Abstract: The computation of longer-term share prices requires a strong algorithmic foundation for the complicated process of stock value prediction. Due to the structure of the market, stock prices are connected, making it challenging to estimate expenses. The suggested algorithm employs machine learning methods like a recurrent neural network called Long Short Term Memory to estimate the share price using market data. Weights are corrected for each data point using stochastic gradient descent during this process. In contrast to the stock price predictor algorithms that are now accessible, our system will produce accurate results. To drive the graphical results, the network is trained and assessed with a range of input data sizes.
Keywords: Stock Market, Long Short- Term Memory, Machine Learning, Artificial Neural Networks, National Stock Exchange
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DOI:
10.17148/IJARCCE.2023.124160
