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
Null option (theme 11)
Elsevier
dx.doi.org/10.1016/j.jedc.2016.01.001
Journal of Economic Dynamics and Control
Scientific Computing

Cong, F, & Oosterlee, C.W. (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