We report a dynamic programming algorithm which, given a set of efficient (or even inefficient) portfolios, constructs an optimal portfolio trading strategy that maximizes the probability of attaining an investor’s specified target wealth at the end of a designated time horizon. Our algorithm also accommodates periodic infusions or withdrawals of cash with no degradation to the dynamic portfolio’s performance or runtime. We explore the sensitivity of the terminal wealth distribution to restricting the segment of the efficient frontier available to the investor. Since our algorithm’s optimal strategy can be on the efficient frontier and is driven by an investor’s wealth and goals, it soundly beats the performance of target date funds in attaining investors’ goals. These optimal goals-based wealth management strategies are useful for independent financial advisors to implement behavioral-based FinTech offerings and for robo-advisors.
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The three index funds used are (i) Vanguard Total Bond Market II Index Fund Investor Shares (VTBIX), representative of U.S. Fixed Income (Intermediate-Term Bond), (ii) Vanguard Total International Stock Index Fund Investor Shares (VGTSX), representative of Global Equity (Large Cap Blend), (iii) Vanguard Total Stock Market Index Fund Investor Shares (VTSMX), representative of U.S. Equity (Large Cap Blend). These three funds have been chosen only as representatives of their respective asset categories for illustrative purposes.
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We are grateful for discussions and contributions from many of the team at Franklin Templeton Investments.
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Das, S.R., Ostrov, D., Radhakrishnan, A. et al. Dynamic portfolio allocation in goals-based wealth management. Comput Manag Sci 17, 613–640 (2020). https://doi.org/10.1007/s10287-019-00351-7
- Wealth management
- Behavioral portfolio theory
- Dynamic portfolios
- Efficient portfolios