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The Dynamics of Economic Functions: Modelling and Forecasting the Yield Curve

  • Clive G. Bowsher
  • Roland Meeks

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.

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Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 2008-WO5.

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Date of creation: 01 Mar 2008
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Handle: RePEc:oxf:wpaper:2008-wo5
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  1. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
  2. Zellner, A., 1992. "Statistics, Science and Public Policy," Papers 92-21, California Irvine - School of Social Sciences.
  3. 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.
  4. Pagan, A.R. & Hall, A.D. & Martin, V., 1995. "Modelling the Term Structure," Papers 284, Australian National University - Department of Economics.
  5. Shea, Gary S, 1992. "Benchmarking the Expectations Hypothesis of the Interest-Rate Term Structure: An Analysis of Cointegration Vectors," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 347-66, July.
  6. Philippe C. Besse, 2000. "Autoregressive Forecasting of Some Functional Climatic Variations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(4), pages 673-687.
  7. Oliver Linton & Andrew Jeffrey & Thong Nguyen, 2001. "Flexible Term Structure Estimation: Which Method is Preferred?," FMG Discussion Papers dp385, Financial Markets Group.
  8. Michiel D. de Pooter & Francesco Ravazzolo & Dick van Dijk, 2007. "Predicting the Term Structure of Interest Rates: Incorporating Parameter Uncertainty, Model Uncertainty and Macroeconomic Information," Tinbergen Institute Discussion Papers 07-028/4, Tinbergen Institute.
  9. Francis X. Diebold & Canlin Li, 2003. "Forecasting the Term Structure of Government Bond Yields," NBER Working Papers 10048, National Bureau of Economic Research, Inc.
  10. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, Elsevier.
  11. Clive Bowsher & Roland Meeks, 2006. "The Impossibility of Stationary Yield Spreads and I(1) Yields under the Expectations Theory of the Term Structure," Economics Series Working Papers 2006-W05, University of Oxford, Department of Economics.
  12. Marius Ooms & Bj�rn de Groot & Siem Jan Koopman, 1999. "Time-Series Modelling of Daily Tax Revenues," Computing in Economics and Finance 1999 312, Society for Computational Economics.
  13. Clive G. Bowsher, 2004. "Modelling the Dynamics of Cross-Sectional Price Functions: an Econometric Analysis of the Bid and Ask Curves of an Automated Exchange," Economics Papers 2004-W21, Economics Group, Nuffield College, University of Oxford.
  14. Brian P. Sack, 2000. "Using Treasury STRIPS to measure the yield curve," Finance and Economics Discussion Series 2000-42, Board of Governors of the Federal Reserve System (U.S.).
  15. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," NBER Working Papers 11285, National Bureau of Economic Research, Inc.
  16. 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.
  17. Tao Wu & Glenn Rudebusch, 2003. "Macroeconomics and the Yield Curve," Computing in Economics and Finance 2003 206, Society for Computational Economics.
  18. McCulloch, J Huston, 1975. "The Tax-Adjusted Yield Curve," Journal of Finance, American Finance Association, vol. 30(3), pages 811-30, June.
  19. Mark Fisher & Douglas Nychka & David Zervos, 1995. "Fitting the term structure of interest rates with smoothing splines," Finance and Economics Discussion Series 95-1, Board of Governors of the Federal Reserve System (U.S.).
  20. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
  21. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-89, October.
  22. Fama, Eugene F & Bliss, Robert R, 1987. "The Information in Long-Maturity Forward Rates," American Economic Review, American Economic Association, vol. 77(4), pages 680-92, September.
  23. Daniel F. Waggoner, 1997. "Spline methods for extracting interest rate curves from coupon bond prices," FRB Atlanta Working Paper 97-10, Federal Reserve Bank of Atlanta.
  24. Clements, M.P. & Hendry, D., 1992. "On the Limitations of Comparing Mean Square Forecast Errors," Economics Series Working Papers 99138, University of Oxford, Department of Economics.
  25. Hall, Anthony D & Anderson, Heather M & Granger, Clive W J, 1992. "A Cointegration Analysis of Treasury Bill Yields," The Review of Economics and Statistics, MIT Press, vol. 74(1), pages 116-26, February.
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