Volume 18, No. 6, 2021
Stock Market Prediction Using Deep Learning
Anjani Kumar Singh , Chinmaya Nayak , Dr. Kirti Shukla , Suraj prakash
Abstract
In Stock Market Prediction, the end is to predict the unborn value of the fiscal stocks of a company. The recent trend in stock request Prediction technologies is the use of machine literacy which makes predictions hung on the values of current stock request indicators by training on their former values. In this design we're working on the stock request Prediction using LSTM (Long Short-Term Memory) with RNN ( intermittent neural network) function. We're using machine literacy algorithm neural network and LSTNN ( Long Short- Term Memory neural network) for bus-generating law and predicting crypto-currency. We'll train the data (supervised literacy) by taking the normal former data of stock requests and making it a successional function. This design will give 97 to 98 percent delicacy in the vaticination of crypto-currency, this will lead to huge profits in the business. The design will focus on the use of LSTM-based deep learning to predict stock values. Factors considered are open, close, low, high and volume.
Pages: 4686-4694
Keywords: LSTM, Vaticination, Deep Learning, data pre processing .