Abstract
Stock is a curve with a lot of unknowns. Stock market forecasting is fraught with complications and unpredictability. One of the most challenging and sophisticated methods of doing business is investing in the stock market. Stock forecasting is a difficult and time-consuming activity since the stock market is extremely volatile with stock prices fluctuating due to a variety of variables. Investors nowadays want quick and precise information to make informed decisions, thanks to the rapid growth of technology in stock price prediction. Understanding a company's stock price pattern and estimating its future development and financial growth will be quite advantageous. As the stock is made up of dynamic data, data is the critical source of efficiency. In the current trend of predicting stocks, deep learning is the most popular among the prediction of datasets. To forecast and automate operations, deep learning employs several prediction models and algorithms. The paper briefs about different algorithms and methods used for stock market prediction.
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