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Title |
An Approach for Stock Price Forecast using Long Short Term Memory |
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Author |
K.A.Surya Rajeswar, Pon Ramalingam, Sudalaimuthu.T |
| Citation |
Vol. 23 No. 4 pp. 166-171 |
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Abstract |
The Stock price analysis is an increasing concern in a financial time series. The purpose of the study is to analyze the price parameters of date, high, low, and news feed about the stock exchange price. Long short term memory (LSTM) is a cutting-edge technology used for predicting the data based on time series. LSTM performs well in executing large sequence of data. This paper presents the Long Short Term Memory Model has used to analyze the stock price ranges of 10 days and 20 days by exponential moving average. The proposed approach gives better performance using technical indicators of stock price with an accuracy of 82.6% and cross entropy of 71%. |
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Keywords |
Stock Price, Long short time memory, Cross entropy, Accuracy |
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