Stock Price Prediction Using LSTM Algorithm

Stock price prediction is a challenging task due to the volatile and non-linear nature of the financial markets. This paper explores the application of the Long Short-Term Memory (LSTM) neural network, a type of Recurrent Neural Network (RNN), for predicting stock prices. The study demonstrates the effectiveness of LSTM in capturing the temporal dependencies in stock price data, comparing its performance with traditional models.