Global Data Quantum, a Spanish company, has added its Quantum Portfolio Optimizer software to IBM’s Qiskit Functions Catalog. This new application function was introduced at the IBM Quantum Partner Forum 2025 in London, enabling finance professionals to leverage quantum computing resources for investment strategy backtesting and dynamic portfolio optimization. This addition expands the catalog’s offerings, providing a dedicated tool for financial use cases at the 100+ qubit scale.
The Quantum Portfolio Optimizer is designed to abstract the complexities of quantum development, requiring only domain-specific inputs such as historical or expected asset prices. It translates this financial information into a problem formulated for quantum resolution, applying a Variational Quantum Eigensolver (VQE) algorithm to identify efficient investment combinations. The system then performs a post-processing adjustment to mitigate noise from current quantum devices, generating an optimized and robust recommendation. The function features ansatzes tailored for IBM Quantum Processing Units (QPUs) and differential evolution for enhanced efficiency.
This integration addresses the scalability limitations of traditional optimization methods in finance, which become slower and less efficient as the number of assets or constraints increases. By processing multiple variables in parallel using quantum resources, the Quantum Portfolio Optimizer aims to deliver faster and more effective solutions for complex financial problems. It makes quantum computing accessible to portfolio managers, analysts, and individual investors without requiring advanced quantum expertise, thereby enhancing investment performance while minimizing risks and transaction costs.
Read more about the new application functions on the IBM Quantum Blog here, access the Quantum Portfolio Optimizer in the Qiskit Functions Catalog here, and view Global Data Quantum’s press release here.
June 25, 2025
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