Agenda

We develop a dynamic programming methodology to maximize investor outcomes over multiple goals. Our algorithm optimally chooses whether or not to cash-out a part of the portfolio to implement a sequence of goals (such as upgrading a home, college fees, an income stream in retirement, etc.). We may also optimally choose to implement partial goals. Our model is able to solve a problem over a huge number of goals, something that is infeasible with Monte Carlo approaches currently in use by practitioners in the wealth management industry.

There is a growing retirement crisis and most of the focus has been on the fact that individuals are not saving enough for retirement, may not have access to pension schemes, and find it difficult to choose from a wide range of retirement products. One solution that has been considered is to improve access to Reverse Mortgages (RMs) so that individuals can convert their (possibly) single largest asset into a through-death income stream. However, current RMs are complex with constraints on who can use them, and with multiple parties to the transaction to hedge residual risks. As a result, a limited number of institutions (and that too with government support) offer such products. These challenges may have also limited the use of RMs for the typical individual saving for retirement and are unlikely to solve the larger crisis. We suggest a new approach - “Retire In-Home” (Retire through Income from one’s Home) - that leverages recently proposed tradeable instruments to improve retirement security and hedge against standard-of-living risks. These include a bond called BFFS/SeLFIES, designed to secure real retirement income for a fixed term (with potentially a second new bond, called a LIVE bond, designed to protect individuals against longevity risk if individuals do not want to purchase deferred annuities because of annuity challenges). Further, the paper also shows how a new investor segment could be tapped to expand financing for such transactions as recommended by Prof. Robert C. Merton.

This paper demonstrates how Retire In-Home could simplify this market and allow even the most financially unsophisticated individual to participate in this transaction. The paper works through three cases: (a) when death is known (or a term income); (b) when longevity risk is hedged with deferred annuities; and (c) when longevity risk is hedged with LIVE Bonds. The paper concludes with extensions including accounting for up-front lumpsum payments, forward-starting contracts and even multi-occupant situations.

Using a proprietary dataset of the portfolio holdings of millions of anonymized households with trillions in wealth, we test the central tenet of rational-expectations theories of asset pricing and portfolio choice – that agents believe in a common model and update their beliefs identically in response to public signals – against alternative theories in which agents hold different models of the world and update beliefs heterogeneously. We identify households that ex ante are likely to believe in different models of the world using political party affiliation (probabilistically inferred from zip code), and our public signal is the unexpected outcome of the US election of November 2016. Relative to Democrats, Republican investors actively increase the share of equity and market beta of their portfolios following the election. Inconsistent with the effect being driven by differences in hedging needs with common beliefs, the results are robust to controls for age, wealth, income, state, and even county-employer fixed effects.