An Investigation on Quantum-Inspired Algorithms for Portfolio Optimization Across Global Markets

Yao Hsin Chou, Ming Ho Chang, Yu Chi Jiang, Shu Yu Kuo, Sun Yuan Kung, Bing J. Sheu

研究成果: 期刊稿件文章同行評審

摘要

Quantum-inspired algorithms have attracted considerable attention for their effective approach to addressing various optimization problems, drawing inspiration from quantum properties. This article introduces a portfolio recommendation system based on trend ratio and quantum-inspired optimization specifically designed for global cross-stock markets. The proposed intelligent portfolio optimization model excels at identifying strong, stable uptrends within individual markets and extends its effectiveness to cross-market analysis. Furthermore, this financial application prioritizes explainability and transparency, empowering investors to comprehend AI-generated results and, in turn, fostering trust in the proposed recommendation system. Results demonstrate its ability to accurately assess complex market relationships, reflect stock connections across countries, and highlight its robustness and reliability in explaining market performance.

原文英語
頁(從 - 到)1-8
頁數8
期刊IEEE Nanotechnology Magazine
DOIs
出版狀態已出版 - 05 2024

文獻附註

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IEEE

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