Open AccessVisualizing and Forecasting Stocks Using Machine Learning
Author(s) -
Ajitkumar Jagtap,
Yash Patil,
Darshan Oswal
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.41846
Subject(s) - stock market prediction , stock (firearms) , stock market , artificial neural network , computer science , artificial intelligence , machine learning , econometrics , economics , engineering , mechanical engineering , paleontology , horse , biology
India's stock market is exceedingly changing and reductionism, which has a countless number of features that control the directions and trends of the stock price; therefore, prediction of uptrend and downtrend is a complex process. This paper point of view to demonstrate the use of recurrent neural network in finance to prediction of the closing price of a selected stock and analyse opinions around it in real-time. By combining both techniques, the submitted model can give buy or sell recommendation. In Stock Market Prediction, the aim is to predict the upcoming future value of the financial stocks of the company. The latest trend in stock market prediction technologies is the use of machine learning which makes predictions depending on the values of current stock market indices by training on their previous stock values. Machine learning itself use different models to make prediction easier and authentic. The paper focuses on the use of Regression and LSTM based Machine learning to prediction of stock values. Factors for stocks considered are open, close, low, high and volume. Keywords: Machine learning, Stock Market, Long Short-Term Memory, Recurrent Neural Network.