Quantum Portfolio Optimization Benchmark
QAOA / VQE / Quantum Annealing · Optimization · Qiskit Finance, PennyLane, D-Wave Ocean
Finance-specific benchmark evaluating quantum optimization algorithms for Markowitz mean-variance portfolio selection. Compares QAOA, VQE, and quantum annealing against classical solvers (MIP, meta-heuristics) on asset selection and allocation problems. Recent studies find classical mixed-integer programming and problem-tailored heuristics significantly outperform the quantum approaches at fixed time budgets — instances of up to 1,000 assets solve to proven optimality in seconds — leaving "only very limited room for a potential quantum advantage" on this problem variant.
3 credible sources · last verified 6 months ago
Finance-specific benchmark evaluating quantum optimization algorithms for Markowitz mean-variance portfolio selection. Compares QAOA, VQE, and quantum annealing against classical solvers (MIP, meta-heuristics) on asset selection and allocation problems. Recent studies find classical mixed-integer programming and problem-tailored heuristics significantly outperform the quantum approaches at fixed time budgets — instances of up to 1,000 assets solve to proven optimality in seconds — leaving "only very limited room for a potential quantum advantage" on this problem variant.
Sets a concrete classical baseline for quantum finance claims: on mean-variance portfolio selection, classical solvers currently dominate, and quantum-produced portfolios may additionally violate practical financial constraints.
Multi-platform
Qiskit Finance, PennyLane, D-Wave Ocean
3 of 3 count toward the source bar · last read 6 months ago (2026-03-19)