Forecasting Stock Exchange Using Gated Recurrent Unit

Abstract

Stock forecasting is an important thing in investing stock to find the next movement. The major aim of this research is to forecast the McDonald's stock from New York Stock Exchange using data covering the period from 6 January 2006 to 14 April 2021 on a daily, weekly, and monthly basis. The GRU (Gated Recurrent Unit) method is used to create the training model and making predictions from closing movement McDonald's shares. The results of this study are to determine the best forecasting results using the GRU method based on the accuracy and error values obtained in the existing data. The results on the three data that have been tested showed that the medium-term data (weekly data) provide the best result compared to the others based on the accuracy value, the minimum error value, and consistent results obtained on reneated tests.