Exchange rate forecasting with optimum singular spectrum analysis

Abstract

Forecasting exchange rate is undoubtedly an attractive and challenging issue that has been of interest in different domains for many years. The singular spectrum analysis (SSA) technique has been used as a promising technique for time series forecasting including exchange rate series. The SSA technique is based upon two main choices: Window length, L, and the number of singular values, r. These values are very important for the reconstruction stage and forecasting purposes. Here the authors consider an optimum version of the SSA technique for forecasting exchange rates. The forecasting performances of the SSA technique for one-step-ahead forecast of six exchange rate series are used to find the best L and r.