Goal-Based Portfolios - A mean-variance optimization approach with subportfolios -

Abstract

This thesis analysis the goal-based portfolio optimization approach and compares it to established theories of portfolio management. First, we review previous literature on the topic of portfolio optimization. Second, we identify the investor’s problem and define the methodology. Further, we perform a quantitative analysis of the goal-based portfolio optimization approach. We use historical asset returns to simulate future portfolio outcomes and analyse the performance of an investment according to goal-based portfolio theory. We find that by dividing an investment into multiple subportfolios, and optimizing each subportfolio separately, decreases the portfolios probability of failure. We conclude that an investor, with specific goals beyond attaining highest possible return, is better off investing in subportfolios as opposed to a single portfolio.