Robust Stock Price Prediction using Gated Recurrent Unit (GRU)

  • Hamzah Hamzah Universitas Respati Yogyakarta
  • Sugeng Winardi Universitas Respati Yogyakarta
  • Poly Endrayanto Eko Chrismawan Universitas Respati Yogyakarta, Indonesia
  • Rainbow Tambunan Universitas Respati Yogyakarta

Abstract

Forecasting the direction of price movement of the stock market could yield significant profits. Traders use technical analysis, which is the study of price by scrutinizing past prices, to forecast the future price of the nickel stock price. Therefore, in this study, we propose Gated Recurrent Units (GRU) to predict nickel stock price trends. This research aims to produce an accurate nickel stock price trend prediction model. The research method utilized historical data on nickel stock prices from Yahoo Finance. The research results show that the model developed accurately predicted nickel stock price trends. From the RMSE, MAE, and MSE analysis results, the RMSE value was 0.0123, the MAE value was 0.0089, and the MSE value was 0.0002 on the test data.

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Published
2023-09-20
How to Cite
HAMZAH, Hamzah et al. Robust Stock Price Prediction using Gated Recurrent Unit (GRU). International Journal of Informatics and Computation, [S.l.], v. 5, n. 1, p. 29-38, sep. 2023. ISSN 2714-5263. Available at: <https://ijicom.respati.ac.id/index.php/ijicom/article/view/56>. Date accessed: 19 may 2024. doi: https://doi.org/10.35842/ijicom.v5i1.56.