Maximum principle for a Markovian regime switching system under model uncertainty

Abstract

In this paper, we study a stochastic optimal control problem with a Markovian regime switching system, where the coefficients of the state equation and the cost functional are uncertain. First, we obtain the variational inequality by showing the continuity with respect to the uncertainty parameter of the variational equation, which is characterized as forward-backward stochastic differential equations. Second, using the linearization method and weak convergence technique, we prove the necessary stochastic maximum principle and show the sufficient condition of the stochastic optimal control. Finally, as an application, a risk-minimizing portfolio selection problem is studied. Meanwhile, the $L^\beta$-solution and $L^\beta$-estimate of stochastic differential equations with regime switching are given for \b=2k with $k\in \mathbb{N}$.Comment: 37 Page