DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
||||||||
Issue |
Volume-11,Issue-9 ( Sep, 2023 ) | |||||||||
Paper Title |
Stock Market Prediction Using Machine Learning Techniques | |||||||||
Author Name |
Rocky Kumar, Shivam Dubey, Rahul Kumar, Alok Singh Chauhan | |||||||||
Affilition |
||||||||||
Pages |
57-62 | |||||||||
Abstract |
In this research, we are trying to use machine learning techniques to predict stock price. Machine learning has been successfully used in stock price prediction. The goal is to assess the product's value and utilize this information to make well-informed investment decisions. We propose a product price estimation system that includes math, machine learning and other external tools to get better product prediction and post market value. There are two types of products. You may be familiar with day trading from the term "day trading". Day traders hold positions in securities from at least one day to the next, usually days to weeks or months. LSTMs are very powerful in forecasting problems due to their ability to store historical data. This is important in our case because the past price of a stock is important in predicting its future price. Although predicting the true price of a stock is a difficult process, we can build a model to predict whether the price will rise or fall. Keywords - LSTM, CNN, ML, DL, Open Market, Closed Market, Low Market, Highmarket | |||||||||
| View Paper | ||||||||||
