Abstract
We propose a simulation-based approach for solving the constrained dynamic mean-variance portfolio management problem. 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 least as 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.
Original language | English |
---|---|
Pages (from-to) | 23-38 |
Number of pages | 16 |
Journal | Journal of Economic Dynamics and Control |
Volume | 64 |
DOIs | |
Publication status | Published - 2016 |
Keywords
- Constrained optimization
- Dynamic portfolio management
- Least squares regression
- Mean-variance optimization
- Simulation method