Stock Market with Sentiment using LSTM

Stock Market with Sentiment using LSTM

Bhalchandra R. Ban                                                        Deepa H. Kulkarni

Computer Engineering                                                   Computer Engineering

Smt.Kashibai Navale College of Engg, Pune,India    Smt.Kashibai Navale College of Engg, Pune,India

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Abstract - 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.

Key Words:  LSTM, Stock Patterns, Machine Learning, Stock prediction