Multi-Period Mean-Variance Portfolio Selection with Regime-Switching
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Science and Engineering
School of Electrical Engineering, Computing and Mathematical Sciences
This thesis studies the multi-period mean-variance portfolio selection under regime-switching with two kinds of constraints: uncertain time horizon and special market conditions. The thesis uses dynamic programming approach to obtain the optimal investment strategies and the corresponding efficient frontiers. Some special cases and numerical analysis are used to illustrate the effect of different factors on the efficient frontiers.