This project explores the performance of fine-tuning OpenAI’s GPT-3.5 Turbo for stock price forecasting. Experiments on Bigdata22 and CIKM18 show that fine-tuning improves model's accuracy and F1-score. However, performance still lags behind traditional models, highlighting the need for further domain-specific tuning in financial NLP. - View it on GitHub