  We investigate discrete-time mean-variance portfolio selection problems
viewed as a Markov decision process. We transform the problems into a new model
with deterministic transition function for which the Bellman optimality
equation holds. In this way, we can solve the problem recursively and obtain a
time-consistent solution, that is an optimal solution that meets the Bellman
optimality principle. We apply our technique for solving explicitly a more
general framework.
