Target date funds: a goal-based wealth approach with random labour income

Abstract

Target date funds (TDF) are mutual funds with an asset allocation following a downward glide path in the proportion of stocks as a target retirement date becomes closer. Here, we compare the wealth outcomes of a typical downward glide path of TDFs with the wealth outcomes of an adaptive goal-based wealth management (GBWM) allocation strategy, which accounts for the investor's financial position. For this purpose, we extend the GBWM models of Das, Ostrov, Radhakrishnan, and Srivastav (2018) and (2020), where the investor maximizes the probability of reaching a goal, to the context of an individual earning a random labour income. With bootstrapped data from several stocks and bond indices, we document and compare the distribution of wealth outcomes of the models with those from other approaches in the context of a long-term investor with a target retirement date. Our results suggest that in terms of goal achievement, a goal-based wealth investor focusing on the probability of reaching a goal does better than the typical target date fund or a conventional mean-variance investor. The GBWM allocation strategy changes the wealth distribution with a much lower standard deviation and a more significant frequency of ending wealth around the goal, but a lower frequency of large ending wealth. We also show that maximizing the probability of reaching a goal using a static approach is just as effective as a dynamic approach. The static method is more straightforward and requires fewer computational resources. Maximizing the probability of reaching the goal can thus be done simply and swiftly with the static approach.