학술논문

Quantum-inspired Computing: Entanglement-enhanced Technique for Short Portfolio in Global Markets
Document Type
Conference
Source
2023 IEEE 23rd International Conference on Nanotechnology (NANO) Nanotechnology (NANO), 2023 IEEE 23rd International Conference on. :534-538 Jul, 2023
Subject
Bioengineering
Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Quantum computing
Quantum entanglement
Computational modeling
Globalization
Market research
Quantum annealing
Portfolios
Language
ISSN
1944-9380
Abstract
Portfolio optimization is an essential aspect of the development of quantum computing. The quantum-inspired op-timization (QIO) algorithm facilitates an efficient search for the optimal solution by simulating quantum mechanics on a classical computer, thus bridging quantum theory and the actual implementation of quantum computing. This study proposes an entanglement-based QIO to optimize the short-selling portfolio in a group of seven (G7) industrialized nations, which are the world's largest markets and significantly impact global economies. To diversify investment options in response to the ever-changing markets, short-selling is a worthy topic for dis-cussion. The innovative trend ratio can precisely determine the performance of a short-selling portfolio during a stable downward trend. Implementing the short-selling trend ratio model in the significant G7 markets broadens its applicability.