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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM13283
Volume:
6 |
5 |
May 2022
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Stock investment is an essential tool for managing one’s finances in today’s world, and stock price forecasting has turned into a hot issue. Deep learning technology has gained popularity in recent years has successfully handled a variety of prediction challenges. The LSTM (Long Short Term Memory), which excels at understanding data collected throughout time, is utilized to estimate the price of a stock using historical transaction data and text sentiments, and government NLP is employed to recognize text sentiments. We propose stock market having sentiment in this system, which means whether the news of the stock market is positive or negative. If the news is negative, we see the graph of the market falling, and if the news is positive, we see the graph of the market rising. We use NLP for this sentiment analysis as well as LSTM for stock market prediction. This technology allows the system to produce precise results while also executing quickly and providing outcomes in under a minute.
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Publication Date
5/16/2022
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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