INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Stock price prediction is always a most challenging task. Stock price prediction helps in identifying the decision before investing on different companies. In nature, stock market is multidimensional. Stock market price prediction is necessary for getting profit and investment of companies. The various attributes related in change of market price values are economic, political, and human. Many intelligent networks are available to predict the price. Still there is a need a for new prediction to optimize the stock index price. Artificial Neural Network LSTM has been applied in many different domains with success. LSTM generalized and applied in learned base of example. LSTM helps the better prediction to forecast the closing stock price. Neural network offers the capacity to determine the outlines in market prediction. LSTM prediction clears the stock price forecasting challenge by forming the training set. LSTM techniques are used to form the prediction of different variables. LSTM is one of the best techniques used for analyzing the historical dataset. Historical information in the network input is used to get the expected output of the network. This approach advances in predicting the best future stock price by forming training and testing set.
Keywords:
Keywords: Machine Learning, Stock Price Prediction, Long Short- Term Memory, Stock Market, Artificial neural Networks, National Stock Exchange
Cite Article:
"STOCK PRICE PREDICTION USING LSTM", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.1270 - 1277, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303207.pdf
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Publication Details:
Published Paper ID: IJSDR2303207
Registration ID:204811
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 1270 - 1277
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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