Effective Approximation Methods for Constrained Utility Maximization with Drift Uncertainty

Abstract In this paper, we propose a novel and effective approximation method for finding the value function general utility maximization with closed convex control constraints partial information. Using separation principle weak duality relation, transform stochastic maximum of fully observable dual problem into an equivalent error minimization find tight lower upper bounds its approximate value. Numerical examples show goodness usefulness proposed method.