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.

Arbia, G., Di Marcantonio, M., Forecasting Interest Rates Using Geostatistical Techniques, Abstract de <<8th International Conference on Computational and Financial Econometrics (CFE 2014)>>, (Pisa, 06-08 December 2014 ), CMStatistics and CFEnetwork, Pisa 2014: 126-126 [http://hdl.handle.net/10807/67768]

Forecasting Interest Rates Using Geostatistical Techniques

Arbia, Giuseppe;Di Marcantonio, Michele
2014

Abstract

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.
Inglese
Book of Abstracts CFE-ERCIM Conference 2014
8th International Conference on Computational and Financial Econometrics (CFE 2014)
Pisa
6-dic-2014
8-dic-2014
9788493782245
CMStatistics and CFEnetwork
http://www.cmstatistics.org/ERCIM2014/docs/BoA%20CFE-ERCIM%202014.pdf
Arbia, G., Di Marcantonio, M., Forecasting Interest Rates Using Geostatistical Techniques, Abstract de <<8th International Conference on Computational and Financial Econometrics (CFE 2014)>>, (Pisa, 06-08 December 2014 ), CMStatistics and CFEnetwork, Pisa 2014: 126-126 [http://hdl.handle.net/10807/67768]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/67768
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