Hierarchical portfolio optimization using clustering and near-term quantum computers
US11809964B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 9, 2022 |
| Grant date | Nov 7, 2023 |
| Priority date | — |
| Expiry date | Dec 9, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods that address an optimized method to handle portfolio constraints such as integer budget constraints and solve portfolio optimization problems that map both to mixed binary and quadratic binary optimization problems. A digital processor is used to create a hierarchical clustering; this clustering is leveraged to allocate capital to sub-clusters of the hierarchy. Once the sub-clusters are sufficiently small, a quantum processor is used to solve the portfolio optimization problem. Thus, the innovation employs clustering to reduce an optimization problem to sub-problems that are sufficiently small enough to be solved using a quantum computer given available qubits.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.