Stock Market Price Prediction Using Machine Learning and Deep Learning

Abstract

This project aims to address the long-standing challenge of stock market prediction by leveraging the power of machine learning. The stock market is influenced by a multitude of factors, making it difficult for investors to accurately predict trends and make informed decisions. To mitigate this risk, we have chosen to analyse NSE real-time series data using the ARIMA model, a popular forecasting method. Our ultimate goal is to develop a user-friendly web application using Flask, which will allow investors to select a specific firm and receive a forecast for its future stock price. This application will utilize web scraping techniques to retrieve real-time data from the NSE, and the ARIMA model will be applied to predict future outcomes. By combining these powerful tools, we hope to significantly reduce the potential danger associated with stock market prediction and enable investors to make more informed decisions.