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A Certainty Equivalent Merton Problem

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  • Nicholas Moehle
  • Stephen Boyd

Abstract

The Merton problem is the well-known stochastic control problem of choosing consumption over time, as well as an investment mix, to maximize expected constant relative risk aversion (CRRA) utility of consumption. Merton formulated the problem and provided an analytical solution in 1970; since then a number of extensions of the original formulation have been solved. In this note we identify a certainty equivalent problem, i.e., a deterministic optimal control problem with the same optimal value function and optimal policy, for the base Merton problem, as well as a number of extensions. When time is discretized, the certainty equivalent problem becomes a second-order cone program (SOCP), readily formulated and solved using domain specific languages for convex optimization. This makes it a good starting point for model predictive control, a policy that can handle extensions that are either too cumbersome or impossible to handle exactly using standard dynamic programming methods.

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  • Nicholas Moehle & Stephen Boyd, 2021. "A Certainty Equivalent Merton Problem," Papers 2101.10510, arXiv.org.
  • Handle: RePEc:arx:papers:2101.10510
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    References listed on IDEAS

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    1. Richard, Scott F., 1975. "Optimal consumption, portfolio and life insurance rules for an uncertain lived individual in a continuous time model," Journal of Financial Economics, Elsevier, vol. 2(2), pages 187-203, June.
    2. Stephen Boyd & Enzo Busseti & Steven Diamond & Ronald N. Kahn & Kwangmoo Koh & Peter Nystrup & Jan Speth, 2017. "Multi-Period Trading via Convex Optimization," Papers 1705.00109, arXiv.org.
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    Cited by:

    1. Steven Diamond & Stephen Boyd & David Greenberg & Mykel Kochenderfer & Andrew Ang, 2021. "Optimal Claiming of Social Security Benefits," Papers 2106.00125, arXiv.org.

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