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Research Article 


A Survey on LSTM-based Stock Market Prediction

Sachin Tiwari, Anoop Kumar Chaturvedi.

Abstract
The stock price incorporates variables rate of economic growth, inflation rate, overall economy, trade balance, and monetary system that affect the whole stock market. For investors, the principle of the stock price trend has often been unclear due to numerous significant variables. In developing an investment plan or deciding duration for the purchasing or selling of a stock, the prediction of stock markets provides a crucial function. The stock index's non-linear and dynamic nature estimates the stock market avalue is challenging. Deep learning strategies have emerged as a critical technique in the analysis of dynamic temporal data relations. Several studies of deep learning techniques have been effective in making such a prediction. The Long Short Term Memory (LSTM) has gained popularity for estimating stock market prices. LSTM is a particular form of recurrent neural network (RNN) which implements a gradient descent technique. This paper extensively investigates approaches used for stock market forecasts using LSTM, explains them, and conducts a comparative analysis. The stock market's principal application comprises stock price forecasting, index modeling, risk assessment, and return estimates. We include future directions and summarize the importance of applying LSTM for stock market prediction based on our surveyed papers.

Key words: Long short-term memory (LSTM), recurrent neural network (RNN), nifty 50, root mean square error (RMSE), prediction, stock prices.


 
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Pubmed Style

Sachin Tiwari, Anoop Kumar Chaturvedi. A Survey on LSTM-based Stock Market Prediction. EEO. 2021; 20(5): 1671-1677. doi:10.17051/ilkonline.2021.05.182


Web Style

Sachin Tiwari, Anoop Kumar Chaturvedi. A Survey on LSTM-based Stock Market Prediction. http://ilkogretim-online.org//?mno=59724 [Access: April 09, 2021]. doi:10.17051/ilkonline.2021.05.182


AMA (American Medical Association) Style

Sachin Tiwari, Anoop Kumar Chaturvedi. A Survey on LSTM-based Stock Market Prediction. EEO. 2021; 20(5): 1671-1677. doi:10.17051/ilkonline.2021.05.182



Vancouver/ICMJE Style

Sachin Tiwari, Anoop Kumar Chaturvedi. A Survey on LSTM-based Stock Market Prediction. EEO. (2021), [cited April 09, 2021]; 20(5): 1671-1677. doi:10.17051/ilkonline.2021.05.182



Harvard Style

Sachin Tiwari, Anoop Kumar Chaturvedi (2021) A Survey on LSTM-based Stock Market Prediction. EEO, 20 (5), 1671-1677. doi:10.17051/ilkonline.2021.05.182



Turabian Style

Sachin Tiwari, Anoop Kumar Chaturvedi. 2021. A Survey on LSTM-based Stock Market Prediction. Elementary Education Online, 20 (5), 1671-1677. doi:10.17051/ilkonline.2021.05.182



Chicago Style

Sachin Tiwari, Anoop Kumar Chaturvedi. "A Survey on LSTM-based Stock Market Prediction." Elementary Education Online 20 (2021), 1671-1677. doi:10.17051/ilkonline.2021.05.182



MLA (The Modern Language Association) Style

Sachin Tiwari, Anoop Kumar Chaturvedi. "A Survey on LSTM-based Stock Market Prediction." Elementary Education Online 20.5 (2021), 1671-1677. Print. doi:10.17051/ilkonline.2021.05.182



APA (American Psychological Association) Style

Sachin Tiwari, Anoop Kumar Chaturvedi (2021) A Survey on LSTM-based Stock Market Prediction. Elementary Education Online, 20 (5), 1671-1677. doi:10.17051/ilkonline.2021.05.182








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