Exchange rate forecast between Euro and US dollar based on recurrent neural network

Abstract

In the global financial market, the euro and the US dollar are the two most important currencies. The euro is the official currency of EU member states and the second largest trading currency in the world. Its exchange rate is determined by market supply and demand. The US dollar is the world's largest trading currency, and its position in international trade and financial markets is irreplaceable. They play an important role in international trade, financial markets, and travel. It plays an important role in various aspects and has a profound impact on the global economy. The relative value of these two currencies is influenced by various factors, and predicting their exchange rate movements is of great significance for investors, economists, and policymakers. This paper introduces a method to predict the exchange rate between Euro and US dollar using recurrent neural network (RNN). By processing and analyzing historical exchange rate data, the RNN-based model is trained and used to predict future exchange rate changes. Our model shows high accuracy, which proves the predictive ability of RNN in this respect. Deep-learning-based forecasting models and their applications in finance have attracted considerable attention in recent research (Fischer and Krauss 2018; Huck 2019; Kim et al. 2019).