Quantum-inspired Financial Optimization for Dynamic G7 Portfolio Management [Feature]

View at publisher
Authors: Yao–Hsin Chou, Yun-Ting Lai, Yu-Chi Jiang, Shu-Yu Kuo, Sun-Yuan Kung
Cited by: 0
References: 44

Abstract

Quantum finance has recently attracted significant attention for its potential to enhance investment strategies.This work introduces an entanglement-enhanced quantum-inspired optimization (QIO) system for dynamic portfolio management across the global Group of Seven (G7) markets. A comprehensive analysis is conducted over both training and testing phases to demonstrate the system’s robustness and practical utility in real-world financial scenarios. Extensive experiments validate its profitability under various sliding window configurations across different markets. The results reveal both shared patterns and distinct differences among G7 countries. In addition, the system’s performance under volatile market conditions, particularly during the COVID-19 pandemic, is examined to highlight its resilience and adaptability. These findings underscore the practical value of QIO-based systems for adaptive portfolio management in complex, interconnected markets and suggest promising directions for future research in cross-market analysis and advanced optimization strategies.

Fields of Study & Subjects

Quantum Computing Algorithms and Architecture Stock Market Forecasting Methods Risk and Portfolio Optimization

Publication details

Journal / source
IEEE Nanotechnology Magazine
Volume
20
Issue
1
Pages
22–31
Publication date
5 January 2026