Predicting Stock Prices Using LSTM
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064



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Research Paper | Neural Networks | India | Volume 6 Issue 4, April 2017

Predicting Stock Prices Using LSTM

Murtaza Roondiwala, Harshal Patel, Shraddha Varma

The art of forecasting the stock prices has been a difficult task for many of the researchers and analysts. In fact, investors are highly interested in the research area of stock price prediction. For a good and successful investment, many investors are keen in knowing the future situation of the stock market. Good and effective prediction systems for stock market help traders, investors, and analyst by providing supportive information like the future direction of the stock market. In this work, we present a recurrent neural network (RNN) and Long Short-Term Memory (LSTM) approach to predict stock market indices.

Keywords: Long short-term memory LSTM, recurrent neural network RNN, nifty 50, root mean square error RMSE, prediction, stock prices

Edition: Volume 6 Issue 4, April 2017

Pages: 1754 - 1756

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How to Cite this Article?

Murtaza Roondiwala, Harshal Patel, Shraddha Varma, "Predicting Stock Prices Using LSTM", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20172755, Volume 6 Issue 4, April 2017, 1754 - 1756

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Research Paper, Neural Networks, India, Volume 6 Issue 4, April 2017

Pages: 1754 - 1756

Predicting Stock Prices Using LSTM

Murtaza Roondiwala, Harshal Patel, Shraddha Varma

Share this Article



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