STOCK PRICE PREDICTION USING LSTM

S.Subasree , J.R.vasan , S.Anandnarayanan , S.Arvindan , N.Moganarangan

Keywords: Machine Learning, Stock Price Prediction, Long Short- Term Memory, Stock Market, Artificial neural Networks, National Stock Exchange

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.

Published Paper   E-Certificate

"STOCK PRICE PREDICTION USING LSTM", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 3, page no.1270 - 1277, March-2023, Available :https://ijsdr.org/papers/IJSDR2303207.pdf

Volume 8 Issue 3, March-2023

Pages : 1270 - 1277

Paper Reg. ID: IJSDR_204811

Published Paper Id: IJSDR2303207

Downloads: 000347519

Research Area: Computer Science & Technology 

Country: PONDICHERRY, pudhucherry, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2303207

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2303207

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

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