Forecasting stock market price using LSTM-RNN

Predicting the securities exchange is the most challenging task. There are a lot of variables involved in the scenario- physical elements and psychological factors, rational and irrational behavior, etc. These factors combine to make the price of shares not only unpredictable but difficult to estimate with any accuracy. Here, we are trying to predict the price of stocks using an RNN architecture called Long-Short Term Memory(LSTM). Here we are predicting the closing price of the NSE on the basis of the past prices available. The model was trained with the company's stock price, and then the model will be used to predict the future costs of stock. After the training and prediction, we compare the actual and predicted stock values. For comparison, we plot a graph, and the more the lines overlap, the more accuracy we get in predicting the stock price.