Forecasting Interest Rates Using Geostatistical Techniques

Giuseppe Arbia, Michele Di Marcantonio

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.
Original languageEnglish
Title of host publicationBook of Abstracts CFE-ERCIM Conference 2014
Number of pages1
Publication statusPublished - 2014
Event8th International Conference on Computational and Financial Econometrics (CFE 2014) - Pisa
Duration: 6 Dec 20148 Dec 2014


Conference8th International Conference on Computational and Financial Econometrics (CFE 2014)


  • Forecasting
  • Geostatistics
  • Ordinary Kriging
  • Term structure
  • Variogram
  • Yield curve


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