TITLE:
Exchange Rate Forecasting via a Machine Learning Approach
AUTHORS:
Chikashi Tsuji
KEYWORDS:
Artificial Intelligence, Exchange Rate, Machine Learning, Random Forest Algorithm
JOURNAL NAME:
iBusiness,
Vol.14 No.3,
July
12,
2022
ABSTRACT: This paper attempts to forecast exchange rates by
applying a machine learning approach. More specifically, in this study, we
attempt to forecast the dynamic evolutions of the four exchange rates of
Canadian dollars, Australian dollars, Great Britain pounds, and euros, which
are all against the US dollar, by using random forest methodology. Evaluating
the effectiveness, we find that the predictive performance of random forest
approach in exchange rate forecasting is rather high.