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The Dynamics of Economic Functions: Modelling and Forecasting the Yield Curve (2008)
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@MISC{Bowsher08thedynamics,
author = {Clive G. Bowsher and Roland Meeks},
title = {The Dynamics of Economic Functions: Modelling and Forecasting the Yield Curve},
year = {2008}
}
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Abstract
The class of Functional Signal plus Noise (FSN) models is introduced that provides a new, general method for modelling and forecasting time series of economic functions. The underlying, continuous economic function (or ‘signal’) is a natural cubic spline whose dynamic evolution is driven by a cointegrated vector autoregression for the ordinates (or ‘y-values’) at the knots of the spline. The natural cubic spline provides flexible cross-sectional fit and results in a linear, state space model. This FSN model achieves dimension reduction, provides a coherent description of the observed yield curve and its dynamics as the cross-sectional dimension N becomes large, and can feasibly be estimated and used for forecasting when N is large. The integration and cointegration properties of the model are derived. The FSN models are then applied to forecasting 36-dimensional yield curves for US Treasury bonds at the one month ahead horizon. The method consistently outperforms the Diebold and Li (2006) and random walk forecasts on the basis of both mean square forecast error criteria and economically relevant loss functions derived from the realised profits of pairs trading algorithms. The analysis also highlights in a concrete setting the dangers of attempts to infer the relative economic value of model forecasts on the basis of their associated mean square forecast errors. Keywords: FSN-ECM models, functional time series, term structure, forecasting interest rates, natural cubic spline, state space form. JEL classification: C33, C51, C53, E47, G12. 1
Keyphrases
economic function yield curve natural cubic spline fsn model model forecast u treasury bond pair trading algorithm forecasting time series random walk forecast flexible cross-sectional fit state space form relevant loss function fsn-ecm model mean square forecast error criterion cointegrated vector autoregression functional signal observed yield curve term structure continuous economic function relative economic value state space model jel classification cointegration property cross-sectional dimension interest rate functional time series general method dimension reduction realised profit mean square forecast error coherent description dynamic evolution 36-dimensional yield curve
