Forex Daily Price Prediction Using Gated Recurrent Unit

Jia You Ong, Kian Ming Lim, Chin Poo Lee, Jit Yan Lim

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

The foreign exchange (Forex) market is globally recognized as one of the most prominent financial markets. In this paper, we focus on three major currency pairs: EUR/USD, GBP/USD, and USD/CHF, spanning from January 2007 to July 2022. We employ a range of techniques, including technical indicators, feature scaling, and Gated Recurrent Unit (GRU) network, to predict the closing price one day ahead of the current day. Our method demonstrates superior performance compared to other state-of-the-art approaches, achieving remarkably low Mean Absolute Errors (MAE) of 0.0046, 0.0063, and 0.0039 for the respective currency pairs: EUR/USD, GBP/USD, and USD/CHF.

Original languageEnglish
Title of host publication2023 IEEE 11th Conference on Systems, Process and Control, ICSPC 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages72-77
Number of pages6
ISBN (Electronic)9798350340860
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event11th IEEE Conference on Systems, Process and Control, ICSPC 2023 - Malacca, Malaysia
Duration: 16 Dec 2023 → …

Publication series

Name2023 IEEE 11th Conference on Systems, Process and Control, ICSPC 2023 - Proceedings

Conference

Conference11th IEEE Conference on Systems, Process and Control, ICSPC 2023
Country/TerritoryMalaysia
CityMalacca
Period16/12/23 → …

Keywords

  • Forex price prediction
  • Gated Recurrent Unit
  • Recurrent neural networks

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Modelling and Simulation
  • Education

Fingerprint

Dive into the research topics of 'Forex Daily Price Prediction Using Gated Recurrent Unit'. Together they form a unique fingerprint.

Cite this