Abstract

Investors planning for retirement balance three Ls: (1) lifestyle risk, hoping to maintain a consumption stream that provides a chosen standard of living; (2) longevity risk, hoping to remain solvent throughout their lifetime; and (3) legacy risk, hoping to leave a bequest to their heirs. We solve this multiple objective problem for a wide range of consumption and annuitization scenarios. For each scenario, we apply dynamic programming to optimally evolve the investments in the non-annuitized portion of the portfolio so as to minimize longevity risk. Our dynamic programming approach has the advantages of (1) generating results that are far superior to what standard Monte Carlo methods, static portfolios, and target date fund glide paths can provide and (2) not requiring utility functions, which are hard to specify for individuals. We show that investors who want to minimize their longevity and legacy risk and who are unable to annuitize their full consumption stream are best off avoiding even partial annuitization of their portfolio. For investors who are able to annuitize their full consumption stream, we quantify their longevity versus legacy risk trade-offs, enabling them to select the best annuity for their needs.

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