Investor Sentiment

Investor sentiment analysis aims to understand how market participants feel about assets, using this information to predict market movements and improve investment strategies. Current research heavily utilizes Natural Language Processing (NLP) techniques, particularly deep learning models like BERT, XLNet, and fine-tuned LLMs, to analyze textual data from news articles, social media posts, and financial forums, often incorporating features like emojis and numerical data for enhanced accuracy. This field is significant because accurately gauging investor sentiment can improve financial forecasting, risk management, and portfolio optimization, offering valuable insights for both academics and practitioners.