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High Dimensional Yield Curves: Models and Forecasting

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  • Clive G. Bowsher

    ()

  • Roland Meeks

    ()

Abstract

Functional 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 Info

Paper provided by Oxford Financial Research Centre in its series OFRC Working Papers Series with number 2006fe11.

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Length: 37
Date of creation: 2006
Date of revision:
Handle: RePEc:sbs:wpsefe:2006fe11

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Web page: http://www.finance.ox.ac.uk
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Related research

Keywords: Yield curve; term structure; expectations theory; FSN models; functional time series; forecasting; state space form; cubic spline.;

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  1. Campbell, John Y & Shiller, Robert J, 1991. "Yield Spreads and Interest Rate Movements: A Bird's Eye View," Review of Economic Studies, Wiley Blackwell, vol. 58(3), pages 495-514, May.
  2. Francis X. Diebold & Glenn D. Rudebusch & S. Boragan Aruoba, 2004. "The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach," NBER Working Papers 10616, National Bureau of Economic Research, Inc.
  3. Clive G. Bowsher & Roland Meeks, 2006. "The Impossibility of Stationary Yield Spreads and I(1) Yields under the Expectations Theory of the Term Structure," Economics Papers 2006-W05, Economics Group, Nuffield College, University of Oxford.
  4. Diebold, Francis X. & Li, Canlin, 2003. "Forecasting the term structure of government bond yields," CFS Working Paper Series 2004/09, Center for Financial Studies (CFS).
  5. Gregory R. Duffee, 2002. "Term Premia and Interest Rate Forecasts in Affine Models," Journal of Finance, American Finance Association, vol. 57(1), pages 405-443, 02.
  6. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
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Cited by:
  1. Almeida, Caio & Vicente, José, 2008. "The role of no-arbitrage on forecasting: Lessons from a parametric term structure model," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2695-2705, December.

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