Prediction of stock markets is a complex and challenging task due to price data generated is huge in volume, changes every second, sensitive to human emotions (fear), actions (Wars) and natural disasters (floods, famine, earthquake). Many Methods have been used to predict the stock price like Technical Analysis, Time Series, Fundamental analysis, etc. Prediction of stock price provides knowledgeable information about the status of the stock price and will also help in decision making for the investors. Much research has been carried out in prediction of stock prices using different approaches of Machine Learning techniques, Deep Learning, Sentiment Analysis etc. This paper explores and reviews some of the recent works carried out in predicting stock prices.
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