High Dimensional Yield Curves: Models and Forecasting
AbstractFunctional Signal plus Noise (FSN) models are proposed for analysing the dynamics of a large cross-section of yields or asset prices in which contemporaneous observations are functionally related. The FSN models are used to forecast high dimensional yield curves for US Treasury bonds at the one month ahead horizon. The models achieve large reductions in mean square forecast errors relative to a random walk for yields and readily dominate both the Diebold and Li (2006) and random walk forecasts across all maturities studied. We show that the Expectations Theory (ET) of the term structure completely determines the conditional mean of any zero-coupon yield curve. This enables a novel evaluation of the ET in which its 1-step ahead forecasts are compared with those of rival methods such as the FSN models, with the results strongly supporting the growing body of empirical evidence against the ET. Yield spreads do provide important information for forecasting the yield curve, especially in the case of shorter maturities, but not in the manner prescribed by the Expectations Theory.
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Bibliographic InfoPaper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2006-W12.
Length: 37 pages
Date of creation: 02 Oct 2006
Date of revision:
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Web page: http://www.nuff.ox.ac.uk/economics/
Yield curve; term structure; expectations theory; FSN models; functional time series; forecasting; state space form; cubic spline.;
Other versions of this item:
- Clive G. Bowsher & Roland Meeks, 2006. "High Dimensional Yield Curves: Models and Forecasting," OFRC Working Papers Series 2006fe11, Oxford Financial Research Centre.
- Clive Bowsher & Roland Meeks, 2006. "High Dimensional Yield Curves: Models and Forecasting," Economics Series Working Papers 2006-FE-11, University of Oxford, Department of Economics.
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-10-14 (All new papers)
- NEP-ECM-2006-10-14 (Econometrics)
- NEP-FIN-2006-10-14 (Finance)
- NEP-FMK-2006-10-14 (Financial Markets)
- NEP-FOR-2006-10-14 (Forecasting)
- NEP-MAC-2006-10-14 (Macroeconomics)
- NEP-MON-2006-10-14 (Monetary Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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