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Forecasting Interest Rates Using Geostatistical Techniques

Department of Statistics, Catholic University of the Sacred Heart, Largo Francesco Vito, 1-00168 Rome, Italy
Department of Statistical Sciences, University of Rome “La Sapienza”, Viale Regina Elena, 295-00161 Rome, Italy
Author to whom correspondence should be addressed.
Academic Editors: Fredj Jawadi, Tony S. Wirjanto, Marc S. Paolella and Nuttanan Wichitaksorn
Econometrics 2015, 3(4), 733-760;
Received: 31 July 2015 / Revised: 16 October 2015 / Accepted: 29 October 2015 / Published: 9 November 2015
(This article belongs to the Special Issue Recent Developments of Financial Econometrics)
Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of an empirical application where we apply the proposed method to forecast Euro Zero Rates (2003–2014) using the Ordinary Kriging method based on the anisotropic variogram. Furthermore, a comparison with other recent methods for forecasting yield curves is proposed. The results show that the model is characterized by good levels of predictions’ accuracy and it is competitive with the other forecasting models considered. View Full-Text
Keywords: term structure; yield curve; forecasting; geostatistics; variogram; Ordinary Kriging term structure; yield curve; forecasting; geostatistics; variogram; Ordinary Kriging
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MDPI and ACS Style

Arbia, G.; Di Marcantonio, M. Forecasting Interest Rates Using Geostatistical Techniques. Econometrics 2015, 3, 733-760.

AMA Style

Arbia G, Di Marcantonio M. Forecasting Interest Rates Using Geostatistical Techniques. Econometrics. 2015; 3(4):733-760.

Chicago/Turabian Style

Arbia, Giuseppe, and Michele Di Marcantonio. 2015. "Forecasting Interest Rates Using Geostatistical Techniques" Econometrics 3, no. 4: 733-760.

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