Deep Learning for Dynamic Programming with Recursive Utility

arXiv:2607.04278 · q-fin.CP, cs.LG, econ.EM, math.OC, stat.ML · Submitted 2026-07-05 · Read on arXiv

Xianhua Peng, Wu Guo

q-fin.CP, cs.LG, econ.EM, math.OC, stat.ML

Submitted: 2026-07-05

Comments: 93 pages, 44 figures

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 111× in this paper · explained in 2 episodes
• Accuracy — 29× in this paper · explained in 1 episode
• Robustness — 29× in this paper · explained in 6 episodes
• Adam — 9× in this paper · explained in 3 episodes
• Consistency — 8× in this paper · explained in 3 episodes
• Reinforcement Learning — 8× in this paper · explained in 4 episodes
• Certainty Equivalent Learning — 5× in this paper
• Training Objective — 5× in this paper · explained in 3 episodes
• Training Objectives — 5× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 3× in this paper · explained in 3 episodes
• Calibration — 2× in this paper · explained in 9 episodes
• Curse of Dimensionality — 2× in this paper · explained in 6 episodes
• Feedback Loop — 2× in this paper · explained in 2 episodes
• Fixed Point — 2× in this paper · explained in 2 episodes
• Monotonicity — 2× in this paper · explained in 2 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Stochastic Dynamics — 2× in this paper · explained in 3 episodes
• Composition — 1× in this paper · explained in 2 episodes
• Computational Efficiency — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Evaluation Framework — 1× in this paper · explained in 3 episodes
• Generator — 1× in this paper · explained in 2 episodes
• Hysteresis — 1× in this paper · explained in 3 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Modular Architecture — 1× in this paper · explained in 4 episodes
• Neural Network Approximation — 1× in this paper · explained in 2 episodes
• Papers — 1× in this paper · explained in 3 episodes
• Uncertainty Quantification — 1× in this paper · explained in 9 episodes
• Unsupervised Learning — 1× in this paper · explained in 2 episodes

Sources

• Economics-Inspired Neural Networks with Stabilizing Homotopies
• Numerical Solution of Dynamic Portfolio Optimization with Transaction Costs
• Optimal consumption and portfolio selection with Epstein-Zin utility under general constraints
• Consumption-investment optimization with Epstein-Zin utility in unbounded non-Markovian markets
• Non-linear approximations of DSGE models with neural-networks and hard-constraints
• DeepHAM: A Global Solution Method for Heterogeneous Agent Models with Aggregate Shocks
• Stochastic dynamic programming under recursive Epstein-Zin preferences
• Deep Learning for Solving and Estimating Dynamic Models in Economics and Finance

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