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What is Enhancing Stock Market Prediction With Hybrid Deep about?

This article presents a hybrid deep learning framework for stock market prediction that integrates LSTM networks, Transformer attention mechanisms, sentiment analysis, and Federated Learning. The proposed model outperforms traditional forecasting methods, achieving an average R2 variance score of 0.91 across ten major technology companies, highlighting its effectiveness in capturing temporal dependencies and market sentiment. This work addresses privacy concerns by enabling decentralized model training with

Author

Maryam Zahra

Language

EN