Sentiment-Driven Predictive Models for Nifty 50 Stock Market Fluctuations: A Time Series Analysis Perspective

This paper conducts a thorough semantic analysis of NIFTY-50 stock data, aiming to unravel the intricate dynamics of the Indian stock market. Employing a versatile blend of analytical and machine learning techniques, we delve into the historical performance of individual constituents of the NIFTY-50, seeking valuable insights into trends, patterns, and behavior. Special emphasis is placed on sentiment analysis, recognizing the crucial role of news, external factors, and market sentiment in influencing stock price movements. The utilization of time series forecasting techniques is a key aspect of our investigation, as these methods prove essential in financial analysis for accurate stock price predictions. This study underscores the significance of such techniques and their applicability to investors, financial analysts, and market participants. In essence, this paper serves as a valuable resource for anyone interested in navigating the complexities of the stock market. Our goal is to facilitate well-informed investment decisions and provide a foundation for further exploration in stock market analysis by incorporating a diverse range of techniques and approaches..