Forecasting Interest Rates Using Geostatistical Techniques

Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. Applications are traditionally confined to fields like geography, geology, meteorology, agriculture and epidemiology and others. We propose to extend their use to finance and, in particular, to forecasting the term structure of interest rates. We present the results of an empirical application where we apply the proposed method to forecast Euro Zero Rates using the Ordinary Kriging method based on the anisotropic variogram, focusing on the period 2003-2014. The empirical results show that, for long-term maturities of interest rates, the model is characterized by good levels of predictions’ accuracy. From a comparative point of view, our model proves to be more accurate than using forward rates implicit in the Euro Zero Rates curve as proxies of the market expectations. Finally, a comparison with other recent methods for forecasting yield curves is proposed. Our work contributes to the existing literature by adopting an innovative approach to analyze the term structure of interest rates for short-term forecasting purposes.