International Journal Artificial Intelligent and Informatics
Vol 3, No 1 (2025)

Comparison of LSTM and GRU Methods for Predicting Gold Exchange Rate against US Dollar

Bohovic, Dušan (Unknown)



Article Info

Publish Date
30 Jan 2025

Abstract

This study aims to compare the performance of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models in predicting the gold exchange rate against the United States Dollar (USD). Using time series data from Yahoo Finance for the period 2017-2023, we evaluate and compare the two models based on comprehensive evaluation metrics. The results show that the GRU model performs better in several important metrics, especially in terms of Root Mean Square Error (RMSE) on the test data (26.41 compared to 27.54 on LSTM) and higher coefficient of determination (R²) on the test data (0.9004 compared to 0.7825 on LSTM). These findings indicate that the GRU model has better generalization ability for gold to USD exchange rate prediction, although both models show very high accuracy rates above 98% on the test data.

Copyrights © 2025






Journal Info

Abbrev

IJARLIT

Publisher

Subject

Computer Science & IT Economics, Econometrics & Finance

Description

International Journal of Artificial Intelligence and Informatics is a scientific journal dedicated to the exploration of theories, methods, and applications of artificial intelligence in time series analysis, forecasting, and prediction. This journal serves as a platform for researchers, academics, ...