On robust multi-period pre-commitment and time-consistent mean-variance portfolio optimization
We consider robust pre-commitment and time-consistent mean-variance optimal asset allocation strategies, that are required to perform well also in a worst-case scenario regarding the development of the asset price. We show that worst-case scenarios for both strategies can be found by solving a specific equation each time step. In the unconstrained asset allocation case, the robust pre-commitment as well as the time-consistent strategy are identical to the corresponding robust myopic strategies, by which investors perform robust portfolio control only for one time step and conduct a risk-free strategy afterwards. In the experiments, the robustness of pre-commitment and time-consistent strategies is studied in detail. Our analysis and numerical results indicate that the time-consistent allocation strategy is more stable when possible incorrect assumptions regarding the future asset development are modeled and taken into account. In some situations, the time-consistent strategy can even generate higher efficient frontiers than the pre-commitment strategy (which is counter-intuitive), because the time-consistency restriction appears to protect an investor in such a situation
|Keywords||Robust optimization, mean-variance optimal asset allocation, target-based strategy, time-consistent strategy, model prediction error|
|Journal||International Journal of Theoretical and Applied Finance|
Cong, F, & Oosterlee, C.W. (2017). On robust multi-period pre-commitment and time-consistent mean-variance portfolio optimization. International Journal of Theoretical and Applied Finance, 20(7), 1750049‐1–1750049‐2.