Paper Title
Forecasting YEN/USD using Artificial Neural Network

Abstract
This study aims to forecast Japanese yen exchange rate against USD. The model is set up base on purchasing power parity (PPP). We forecast the model of YEN/USD based on Feed Forward Artificial Neural Networks with Resilient Back propagation algorithms using monthly data from Jan1999 to Mar 2019. The results of the study show that the resilient back propagation learning algorithm with tan-sigmoid activation function has better performance for YEN/USD exchange rate forecasting than a linear model and the most influential variable that affect the value of yen is relative real interest rate. Keywords - Purchasing Power Parity, Artificial Neural Network, Resilient Back propagation