Prediction and Analysis of USD /JPY Exchange Rate Based on BP Neural Network

¹ College of Urban Rail Transit and Logistics, Beijing Union University, 100101 Beijing, China
² School of International Studies, Zhejiang University, 310000 Hangzhou, China
³ Harper Adams University, TF108NB Newport Shropshire, Britain

^* Corresponding author: 3210101389@zju.edu.cn

Abstract

One of the most important variables in the global financial market is the exchange rate, which is the ratio of change between the currencies of two countries. Moderate currency devaluation can stimulate exports, promote economic growth. This paper uses the back propagation (BP) neural network model to predict the short-term exchange rate of USD/JPY. The research result shows that the exchange rate price prediction trend is basically consistent with the real value trend, and the relative error of USD/JPY is extremely small, controlled within 0.8%, which shows that the superficial BP neural network is relatively accurate in the short-term exchange rate forecast of USD /JPY, which has a positive research impact, that is, it provides help for financial analysis. However, it has certain limitations in terms of timeliness, such as the extension of the prediction time, the prediction accuracy may decrease. Future research may need to be combined with other models and methods to improve its reliability.