Large-scale portfolio optimization with variational neural annealing

arXiv:2507.07159 · cond-mat.dis-nn, cond-mat.stat-mech, cs.LG, q-fin.PM · Submitted 2025-07-09 · Read on arXiv

cond-mat.dis-nn, cond-mat.stat-mech, cs.LG, q-fin.PM

Submitted: 2025-07-09

Updated: 2025-07-09

Comments: 16 pages, 13 figures, 1 table

Journal ref: Phys. Rev. E 114, 024311 (2026)

DOI: 10.1103/p22k-x7p6

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

Terminology

• Objective Function — 26× in this paper · explained in 2 episodes
• Variational Neural Annealing — 11× in this paper
• Benchmark — 7× in this paper · explained in 2 episodes
• Combinatorial Optimization — 7× in this paper · explained in 2 episodes
• Recurrent Neural Network — 7× in this paper
• Classical Optimization — 4× in this paper
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 2× in this paper · explained in 2 episodes
• Modern Portfolio Theory — 2× in this paper
• Quantum Approximate Optimization Algorithm — 2× in this paper
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Phase Transitions — 1× in this paper · explained in 2 episodes
• Quadratic Unconstrained Binary Optimization — 1× in this paper
• Reward Function — 1× in this paper · explained in 2 episodes
• Topological Order — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Quantum Portfolio Optimization with Investment Bands and Target Volatility
• Wasserstein Solution Quality and the Quantum Approximate Optimization Algorithm: A Portfolio Optimization Case Study
• A Quantum Approximate Optimization Algorithm
• Branch-and-bound digitized counterdiabatic quantum optimization
• Solving the Optimal Trading Trajectory Problem Using Simulated Bifurcation
• Large Language Models in Finance: A Survey
• StockGPT: A GenAI Model for Stock Prediction and Trading
• Advancing Investment Frontiers: Industry-grade Deep Reinforcement Learning for Portfolio Optimization
• Lattice Protein Folding with Variational Annealing
• From Deep Learning to LLMs: A survey of AI in Quantitative Investment
• MILLION: A General Multi-Objective Framework with Controllable Risk for Portfolio Management
• Recurrent neural network wave functions for Rydberg atom arrays on kagome lattice
• Leveraging recurrence in neural network wavefunctions for large-scale simulations of Heisenberg antiferromagnets on the triangular lattice
• Iterative Retraining of Quantum Spin Models Using Recurrent Neural Networks
• Pushing the Boundary of Quantum Advantage in Hard Combinatorial Optimization with Probabilistic Computers
• Learning Constrained Optimization with Deep Augmented Lagrangian Methods
• An adaptive augmented Lagrangian method for training physics and equality constrained artificial neural networks

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