Imagine having a crystal ball for the stock market. While that remains a fantasy, researchers are exploring how Large Language Models (LLMs), the brains behind AI chatbots, could help us predict market trends. It turns out that LLMs have a knack for analyzing both numbers (like stock prices) and text (like analyst reports). The challenge? Figuring out how to make sense of the qualitative insights LLMs generate. This new research tackles this problem by feeding daily analyst reports and market data to LLMs, essentially creating a constantly updated snapshot of market conditions. The trick is to convert the LLM’s textual analysis into quantifiable scores using a clever prompting technique. This transforms complex textual insights into numerical predictions. Early experiments show promise: LLMs outperformed traditional time-series models, especially in short-term predictions. However, the research also highlights challenges. Ensuring these AI-powered predictions are reliable and consistent remains a hurdle. Plus, understanding *why* the LLM made a specific prediction is still tricky. This research opens exciting doors for using LLMs in finance. Imagine AI helping us understand market sentiment and predict trends with greater accuracy. While there are hurdles to overcome, this research lays the foundation for a future where AI plays a key role in financial markets.