SMAP - A Stock Market Analysis and Prediction Web Application

Abstract

The Stock Market is one of the most rapidly emerging markets in the country as the participation of retail investors has increased significantly in this pandemic.Since there are no specific rules to compute or predict the price of a stock, it becomes very difficult for the first-time investors to invest in the share market. Methodologies such as technical analysis, fundamental analysis, time series analysis, and statistical analysis, etc. are all used to estimate the price of the stocks but since stocks being volatile in nature, none of these methods are proved as a consistent tool to predict the upcoming trends. Machine learning and statistics can be used to predict and reduce the risk factor of loosing money. Apart from predicting future price trends based on the historical data of the company, the web app also show’s various decision making factors and fundamental indicators for providing multiple options to users for consideration while making a call. With the help of statistical analysis, the relation between the selected factors and share price is formulated for computing better results. Using facebook Prophet without any hyperparameter’s forecast for particular stocks are made. These result’s are evaluated by comparing with other models like Last value and prophet with hyperparameter tuning.