Speaker：Lihua Bo (Nankai University)

Time：2021-06-21 14:30

Location：Tencent Meeting ID：291 554 938（No Password）

Abstract:

In this paper we investigate the optimal dividend problem under the reinforcement learning and continuous time entropy-regularized formulation. More precisely, we try to give the optimal dividend control when the state process is governed by a diffusion process under the reinforcement learning formulation. We use the viscosity solution method to prove existence and uniqueness of smooth solution of the Hamilton-Jacobi-Bellman equation and that the solution is bounded and concave. We show that the optimal control is no longer a threshold control, but a truncated distribution which has a ``gradual'' form. Then, we provide an example of this optimal control. Finally, we show that the condition of the verification theorem holds and the entropy-regularized stochastic control problem of dividend payment degenerates to the classical form.