Market News Analyzer based on Large Language Models
N. Sunanda, Ponagandla Mahesh Reddy, Tarigopula Chaitanya, Velupula Saketh Ram, Vishwanatham Manvith, G. Vanaja Kumari · 2025
In today's fast-paced financial environment, being up-to-date with reliable and timely market information is crucial for making intelligent investment decisions. Yet, the sheer amount of frequent articles from various sources makes it difficult to glean valuable insights and measure their effects. This paper presents Market News Analyzer, an easy-to-use web tool that solves this problem by automating news aggregation, analysis, and summarization of financial information. The system collects news from trusted sources like Moneycontrol, Economic Times, Mint, and CNBC TV18, and uses natural language processing methods to ascertain the sentiment-positive, negative, or neutral-of each article with the TextBlob library. It improves user interaction by providing personalized elements such as stock watchlists, real-time price alerts, and natural language question-answering based on Google's Gemini large language model, allowing contextual insights from financial headlines. Market News Analyzer simplifies the decision-making process for users by transforming unstructured news into actionable intelligence in an interactive Streamlit-based interface and provides a scalable platform for future developments in AI-driven financial analytics.