Forex Rates Prediction on EUR/USD with Simple Moving Average Technique and Financial Factors

Abstract

International businesses usually use Forex exchange market to support their business. However, investing has a risk so they need an accuracy Forex information to make the decision. The simple moving average (SMA) has been widely used and a well-known moving average method for time series forecasting. In this empirical study, we would like to do a performance analysis of EUR/U SD Forex rates by adding simple moving averaged technique and financial factors (Dollar Index (DX), US Interest rate (federal funds rate), Inflation rate (IR) and real Gross Domestic Product (GDP)). Four Forex datasets are Forex, Forex with factors, Forex with SMA, and Forex with factors and SMA to forecast Forex rates. Research efforts on Multilayer Perceptron (MLP) and Linear Regression (LM) for forecasting EUR/USD Forex rates. It is shown by using mean square error (MSE) that by adding financial factors and simple moving average to Forex datasets, the performance has improved significantly.