Leveraging LlaMA 2 for sentiment analysis
This thesis investigates the application of sentiment analysis in predicting stock returns for the companies listed in the OMXS30 index. The recent development of large language models (LLMs), like ChatGPT, has substantially advanced the field of sentiment analysis. This thesis utilizes Meta’s LlaMA 2 LLM for sentiment analysis, while a random forest model is employed to predict monthly stock retu
