Research Area:  Machine Learning
Stock market data is a time-series data in which stock value varies depends on time. Prediction of the stock market is an endeavor to assess the future value of a companys stock rate which will increase the investors profit. The accurate prediction of stock market analysis is still a challenging task. The proposed system predicts stock price of any company mentioned by the user for the next few days. Using the predicted stock price and datasets collected from various sources regarding a certain equity, the overall sentiment of the stock is predicted. The prediction of stock price is done by regression and candlestick pattern detection. The proposed system generates signals on the candlestick graph which allows to predict market movement to a sufficient level of accuracy so that the user is able to judge whether a stock is a Buy/Sell and whether to short the stock or go long by delivery. The prediction accuracy of the stock exchange has analyzed and improved to 85% using machine learning algorithms.
Author(s) Name:  M. Ananthi & K. Vijayakumar
Journal name:  Journal of Ambient Intelligence and Humanized Computing
Publisher name:  Springer
Volume Information:  volume 12, pages 4819–4826 (2021)
Paper Link:   https://link.springer.com/article/10.1007/s12652-020-01892-5