Combining Investment and Tax Strategies for Optimizing Lifetime Solvency under Uncertain Returns and Mortality

Sanjiv Das (), Daniel Ostrov, Aviva Casanova, Anand Radhakrishnan and Deep Srivastav
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Daniel Ostrov: Department of Mathematics and Computer Science, Santa Clara University, Santa Clara, CA 95053, USA
Aviva Casanova: Franklin Templeton, San Mateo, CA 95670, USA
Anand Radhakrishnan: Franklin Templeton, San Mateo, CA 95670, USA
Deep Srivastav: Franklin Templeton, San Mateo, CA 95670, USA

JRFM, 2021, vol. 14, issue 7, 1-25

Abstract: This paper considers investors who are looking to maximize their probability of remaining solvent throughout their lifetime by using an algorithm that aims to optimize their investment allocation strategy and optimize their tax strategy for withdrawal allocations between tax deferred accounts (TDAs), Roth accounts, and taxable stock and bond accounts. This optimization works with stochastic investment returns and stochastic mortality, extending and combining different investment and tax-efficiency paradigms. We find that optimizing the investment strategy has a much larger impact on the investor remaining solvent than optimizing the tax strategy. This result is key to effectively optimizing both strategies simultaneously. This optimized investment strategy soundly beats a standard target date fund strategy, and the novel optimized tax strategy displays optimal desired properties suggested by non-stochastic tax optimization research.

Keywords: goals-based wealth management; dynamic programming; retirement planning; taxes; Monte Carlo methods; mortality; optimal strategy; tax deferred accounts; Roth accounts; taxable accounts (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2021
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