This study proposes a model which will make use of an LSTM model for predicting stock prices. The stock prices will
be predicted on the basis of past information. Stacked LSTM will be employed for the prediction because it utilizes the historic data, therefore, making the predictions more accurate since it is able to learn long term dependencies in data, which makes LSTM an ideal technique for stock market prediction due to its dynamic as well as complex nature.
