One of the most challenging tasks of a researcher in the area of stock market is accurate prediction because of the high volatile and non-linear behavior of the trade market. The main intention is to improve the efficiency of forecasting, since the investors in the stock market are concerned about the future stock market business for smart investments. And hence, advanced methods for prediction are needed that are reliable targeting to increase the profits. In this paper, a comprehensive review of the various prediction techniques for stock marketing is presented in a crisp way. This paper emphasizes on stock market prediction using reinforcement learning, machine learning, deep learning, deep reinforcement learning and sentiment analysis techniques.
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