Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1-8 |
| Number of pages | 8 |
| Journal | IEEE Nanotechnology Magazine |
| DOIs | |
| State | Published - 05 2024 |
Bibliographical note
Publisher Copyright:IEEE
Keywords
- Explainable artificial intelligence
- Investment
- Logic gates
- Market research
- Optimization
- Portfolios
- Standardization
- Training
- global cross-market
- portfolio optimization
- quantum-inspired algorithm
- trend ratio