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Exponentials, Polynomials, and Fourier Series: More Yield Curve Modelling at the Bank of Canada

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  • David Bolder
  • Scott Gusba

Abstract

This paper continues the work started by Bolder and Stréliski (1999) and considers two alternative classes of models for extracting zero-coupon and forward rates from a set of observed Government of Canada bond and treasury-bill prices. The first class of term-structure estimation methods follows from work by Fisher, Nychka, and Zervos (1994), Anderson and Sleath (2001), and Waggoner (1997). This approach employs a B-spline basis for the space of cubic splines to fit observed coupon-bond prices—as a consequence, we call these the spline-based models. This approach includes a penalty in the generalized least-squares objective function—following from Waggoner (1997)—that imposes the desired level of smoothness into the term structure of interest rates. The second class of methods is called function-based and includes variations on the work of Li et al. (2001), which uses linear combinations of basis functions, defined over the entire term-to-maturity spectrum, to fit the discount function. This class of function-based models includes the model proposed by Svensson (1994). In addition to a comprehensive discussion of these models, the authors perform an extensive comparison of these models' performance in the Canadian marketplace.

Suggested Citation

  • David Bolder & Scott Gusba, 2002. "Exponentials, Polynomials, and Fourier Series: More Yield Curve Modelling at the Bank of Canada," Staff Working Papers 02-29, Bank of Canada.
  • Handle: RePEc:bca:bocawp:02-29
    DOI: 10.34989/swp-2002-29
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    References listed on IDEAS

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    1. Andrew Jeffrey & Oliver Linton & Thong Nguyen, 2006. "Flexible Term Structure Estimation: Which Method is Preferred?," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 63(1), pages 99-122, February.
    2. Shea, Gary S, 1985. "Interest Rate Term Structure Estimation with Exponential Splines: A Note," Journal of Finance, American Finance Association, vol. 40(1), pages 319-325, March.
    3. Nicola Anderson & John Sleath, 2001. "New estimates of the UK real and nominal yield curves," Bank of England working papers 126, Bank of England.
    4. Robert R. Bliss, 1996. "Testing term structure estimation methods," FRB Atlanta Working Paper 96-12, Federal Reserve Bank of Atlanta.
    5. McCulloch, J Huston, 1971. "Measuring the Term Structure of Interest Rates," The Journal of Business, University of Chicago Press, vol. 44(1), pages 19-31, January.
    6. Schich, Sebastian T., 1997. "Estimating the German term structure," Discussion Paper Series 1: Economic Studies 1997,04e, Deutsche Bundesbank.
    7. 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.
    8. Mark Fisher, 2001. "Forces that shape the yield curve: Parts 1 and 2," FRB Atlanta Working Paper 2001-3, Federal Reserve Bank of Atlanta.
    9. Linton, Oliver & Mammen, Enno & Nielsen, Jans Perch & Tanggaard, Carsten, 2001. "Yield curve estimation by kernel smoothing methods," Journal of Econometrics, Elsevier, vol. 105(1), pages 185-223, November.
    10. David Bolder & David Stréliski, 1999. "Yield Curve Modelling at the Bank of Canada," Technical Reports 84, Bank of Canada.
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    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • G1 - Financial Economics - - General Financial Markets

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