Hybrid computer system for asset selection optimization
A hybrid classical-quantum system addresses the inefficiencies of classical methods in portfolio selection by using a quantum circuit to optimize asset combinations, resulting in faster and more efficient computational solutions.
WO2025123180A1 Publication Date: 2025-06-19HSBC SOFTWARE DEV (GUANGDONG) LTD
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Patent Information
- Application Number
- PCT/CN2023/137935
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2023-12-11
- Publication Date
- 2025-06-19
AI Technical Summary
Technical Problem
Classical computational methods for portfolio selection, such as Monte Carlo Simulation, are computationally intensive and inefficient in solving complex optimization problems.
Method used
A computer-implemented method using a hybrid classical-quantum system to perform asset selection optimization, involving the generation of a quantum circuit with modules for parameter loading, portfolio loading, computation, and quantum estimation to find the optimal asset combination that minimizes or maximizes a selection metric.
Benefits of technology
The method significantly reduces computational complexity and time by leveraging quantum computing to efficiently identify optimal asset combinations, thereby improving the efficiency of portfolio selection processes.
✦ Generated by Eureka AI based on patent content.
Abstract
A computer-implemented method for performing asset selection is disclosed, using asset data comprising asset parameters defining a plurality of assets. The method generates control data defining a quantum circuit having a plurality of circuit modules, including a parameter loading module arranged to encode the asset parameters of the plurality of assets onto a set of qubits of a quantum computer and a portfolio loading module arranged to encode a set of possible asset combinations as a superposition of a further set of qubits of the quantum computer, each asset combination corresponding to a selection of one or more of the plurality of assets. The circuit modules further include a computation module for calculating a portfolio selection metric based on the asset parameters and the possible asset combinations, wherein the computation module is arranged to produce a quantum superposition state of the quantum computer that corresponds to values of the selection metric for each of the asset combinations encoded by the portfolio loading module, and a quantum estimation module arranged to perform quantum estimation to find an optimal value in the superposition state that corresponds to an optimal value of the selection metric. The control data defining the quantum circuit is transmitted to the quantum computer for execution. The method then identifies from an output of the quantum computer the asset combination of the set of possible asset combinations that corresponds to the optimal selection metric value identified by the quantum estimation module and generates an output specifying the identified asset combination.
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