In this paper we study a continuous time, optimal stochastic investment
problem under limited resources in a market with N firms. The investment
processes are subject to a time-dependent stochastic constraint. Rather than
using a dynamic programming approach, we exploit the concavity of the profit
functional to derive some necessary and sufficient first order conditions for
the corresponding Social Planner optimal policy. Our conditions are a
stochastic infinite-dimensional generalization of the Kuhn-Tucker Theorem.
We study a stochastic, continuous-time model on a finite horizon for a firm
that produces one good utilizing production capacity (capital). We model the
capital as an Ito diffusion controlled by a nondecreasing process representing
the cumulative investment. The firm's optimal problem is to choose capital
investment in order to maximize its expected total net profit. We derive some
necessary and sufficient first order conditions for optimality and we
characterize the optimal solution of the investment problem in terms of the
"base capacity" process, i.e.