We propose a simulation-based approach for solving the constrained dynamic mean– variance portfolio managemen tproblem. For this dynamic optimization problem, we first consider a sub-optimal strategy, called the multi-stage strategy, which can be utilized in a forward fashion. Then, based on this fast yet sub-optimal strategy, we propose a backward recursive programming approach to improve it. We design the backward recursion algorithm such that the result is guaranteed to converge to a solution, which is at leas tas good as the one generated by the multi-stage strategy. In our numerical tests, highly satisfactory asset allocations are obtained for dynamic portfolio management problems with realistic constraints on the control variables
Journal of Economic Dynamics and Control
Scientific Computing

Cong, F., & Oosterlee, K. (2016). Multi-period mean–variance portfolio optimization based on Monte-Carlo simulation. Journal of Economic Dynamics and Control, 64, 23–38. doi:10.1016/j.jedc.2016.01.001