Veljanovska, Kostandina and Nalovski, Simeon and Ristevski, Blagoj and Savoska, Snezana (2025) Stock Trading Recommendations Using Deep Q-learning and NLP. In: 17th International conference ICT Innovations, October 11-13, 2025.
Full text not available from this repository.Abstract
This paper explores the application of deep Q-learning and natural lan-guage processing (NLP) to the stock market trading process. Deep Q-learning, a method that is part of reinforcement learning, is used to create trading strategies based on historical data and technical indicators, aiming to optimize long-term returns through intelligent decision-making. Natural language processing techniques are applied to analyze financial news and social media content to extract sentiment and relevant stock market trends. By investigating the two approaches separately, the research aims to evaluate their effectiveness in predicting stock market trends and making informed decisions, offering a basis for future integration of the two approaches into a single financial system.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering |
| Divisions: | Faculty of Information and Communication Technologies |
| Depositing User: | Prof. d-r. Kostandina Veljanovska |
| Date Deposited: | 09 Mar 2026 01:25 |
| Last Modified: | 09 Mar 2026 01:25 |
| URI: | https://eprints.uklo.edu.mk/id/eprint/11418 |
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