Forecasting the Gold Returns with Artifical Neural Network and Time Series

Abstract

Gold is an important investment tool especially in developing countries. Return-on-gold and prediction thereof is a topic which has been attracting the attention of investors and densely studied recently. For this reason different methods are being used to predict return-on-gold and effectiveness of these methods are being compared. The purpose of this study is to generate a prediction of return-on-gold using artificial neural networks and GARCH and its derivatives, which is a conventional time series method, based on the series obtained from the return of gold values provided by Turkish Gold Exchange belonging to the February 2014 and June 2014 period. As a result of this study, contrary to the expectations and the majority of similar studies, ANN provided less successful outcomes compared to GJR GARCH method.