stochastic maximum principle in the mean-field controls, Automatica J. IFAC, 48 (2012), 366-373.  doi: 10.1016/j.automatica.2011.11.006.
    [16] A. E. B. Lim and X. Y. Zhou, A new risk-sensitive maximum principle, IEEE Trans. Automat. Control, 50 (2005), 958-966.  doi: 10.1109/TAC.2005.851441.
    [17] T. Meyer-BrandisB. Øksendal and X. Y. Zhou, A mean-field stochastic maximum principle via Malliavin calculus, Stochastics, 84 (2012), 643-666.  doi: 10.1080/17442508.2011.651619.
    [18] H. Min, Y. Peng and Y. Qin, Fully coupled mean-field forward-backward stochastic differential equations and stochastic maximum principle, Abstr. Appl. Anal., 2014 (2014), Art. ID 839467, 15 pp. doi: 10.1155/2014/839467.
    [19] J. Shi and Z. Wu, A risk-sensitive stochastic maximum principle for optimal control of jump diffusions and its applications, Acta Math. Sci. Ser. B (Engl. Ed.), 31 (2011), 419-433.  doi: 10.1016/S0252-9602(11)60242-7.
    [20] J. Shi and Z. Wu, Maximum principle for risk-sensitive stochastic optimal control problem and applications to finance, Stoch. Anal. Appl., 30 (2012), 997-1018.  doi: 10.1080/07362994.2012.727138.
    [21] A. S. Sznitman, Topics in propagation of chaos, in In Ecole d'Été de Probabilités de Saint-Flour XIX–1989, Springer, Berlin, 1991,165–251. doi: 10.1007/BFb0085169.
    [22] H. Tembine, Risk-sensitive mean-field-type games with Lp-norm drifts, Automatica J. IFAC, 59 (2015), 224-237.  doi: 10.1016/j.automatica.2015.06.036.
    [23] J. Yong, A stochastic linear quadratic optimal control problem with generalized expectation, Stoch. Anal. Appl., 26 (2008), 1136-1160.  doi: 10.1080/07362990802286533.
    [24] J. Yong and X. Y. Zhou, Stochastic Controls: Hamiltonian Systems and HJB Equations, Springer-Verlag, New York, 1999. doi: 10.1007/978-1-4612-1466-3.
    [25] X. Y. Zhou and D. Li, Continuous-time mean-variance portfolio selection: A stochastic LQ framework, Appl. Math. Optim., 42 (2000), 19-33.  doi: 10.1007/s002450010003.
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