Foreign Exchange Prediction Using Machine Learning Approach: A Pilot Study

• Published in: 2021 4th International Conference on Information and Communications Technology (ICOIACT) pp. 239 - 242
• Main Authors: Sudimanto, Heryadi, Yaya, Lukas, Wibowo, Antoni
• Format: Conference Proceeding
• Language: English
• Published: IEEE 30-08-2021
• Subjects: Foreign Exchange; Gold; MACD; Machine learning; Oils; Predictive models; Silver; Support vector machines; Technical Analysis; Training
• DOI: 10.1109/ICOIACT53268.2021.9563998

Foreign Exchange or FOREX trading is not only done on foreign currencies but, FOREX also can be done on several commodities such as Gold, Silver, Oil. Gold is one of the most valuable commodities in the world. Investors began to offer gold as a trading material against foreign currencies. Machine Learning (ML) in the FOREX trading world is usually used to predict future FOREX values. This pilot study aims to see a model from machine learning that has a fairly high level of accuracy in making FOREX predictions. This pilot study using historical data taken from the investing.com database where the FOREX data taken is FOREX XAU/USD data, with a period year from 2019 until 2021, and the indicator used is Moving Average Convergence/Divergence (MACD) technical analysis. The average accuracy obtained after training on the Tree model is 86.3%, the Support Vector Machine (SVM) model is 86.6% and the Ensemble model is 86.55%. Testing conducted using machine learning models for Tree, SVM and Ensemble models have the same level of accuracy, which is 88.3%.