Constrained BSDEs representation of the value function in optimal control of pure jump Markov processes

Elena Bandini and Marco Fuhrman

Stochastic Processes and their Applications, 2017, vol. 127, issue 5, 1441-1474

Abstract: We consider a classical finite horizon optimal control problem for continuous-time pure jump Markov processes described by means of a rate transition measure depending on a control parameter and controlled by a feedback law. For this class of problems the value function can often be described as the unique solution to the corresponding Hamilton–Jacobi-Bellman equation. We prove a probabilistic representation for the value function, known as nonlinear Feynman–Kac formula. It relates the value function with a backward stochastic differential equation (BSDE) driven by a random measure and with a sign constraint on its martingale part. We also prove existence and uniqueness results for this class of constrained BSDEs. The connection of the control problem with the constrained BSDE uses a control randomization method recently developed by several authors. This approach also allows to prove that the value function of the original non-dominated control problem coincides with the value function of an auxiliary dominated control problem, expressed in terms of equivalent changes of probability measures.

Keywords: Backward stochastic differential equations; Optimal control problems; Pure jump Markov processes; Marked point processes; Randomization (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.spa.2016.08.005

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