AgentPEN: A Prediction-Explanation Network for Sequential Stock Movement via LLMs and Recurrent Generation

AgentPEN is a system that uses large language models (LLMs, AI systems trained on massive text data) to predict stock price movements while explaining why those predictions are made. The system works by combining financial news data with stock price information through a special agent that selects relevant news, remembers important information over time and across different sources, and then predicts stock movements based on the combined insights.