Predicting the stock prices is a very complex task, and to predict an almost accurate stock price,we need a robust and accurate algorithm which can analyze and compute the longer-term share prices.Several researcher’s equally in the world and different industries have been very interested in the stockmarket. Stock processes are correlated within the nature of the market and that is why it is difficult topredict the share price. This project aims at processing and analyzing huge volumes of data (live data)and running comprehensive algorithms on the dataset. The purpose of the paper is to understand theshortcomings of the current prediction algorithms and to provide a method using neural networks andartificial intelligence through which we can predict the shared values with accuracy.By using the proposed method, anyone can monitor the preferred stock in real-time and can invest in thestock to make the most money by buying a large number of shares at the cheapest price and sellingthem at the highest price..
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Chawla et al. (2024) studied this question.
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