AI-Driven Stock Market Prediction Using Ensemble Learning and Investor Knowledge

This research explores a sophisticated AI approach for stock market index prediction by leveraging multiple data sources and investor-specific insights. The use of dynamic stacking ensemble learning suggests a potentially adaptable and robust model for forecasting.

• •Applies ensemble learning, a technique that combines multiple machine learning models to improve predictive accuracy.
• •Utilizes investor knowledge representations, which may incorporate sentiment analysis or other investor-related data.
• •Focuses on multi-source financial data, suggesting a data-driven approach leveraging various types of information.