IDEAS home Printed from https://ideas.repec.org/a/vrs/ngooec/v62y2016i2p42-50n5.html
   My bibliography  Save this article

Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve

Author

Listed:
  • Lorenčič Eva

    (Ranca 35, 2211 Pesnica pri Mariboru, Slovenia)

Abstract

Understanding the relationship between interest rates and term to maturity of securities is a prerequisite for developing financial theory and evaluating whether it holds up in the real world; therefore, such an understanding lies at the heart of monetary and financial economics. Accurately fitting the term structure of interest rates is the backbone of a smoothly functioning financial market, which is why the testing of various models for estimating and predicting the term structure of interest rates is an important topic in finance that has received considerable attention for many decades. In this paper, we empirically contrast the performance of cubic splines and the Nelson-Siegel model by estimating the zero-coupon yields of Austrian government bonds. The main conclusion that can be drawn from the results of the calculations is that the Nelson-Siegel model outperforms cubic splines at the short end of the yield curve (up to 2 years), whereas for medium-term maturities (2 to 10 years) the fitting performance of both models is comparable.

Suggested Citation

  • Lorenčič Eva, 2016. "Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve," Naše gospodarstvo/Our economy, Sciendo, vol. 62(2), pages 42-50, June.
  • Handle: RePEc:vrs:ngooec:v:62:y:2016:i:2:p:42-50:n:5
    DOI: 10.1515/ngoe-2016-0011
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/ngoe-2016-0011
    Download Restriction: no

    File URL: https://libkey.io/10.1515/ngoe-2016-0011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Diebold, Francis X. & Li, Canlin & Yue, Vivian Z., 2008. "Global yield curve dynamics and interactions: A dynamic Nelson-Siegel approach," Journal of Econometrics, Elsevier, vol. 146(2), pages 351-363, October.
    2. Jens H. E. Christensen & Francis X. Diebold & Glenn D. Rudebusch, 2009. "An arbitrage-free generalized Nelson--Siegel term structure model," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 33-64, November.
    3. 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.
    4. Tomas Björk & Bent Jesper Christensen, 1999. "Interest Rate Dynamics and Consistent Forward Rate Curves," Mathematical Finance, Wiley Blackwell, vol. 9(4), pages 323-348, October.
    5. Coroneo, Laura & Nyholm, Ken & Vidova-Koleva, Rositsa, 2011. "How arbitrage-free is the Nelson-Siegel model?," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 393-407, June.
    6. 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.
    7. Jordan, James V. & Mansi, Sattar A., 2003. "Term structure estimation from on-the-run Treasuries," Journal of Banking & Finance, Elsevier, vol. 27(8), pages 1487-1509, August.
    8. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    9. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    10. David Heath & Robert Jarrow & Andrew Morton, 2008. "Bond Pricing And The Term Structure Of Interest Rates: A New Methodology For Contingent Claims Valuation," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 13, pages 277-305, World Scientific Publishing Co. Pte. Ltd..
    11. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
    12. Peter Exterkate & Dick Van Dijk & Christiaan Heij & Patrick J. F. Groenen, 2013. "Forecasting the Yield Curve in a Data‐Rich Environment Using the Factor‐Augmented Nelson–Siegel Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 193-214, April.
    13. Manousopoulos, Polychronis & Michalopoulos, Michalis, 2009. "Comparison of non-linear optimization algorithms for yield curve estimation," European Journal of Operational Research, Elsevier, vol. 192(2), pages 594-602, January.
    14. Gauthier, Geneviève & Simonato, Jean-Guy, 2012. "Linearized Nelson–Siegel and Svensson models for the estimation of spot interest rates," European Journal of Operational Research, Elsevier, vol. 219(2), pages 442-451.
    15. McCulloch, J Huston, 1975. "The Tax-Adjusted Yield Curve," Journal of Finance, American Finance Association, vol. 30(3), pages 811-830, June.
    16. Rafael B. Rezende & Mauro S. Ferreira, 2013. "Modeling and Forecasting the Yield Curve by an Extended Nelson‐Siegel Class of Models: A Quantile Autoregression Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(2), pages 111-123, March.
    17. Ioannides, Michalis, 2003. "A comparison of yield curve estimation techniques using UK data," Journal of Banking & Finance, Elsevier, vol. 27(1), pages 1-26, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Natraj Raman & Jochen L. Leidner, 2018. "Municipal Bond Pricing: A Data Driven Method," IJFS, MDPI, vol. 6(3), pages 1-19, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Leo Krippner, 2009. "A theoretical foundation for the Nelson and Siegel class of yield curve models," Reserve Bank of New Zealand Discussion Paper Series DP2009/10, Reserve Bank of New Zealand.
    2. Aryo Sasongko & Cynthia Afriani Utama & Buddi Wibowo & Zaäfri Ananto Husodo, 2019. "Modifying Hybrid Optimisation Algorithms to Construct Spot Term Structure of Interest Rates and Proposing a Standardised Assessment," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 957-1003, October.
    3. Takamizawa, Hideyuki, 2022. "How arbitrage-free is the Nelson–Siegel model under stochastic volatility?," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 205-223.
    4. Lauren Stagnol, 2017. "Introducing global term structure in a risk parity framework," Working Papers hal-04141648, HAL.
    5. Rafael Barros de Rezende, 2011. "Giving Flexibility to the Nelson-Siegel Class of Term Structure Models," Brazilian Review of Finance, Brazilian Society of Finance, vol. 9(1), pages 27-49.
    6. Ranik Raaen Wahlstrøm & Florentina Paraschiv & Michael Schürle, 2022. "A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 967-1004, March.
    7. Lauren Stagnol, 2019. "Extracting global factors from local yield curves," Journal of Asset Management, Palgrave Macmillan, vol. 20(5), pages 341-350, September.
    8. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    9. Jan Hanousek & Evžen KoÄ enda & Petr ZemÄ Ã­k, 2008. "Bond Market Emergence," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 7(2), pages 141-168, August.
    10. Renata Tavanielli & Márcio Laurini, 2023. "Yield Curve Models with Regime Changes: An Analysis for the Brazilian Interest Rate Market," Mathematics, MDPI, vol. 11(11), pages 1-28, June.
    11. Nagy, Krisztina, 2020. "Term structure estimation with missing data: Application for emerging markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 347-360.
    12. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
    13. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    14. Leo Krippner, 2003. "Modelling the Yield Curve with Orthonomalised Laguerre Polynomials: An Intertemporally Consistent Approach with an Economic Interpretation," Working Papers in Economics 03/01, University of Waikato.
    15. Takamizawa, Hideyuki & 高見澤, 秀幸, 2015. "Impact of No-arbitrage on Interest Rate Dynamics," Working Paper Series G-1-5, Hitotsubashi University Center for Financial Research.
    16. Wali Ullah & Yasumasa Matsuda, 2014. "Generalized Nelson-Siegel Term Structure Model : Do the second slope and curvature factors improve the in-sample fit and out-of-sample forecast?," TERG Discussion Papers 312, Graduate School of Economics and Management, Tohoku University.
    17. Emma Berenguer-Carceles & Ricardo Gimeno & Juan M. Nave, 2012. "Estimation of the Term Structure of Interest Rates: Methodology and Applications," Working Papers 12.06, Universidad Pablo de Olavide, Department of Financial Economics and Accounting (former Department of Business Administration).
    18. Vahidin Jeleskovic & Anastasios Demertzidis, 2018. "Comparing different methods for the estimation of interbank intraday yield curves," MAGKS Papers on Economics 201839, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    19. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    20. Laurini, Márcio Poletti & Hotta, Luiz Koodi, 2010. "Bayesian extensions to Diebold-Li term structure model," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 342-350, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:ngooec:v:62:y:2016:i:2:p:42-50:n:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.