Stock Price Prediction

Stock price prediction aims to forecast future stock market movements, a complex task with significant implications for investment strategies. Current research heavily emphasizes the integration of diverse data sources, including fundamental financial data, social media sentiment, and macroeconomic indicators, into sophisticated prediction models. Popular model architectures include Long Short-Term Memory networks (LSTMs), transformers, graph neural networks, and hybrid approaches combining these techniques, often enhanced by feature selection and ensemble methods. Improved accuracy and the development of more interpretable models remain key objectives, with potential benefits for both academic understanding of market dynamics and practical applications in portfolio management and algorithmic trading.