Stock Market Data

Stock market data analysis aims to predict future stock price movements, leveraging both quantitative (historical price data, order flow) and qualitative (news sentiment, social media posts, annual reports) information. Current research heavily utilizes machine learning, employing models like LSTMs, CNNs, and large language models (LLMs) such as GPT variants, often integrated with techniques like sentiment analysis and graph neural networks to capture complex relationships between stocks and external factors. These advancements offer improved prediction accuracy and interpretability, potentially leading to more informed investment strategies and a deeper understanding of market dynamics.