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Flexible Term Structure Estimation: Which Method Is Preferred?

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  • Andrew Jeffrey
  • Oliver Linton
  • Thong Nguyen

Abstract

We show that the recently developed nonparametric procedure for fitting the term structure of interest rates developed by Linton, Mammen, Nielsen, and Tanggaard (2000) overall performs notably better than the highly flexible McCulloch (1975) cubic spline and Fama and Bliss (1987) bootstrap methods. However, if interest is limited to the Treasury bill region alone then the Fama-Bliss method demonstrates superior performance. We further show, via simulation, that using the estimated short rate from the Linton-Mammen-Nielsen-Tanggaard procedure as a proxy for the short rate has higher precision then the commonly used proxies of the one and three month Treasury bill rates. It is demonstrated that this precision is important when using proxies to estimate the stochastic process governing the evolution of the short rate.

Suggested Citation

  • Andrew Jeffrey & Oliver Linton & Thong Nguyen, 2001. "Flexible Term Structure Estimation: Which Method Is Preferred?," Yale School of Management Working Papers ysm171, Yale School of Management, revised 01 Oct 2001.
  • Handle: RePEc:ysm:wpaper:ysm171
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    File URL: https://repec.som.yale.edu/icfpub/publications/2510.pdf
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    References listed on IDEAS

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    1. Chan, K C, et al, 1992. "An Empirical Comparison of Alternative Models of the Short-Term Interest Rate," Journal of Finance, American Finance Association, vol. 47(3), pages 1209-1227, July.
    2. Chapman, David A & Long, John B, Jr & Pearson, Neil D, 1999. "Using Proxies for the Short Rate: When Are Three Months Like an Instant?," The Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 763-806.
    3. 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.).
    4. Hull, John & White, Alan, 1990. "Pricing Interest-Rate-Derivative Securities," The Review of Financial Studies, Society for Financial Studies, vol. 3(4), pages 573-592.
    5. Conley, Timothy G, et al, 1997. "Short-Term Interest Rates as Subordinated Diffusions," The Review of Financial Studies, Society for Financial Studies, vol. 10(3), pages 525-577.
    6. Sarig, Oded & Warga, Arthur, 1989. "Bond Price Data and Bond Market Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(3), pages 367-378, September.
    7. 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.
    8. Amihud, Yakov & Mendelson, Haim, 1991. "Liquidity, Maturity, and the Yields on U.S. Treasury Securities," Journal of Finance, American Finance Association, vol. 46(4), pages 1411-1425, September.
    9. McCulloch, J Huston, 1975. "The Tax-Adjusted Yield Curve," Journal of Finance, American Finance Association, vol. 30(3), pages 811-830, June.
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    Cited by:

    1. Oliveira, Luís & Curto, José Dias & Nunes, João Pedro, 2012. "The determinants of sovereign credit spread changes in the Euro-zone," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(2), pages 278-304.
    2. 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.
    3. Bowsher, Clive G. & Meeks, Roland, 2008. "The Dynamics of Economic Functions: Modeling and Forecasting the Yield Curve," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1419-1437.
    4. Liu, Yan & Wu, Jing Cynthia, 2021. "Reconstructing the yield curve," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1395-1425.
    5. Antonio Diaz & Francisco Jareno & Eliseo Navarro, 2010. "Term structure of volatilities and yield curve estimation methodology," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 573-586.
    6. Tong, Xiaojun & He, Zhuoqiong Chong & Sun, Dongchu, 2018. "Estimating Chinese Treasury yield curves with Bayesian smoothing splines," Econometrics and Statistics, Elsevier, vol. 8(C), pages 94-124.
    7. Luís Oliveira & João Vidal Nunes & Luís Malcato, 2014. "The performance of deterministic and stochastic interest rate risk measures:," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 13(3), pages 141-165, December.
    8. Tatyana Krivobokova & Göran Kauermann & Theofanis Archontakis, 2006. "Estimating the term structure of interest rates using penalized splines," Statistical Papers, Springer, vol. 47(3), pages 443-459, June.
    9. Michiel De Pooter, 2007. "Examining the Nelson-Siegel Class of Term Structure Models," Tinbergen Institute Discussion Papers 07-043/4, Tinbergen Institute.

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