Stock price prediction using artificial neural network integrated moving average

Abstract

Abstract Stock prices are always interesting to be a research topic because stock prices always change at any time. Stock price index is a benchmark for shareholders to sell, buy or maintain it. As in this study, the data used is the closing price of ANTM’s share price which is then processed to predict future stock prices. The proposed method in this study is an integrated moving average which is used to transform data in order to improve data quality. So that it can improve the accuracy of predictions on the neural network. Based on the experiment conducted using 10 combinations of parameters on the neural network using integrated moving average, has been able to produce the RMSE value. And validation based on t-test also showed a significant difference compared to the previous model. So from the result of experiment use an integrated moving average proved to be able to improve neural network performance.