This study explores the application of sentiment analysis on financial news headlines to understand investor sentiment. By leveraging Natural Language Processing (NLP) and Large Language Models (LLM), the authors analyze sentiment from the perspective of retail investors using the FinancialPhraseBank dataset. They fine-tuned several models, including distilbert-base-uncased, Llama, and gemma-7b, to evaluate their effectiveness in sentiment classification. The experiments demonstrate that the fine-tuned gemma-7b model outperforms others, achieving the highest precision, recall, and F1-score. Specifically, the gemma-7b model showed significant improvements in accuracy after fine-tuning, indicating its robustness in capturing the nuances of financial sentiment. This model can provide valuable insights for market analysis, risk management, and investment decisions by accurately predicting the sentiment of financial news. The results highlight the potential of advanced LLMs in transforming how financial information is analyzed and interpreted, offering a powerful tool for stakeholders in the financial industry.This study explores the application of sentiment analysis on financial news headlines to understand investor sentiment. By leveraging Natural Language Processing (NLP) and Large Language Models (LLM), the authors analyze sentiment from the perspective of retail investors using the FinancialPhraseBank dataset. They fine-tuned several models, including distilbert-base-uncased, Llama, and gemma-7b, to evaluate their effectiveness in sentiment classification. The experiments demonstrate that the fine-tuned gemma-7b model outperforms others, achieving the highest precision, recall, and F1-score. Specifically, the gemma-7b model showed significant improvements in accuracy after fine-tuning, indicating its robustness in capturing the nuances of financial sentiment. This model can provide valuable insights for market analysis, risk management, and investment decisions by accurately predicting the sentiment of financial news. The results highlight the potential of advanced LLMs in transforming how financial information is analyzed and interpreted, offering a powerful tool for stakeholders in the financial industry.