On optimal control of mean-field stochastic systems driven by Teugels martingales via derivative with respect to measures

Abstract

This paper deals with partial information stochastic optimal control problem for general controlled mean-field systems driven by Teugels martingales associated with some Levy process having moments of all orders and an independent Brownian motion. The coefficients of the system depend on the state of the solution process as well as of its probability law and the control variable. We establish a set of necessary conditions in the form of Pontryagin maximum principle for the optimal control. We also give additional conditions under which the necessary optimality conditions turn out to be sufficient. The proof of our result is based on the derivative with respect to the probability law by applying Lions derivatives and a corresponding Ito formula. As an application conditional mean-variance portfolio selection problem in incomplete market where the system is governed by some Gamma process is studied to illustrate our theoretical results.