Stock Market Prediction Analysis using Deep Learning

Abstract

The abstract provides an overview of a proposed approach for stock market value prediction using deep learning techniques, specifically focusing on artificial neural networks (ANN) and long-short-term memory (LSTM) algorithms. The stock market is a dynamic environment influenced by various factors, such as economic conditions and market sentiment, making accurate prediction challenging yet crucial for investors.In this study, the objective is to leverage deep learning methodologies to enhance the accuracy and robustness of stock market predictions compared to traditional methods. By harnessingthe Python programming language, the research aims to develop a model capable of analyzing historical stock data and generating forecasts of future stock prices