Stock Price Prediction Using Recurrent Neural Network and Long Short-Term Memory

The stock market or equity market has a significant impact on our world. An increment or the decrement in the share price determines whether an investor is going to be in gain or not. The existing prediction models with the help of both dynamic and definite algorithms focuses on foreseeing the stock value of a single organization using the daily opening and closing stock price while the recommended model uses a different approach, where instead of using the data for a specific model, latent dynamics of the data-set is identified with the help of deep learning algorithms. In the proposed model, the price of Google Stock is predicted using two deep learning models with the least possible error. We are applying the Recurrent Neural Network for predicting the price on a short term basis.