Quantum Portfolio Optimization Benchmark

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 highlight that while quantum methods minimize cost functions effectively, resulting portfolios may violate practical financial constraints.[1]

  • Algorithm: QAOA / VQE / Quantum Annealing
  • Category: optimization
  • Framework: Qiskit Finance, PennyLane, D-Wave Ocean
  • Reproducible: Yes
  • Published:
  • finance
  • portfolio
  • QAOA
  • VQE
  • quantum-annealing
  • Markowitz

What algorithm does Quantum Portfolio Optimization Benchmark use?

Quantum Portfolio Optimization Benchmark uses the QAOA / VQE / Quantum Annealing algorithm, categorized under optimization.

Frequently Asked Questions

What is the Quantum Portfolio Optimization Benchmark benchmark?

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 highlight that while quantum methods minimize cost functions effectively, resulting portfolios may violate practical financial constraints.

Is Quantum Portfolio Optimization Benchmark reproducible?

Yes, this benchmark is reproducible.

Sources

  1. "Quantum Portfolio Optimization: An Extensive Benchmark", accessed 2026-03-19 — arXiv
  2. "PO-QA: A Framework for Portfolio Optimization using Quantum Algorithms", accessed 2026-03-19 — arXiv