AI-Powered Stock Market Forecasting: A Hybrid Approach
Analysis
This research explores a novel approach to stock market forecasting by combining news sentiment with time series data using Graph Neural Networks. The integration of diverse data sources could potentially lead to more accurate and robust predictions.
Key Takeaways
- •Hybrid models leverage both qualitative (news sentiment) and quantitative (time series) data.
- •Graph Neural Networks (GNNs) are utilized for processing relationships between data points.
- •This approach aims to improve forecasting accuracy in the stock market.
Reference
“The study integrates news sentiment and time series data with Graph Neural Networks.”