Research on the Prediction of the Price Change of the US Against the JPY Based on Neural Network Modeling - Xu, Ze (Transactions on Computer Science and Intelligent Systems Research, 2024)
With the global economy getting closer, the fluctuation of the foreign exchange market has an increasingly significant impact on the world economy. As one of the important foreign currencies, the research on the price change of the dollar against the yen is of great significance. In recent years, the emergence of neural network models has made remarkable achievements in the field of forecasting the price of USD against JPY. This paper discusses the feasibility of using the neural network model to predict the price change of the dollar against the yen, and the method of using the neural network model to predict the price change of the dollar against the yen. By collecting historical exchange rate data, we build a training neural network model, analyze the performance of the model in forecasting exchange rate changes, and explore its potential application value. Research results: The mean square absolute error of the prediction model constructed in this paper is less than 2.5%, and the accuracy of the model reaches 97.4%; The simulation analysis of multiple samples shows that the error of the calculation result of the exchange rate of USD and JPY based on BP neural network is very small, the prediction effect is relatively good, and the prediction performance is high, which indicates that the neural network model has certain accuracy and reliability in the exchange rate prediction, and provides a useful reference tool for investors and financial institutions.