New research from IBM and Vanguard explores how quantum computing can be used for portfolio construction, one of the most computationally demanding problems in finance. The study, detailed in a paper on arXiv, demonstrates that a quantum-classical hybrid workflow has the potential to provide solutions on par with purely classical methods for complex financial optimization tasks.
The team used a sampling-based Variational Quantum Algorithm (VQA) on an IBM Quantum Heron r1 processor with up to 109 qubits and up to 4,200 gates. The quantum samples were then refined using a classical local search algorithm. The study found that for a bond Exchange Traded Fund (ETF) portfolio construction problem, the quantum-classical workflow consistently outperformed a purely classical local search approach, especially as problem size increased. The solution achieved a relative solution error of 0.49%.
This study is positioned as a step forward for the application of quantum computing to real-world financial problems. It suggests that quantum hardware can contribute to solving simplified versions of practical optimization tasks and that hybrid workflows could eventually be integrated into the daily operations of financial professionals. Paul Malloy, Vanguard head of municipals, noted that the team successfully constructed a bond portfolio at a scale exceeding their original expectations.
Read the full announcement in the IBM Quantum blog post here, the Vanguard corporate article here, and the arXiv paper here.
September 30, 2025
