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CCF Seminar

Timeslot

Song Yao
University of Pittsburgh
Title: Optimal Stopping with Expectation Constraint

Abstract: We will discuss an optimal stopping problem for a diffusion state variable with a constraint on the expected cost. When the reward function and cost function are Lipschitz continuous in state variable, we show that the value of such an optimal stopping problem is a continuous function in current state and in budget level. Then we derive a dynamic programming principle (DPP) for the value function in which the conditional expected cost acts as an additional state process. As the optimal stopping problem with expectation constraint can be transformed to a stochastic optimization problem with supermartingale controls, we explore a second DPP of the value function. Based on these two DPPs, we characterize the value function as a viscosity solution to the related fully non-linear parabolic Hamilton-Jacobi-Bellman equation.

Date: Monday, December 4, 2017
Time: 4:30 pm
Location: Wean Hall 8220
Submitted by:  Johannes Muhle-Karbe