Sinkron : Jurnal dan Penelitian Teknik Informatika
Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023

Comparison of LSTM and GRU Models for Forex Prediction

Pahlevi, Mohammad Rezza (Unknown)
Kusrini, Kusrini (Unknown)
Hidayat, Tonny (Unknown)



Article Info

Publish Date
01 Oct 2023

Abstract

Trading foreign currencies worth trillions of dollars takes place daily in the forex market, characterized by highly volatile movements. The forex market operates on bid and ask prices, with exchange rates determined by the principles of supply and demand. Trading involves currency pairs like EUR/USD, where the value of the Euro is compared to the US Dollar, serving as a basis for analyzing price fluctuations. Due to the volatile nature of forex, market participants must make informed decisions when buying and selling, as improper choices can result in financial losses. One approach to mitigating risk in forex trading decisions is through the use of forecasting techniques. This research study employs LSTM and GRU methods to predict forex trends, which are evaluated using various dataset divisions. The most accurate results are obtained using a dataset of 4979, split into three equal parts: 80% for training, 10% for validation, and 10% for testing. This approach yields an RMSE value of 0.054, MAPE of 0.037, and R-square of 97%

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Journal Info

Abbrev

sinkron

Publisher

Subject

Computer Science & IT

Description

Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial ...