Dynamic programming principle and Hamilton-Jacobi-Bellman equation under nonlinear expectation
Mingshang Hu, Shaolin Ji, Xiaojuan Li
Abstract
Open-access reader
Mingshang Hu, Shaolin Ji, Xiaojuan Li
Abstract
Open-access reader
In this paper, we study a stochastic recursive optimal control problem in which the value functional is defined by the solution of a backward stochastic differential equation (BSDE) under $\tilde{G}$-expectation. Under standard assumptions, we establish the comparison theorem for this kind of BSDE and give a novel and simple method to obtain the dynamic programming principle. Finally, we prove that the value function is the unique viscosity solution of a type of fully nonlinear HJB equation.
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In this paper, we study a stochastic recursive optimal control problem in which the value functional is defined by the solution of a backward stochastic differential equation (BSDE) under $\tilde{G}$-expectation. Under standard assumptions, we establish the comparison theorem for this kind of BSDE and give a novel and simple method to obtain the dynamic programming principle. Finally, we prove that the value function is the unique viscosity solution of a type of fully nonlinear HJB equation.
Key concepts: Hamilton–Jacobi–Bellman equation, Bellman equation, Dynamic programming, Viscosity solution, Mathematics, Nonlinear system, Simple (philosophy), Applied mathematics