Two-stage Dynamic Multi-period Portfolio Optimizations

This paper extends the traditional Markowitz’s mean-variance optimization to a two-stage dynamic multi-period portfolio optimization. The underlying assets time series data are supposed to follow a discrete time triangular cointegrated vector model, and in addition random quadratic transaction costs are taken into consideration. A twostage dynamic multi-period approach is proposed, and the optimal solution under the discussed model is analytically derived. Also, comparisons between a standard one-stage static approach and some two-stage approaches will be numerically examined under constructed data. The results indicate that the proposed two-stage dynamic method performs quite efficiently, and that higher net returns per risk can be expected.