Abstract

Abstract: This report would look at both conventional and modern stock market forecasting methods. We use three distinct methodologies to solve the problem: fundamental analysis, technical analysis, and machine learning. We find support for a weak version of the Efficient Market Hypothesis, which states that while historical prices are meaningless, out-of-sample data can predict future prices. We show how Fundamental Analysis and Machine Learning can assist investors in making better investment decisions. We show how Technical Analysis has a flaw and provides insufficiently usable data. Based on our findings, Quantopian is used to develop and model algorithmic trading programmes. This article makes use of the concepts of stock estimation, data analysis, natural language processing, and machine learning.Keywords:-Stock Prediction, Data Analysis, Natural Language Processing, Machine Learning.