Forecasting exchange rates: An iterated combination constrained predictor approach

Abstract

Forecasting exchange rate returns is of great interest to both academics and practitioners. In this study, we forecast daily exchange rate returns of six widely traded currencies using combination and dimensionality reduction methods. We propose a hybrid iterated combination with constrained predictor approach. In addition, we examine the impact of positivity constraints on the forecasting ability of each method. Our results indicate that the proposed hybrid method outperforms the simple linear bivariate method and both the iterated combination and the predictor constrained approaches. Positivity constraints significantly improve the forecasting ability of all methods.