Abstract: Predicting and analysing are the two most powerful uses of deep learning. Credits go to the tremendous development in Artificial Intelligence. Analysis and prediction have been providing us with highly accurate results along with saving huge amounts of processing time and power. Tasks have become simpler and more accurate. Predicting and analysing the stock market’s behaviour is one such application. By predicting the Stock market, we can help people reap benefits. This is done using historical stock data and then predicting the future value of a stock. Here the stock data refers to historical stock prices news headlines, events which affect the stock’s behaviour. Stock markets are highly volatile and predicting its behaviour can only be done very experienced investors and traders. Thus, it can be difficult for an average investor to make the right decisions. Using the historical stock price data, we use the LSTM model for analysis and using the news events we implement sentiment analysis for predicting and analysis the stock market’s behaviour. Our aim is to understand the deep learning and sentiment analysis methods, implement it to predict the stock market. The final goal of this project is to provide an average/inexperienced trader/investor citizen an insight into the stock exchange and to attain maximum profit with the right amount of investment.

Keywords: Stock Market, Deep Learning, Sentiment Analysis.

PDF | DOI: 10.17148/IARJSET.2021.8630

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