Prediction of Stock Price Movement Using LSTM

Abstract

Making prediction of the stockprice movement is very difficult due to a lot of fluctuations in the prices and a large number of factors that impact it. However, this project tries to make predictions on the future prices of AAPL stock using historical prices and look into the impact of other companies’ stock prices, including FB, AMZN, GOOGL and NFLX stocks, on its prices. These companies together with AAPL stock form FAANG, an acronym for the stocks of five prominent American technology companies. Latest Machine learning algorithms can be used to get insights and trends from the data and predict future values quite accurately. This paper makes use of Long Short-Term Model (LSTM), an Recurrent Neural Network (RNN)to make the prediction using Close values of all the companies included in FAANGas factors. The experimental result predicted by the model shows that this method can get good results for AAPL stock and can clearly show the impact of other prominent companies in the technology industry.