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Self-Consistent Adjoint Policy Iteration for Constrained Dynamic Portfolio Choice

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Listed:
  • Jeonggyu Huh
  • Yeoneung Kim
  • Seungwon Jeong

Abstract

We develop simulation-based policy iteration for continuous-time portfolio choice with predictable returns and convex constraints. Each outer step re-evaluates a fixed-latent open-loop backpropagation-through-time (OL-BPTT) adjoint after deployment and solves the constrained update. Shifted-adjoint cancellation controls the adjoint--HJB Hamiltonian-gradient discrepancy by the policy-improvement residual. For CRRA portfolios, exact HJB policy iteration identifies the optimal reduced value factor, while population OL-BPTT iteration converges globally when the adjoint update is directionally improving and approximate stationarity is asymptotically HJB-compatible. A theorem-matched occupation audit yields maximal $95\%$ upper endpoints of $0.066$ for the primitive directional ratio and $0.074$ for a stronger norm-relative ratio, both against the half-step threshold $0.75$. In the high-precision $50$--$50$ occupancy/broad-anchor design of a three-factor, fifty-asset benchmark, current-policy re-evaluation outperforms matched pooled refinement under the on-policy and broad evaluation laws.

Suggested Citation

  • Jeonggyu Huh & Yeoneung Kim & Seungwon Jeong, 2026. "Self-Consistent Adjoint Policy Iteration for Constrained Dynamic Portfolio Choice," Papers 2608.17808, arXiv.org, revised Sep 2026.
    • Handle: RePEc:arx:papers:2608.17808
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    References listed on IDEAS

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    1. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    2. Kim, Tong Suk & Omberg, Edward, 1996. "Dynamic Nonmyopic Portfolio Behavior," The Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 141-161.
    3. Jun Liu, 2007. "Portfolio Selection in Stochastic Environments," The Review of Financial Studies, Society for Financial Studies, vol. 20(1), pages 1-39, January.
    4. Yanwei Jia & Xun Yu Zhou, 2021. "Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach," Papers 2108.06655, arXiv.org, revised Feb 2022.
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