Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer
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Abstract (arXiv)
We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We derive a formulation of the problem, discuss several possible integer encoding schemes, and present numerical examples that show high success rates. The formulation incorporates transaction costs (including permanent and temporary market impact), and, significantly, the solution does not require the inversion of a covariance matrix. The discrete multi-period portfolio optimization problem we solve is significantly harder than the continuous variable problem. We present insight into how results may be improved using suitable software enhancements, and why current quantum annealing technology limits the size of problem that can be successfully solved today. The formulation presented is specifically designed to be scalable, with the expectation that as quantum annealing technology improves, larger problems will be solvable using the same techniques.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Aug 2015.
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Citing papers per year: 2021: 2; 2022: 3; 2023: 0; 2024: 1; 2025: 2; 2026: 4.
12 papers.
- 2022Application of QUBO solver using black-box optimization to structural design for resonance avoidancecited by 17
- 2022Penalty Weights in QUBO Formulations: Permutation Problemscited by 9
- 2022Black-box optimization for integer-variable problems using Ising machines and factorization machinescited by 8
- 2021Quantum Machine Learning for Financecited by 7
- 2021Assessment of image generation by quantum annealercited by 2
- 2025Relaxation-assisted reverse annealing on nonnegative/binary matrix factorizationcited by 1
- 2024Quantum-Inspired Machine Learning for Molecular Dockingcited by 0
- 2025Large-scale portfolio optimization with variational neural annealingcited by 0
- 2026Variational Quantum Circuit-Based Reinforcement Learning for Dynamic Portfolio Optimizationcited by 0
- 2026A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisationcited by 0
- 2026Benchmarking Quantum Algorithmic Resilience for CVaR Portfolio Optimization: The Expressibility-Coherence Trade-offcited by 0
- 2026A Novel Hybrid Quantum Reservoir Computing (nHQRC) for Phase Transition Detection in Non-Equilibrium Dynamical Systemscited by 0
- 2026A Novel Hybrid Quantum Reservoir Computing (nHQRC) for Phase Transition Detection in Non-Equilibrium Dynamical Systems9 Jul 2026
- 2026Benchmarking Quantum Algorithmic Resilience for CVaR Portfolio Optimization: The Expressibility-Coherence Trade-off5 Jun 2026
- 2026A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation15 May 2026
- 2026Variational Quantum Circuit-Based Reinforcement Learning for Dynamic Portfolio Optimization20 Jan 2026
- 2025Large-scale portfolio optimization with variational neural annealing9 Jul 2025
- 2025Relaxation-assisted reverse annealing on nonnegative/binary matrix factorization3 Jan 2025
- 2024Quantum-Inspired Machine Learning for Molecular Docking22 Jan 2024
- 2022Black-box optimization for integer-variable problems using Ising machines and factorization machines1 Sep 2022
- 2022Penalty Weights in QUBO Formulations: Permutation Problems20 Jun 2022
- 2022Application of QUBO solver using black-box optimization to structural design for resonance avoidance11 Apr 2022
- 2021Quantum Machine Learning for Finance9 Sep 2021
- 2021Assessment of image generation by quantum annealer15 Mar 2021