Simple Allocation Rules and Optimal Portfolio Choice Over the Lifecycle
In many areas of economics, relatively simple models developed for insight are used as quantitative guides to behavior. In this paper, we develop a machine-learning algorithm to solve for optimal portfolio choice in a complex, calibrated lifecycle model that includes many features of reality modeled only separately in previous work. The average optimal portfolio share invested in stocks declines with age, consistent both with age-dependent rules derived from simpler models and with implicit advice embedded in current lifecycle investment products. But optimal portfolios decline more evenly, slowly, and by less than in current lifecycle products, and have substantial heterogeneity, particularly by wealth level and expected equity premium, implying significant gains to further customization in these dimensions. Together these two factors imply gains from moving to optimal portfolios of up to 3.5 to 3.7 percent of average consumption.
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Copy CitationVictor Duarte, Julia Fonseca, Aaron S. Goodman, and Jonathan A. Parker, "Simple Allocation Rules and Optimal Portfolio Choice Over the Lifecycle," NBER Working Paper 29559 (2021), https://doi.org/10.3386/w29559.Download Citation
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