JOURNAL ARTICLE

Robust Stock Price Prediction using Gated Recurrent Unit (GRU)

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.

Keywords:
Stock price Econometrics Computer science Economics Series (stratigraphy) Geology

Metrics

3
Cited By
0.97
FWCI (Field Weighted Citation Impact)
0
Refs
0.77
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Stock Market Forecasting Methods
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Forecasting Techniques and Applications
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Energy Load and Power Forecasting
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
© 2026 ScienceGate Book Chapters — All rights reserved.