Portfolio Optimization in the Chilean Pension System: Alternatives and Challenges

Abstract

This thesis aims to describe the problem that a saver belonging to the Chilean pension system faces when allocating asset during the period before to retiring. Through this paper it is illustrated the performance and risk metrics of different portfolio allocations, such as: the naive portfolio allocation (1/n), tangency portfolio, global minimum variance and portfolio choice under quadratic preferences. For this case different degrees of risk aversion has been used . The analysis was extended by allowing short selling, using different sample size to estimate portfolio weights, and comparing different optimization frequencies (static versus monthly rebalancing). The results suggests that portfolio re-balancing generates improvements in terms of performance compared to static optimization. However, some of the main drawbacks of Markowitz portfolio type optimization were detected, these are related to: 1) dramatic portfolio changes when inputs change lightly. 2) Highly concentrated portfolios, in most cases, less than five assets concentrate more than 90% of the portfolio—3) low out-of-sample performance. As a way to mitigate the negative consequences of Markowitz optimization, a novel algorithm was implemented. The Hierarchical Risk Parity method which generate portfolio allocations that are relatively stable through time, high out-of-sample performance (compared to GMVP), and a high level of diversification. These characteristics are desirable in a system as the Chilean one, where portfolio re-balancing is costly, and with low levels of financial literacy, this factor has been link with savers little involvement in investment choices