Advancing Stock Price Forecasting: Exploring Methods, Models & Literature

Abstract

In stock market prediction, aim is to identify future values of different financial stocks of companies. This research paper delves into the dynamic and challenging domain of stock price forecasting, that aims to Participate to existing body of knowledge by introducing a comprehensive analysis of methods, model building flow, and pertinent literature. By introducing the situation, this section emphasizes the difficulties posed by the intrinsic variability of financial markets as well as the crucial role that precise stock price forecasts play in financial decision-making. A key component of financial market is stock price forecasting that offers experts in finance & investors able to take wise investment decisions. This research paper explores the latest advancements, methodologies, and challenges in stock price forecasting. The paper systematically explores various forecasting methods, ranging from traditional time series analysis to advanced machine learning techniques. Understanding each method's advantages and disadvantages is emphasized, providing readers with a nuanced perspective on the applicability of different approaches in different market conditions.