IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v42y2015i4p876-904.html
   My bibliography  Save this article

Generalized Nelson-Siegel term structure model: do the second slope and curvature factors improve the in-sample fit and out-of-sample forecasts?

Author

Listed:
  • Wali Ullah
  • Yasumasa Matsuda
  • Yoshihiko Tsukuda

Abstract

The dynamic Nelson-Siegel (DNS) model and even the Svensson generalization of the model have trouble in fitting the short maturity yields and fail to grasp the characteristics of the Japanese government bonds yield curve, which is flat at the short end and has multiple inflection points. Therefore, a closely related generalized dynamic Nelson-Siegel (GDNS) model that has two slopes and curvatures is considered and compared empirically to the traditional DNS in terms of in-sample fit as well as out-of-sample forecasts. Furthermore, the GDNS with time-varying volatility component, modeled as standard EGARCH process, is also considered to evaluate its performance in relation to the GDNS. The GDNS model unanimously outperforms the DNS in terms of in-sample fit as well as out-of-sample forecasts. Moreover, the extended model that accounts for time-varying volatility outpace the other models for fitting the yield curve and produce relatively more accurate 6- and 12-month ahead forecasts, while the GDNS model comes with more precise forecasts for very short forecast horizons.

Suggested Citation

  • Wali Ullah & Yasumasa Matsuda & Yoshihiko Tsukuda, 2015. "Generalized Nelson-Siegel term structure model: do the second slope and curvature factors improve the in-sample fit and out-of-sample forecasts?," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(4), pages 876-904, April.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:4:p:876-904
    DOI: 10.1080/02664763.2014.993363
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2014.993363
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2014.993363?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Bank for International Settlements, 2005. "Zero-coupon yield curves: technical documentation," BIS Papers, Bank for International Settlements, number 25.
    5. Harvey, Andrew & Ruiz, Esther & Sentana, Enrique, 1992. "Unobserved component time series models with Arch disturbances," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 129-157.
    6. 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.
    7. Wali Ullah & Yoshihiko Tsukuda & Yasumasa Matsuda, 2013. "Term Structure Forecasting of Government Bond Yields with Latent and Macroeconomic Factors: Do Macroeconomic Factors Imply Better Out‐of‐Sample Forecasts?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(8), pages 702-723, December.
    8. 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.
    9. Kim, Don H. & Singleton, Kenneth J., 2012. "Term structure models and the zero bound: An empirical investigation of Japanese yields," Journal of Econometrics, Elsevier, vol. 170(1), pages 32-49.
    10. Wali Ullah & Yoshihiko Tsukuda & Yasumasa Matsuda, 2012. "Term Structure Forecasting of Government Bond Yields with Latent and Macroeconomic Factors: Does Macroeconomic Factors Imply Better Out-of-Sample Forecasts?," TERG Discussion Papers 287, Graduate School of Economics and Management, Tohoku University.
    11. Christensen, Jens H.E. & Diebold, Francis X. & Rudebusch, Glenn D., 2011. "The affine arbitrage-free class of Nelson-Siegel term structure models," Journal of Econometrics, Elsevier, vol. 164(1), pages 4-20, September.
    12. Siem Jan Koopman & Max I.P. Mallee & Michel van der Wel, 2007. "Analyzing the Term Structure of Interest Rates using the Dynamic Nelson-Siegel Model with Time-Varying Parameters," Tinbergen Institute Discussion Papers 07-095/4, Tinbergen Institute.
    13. Koopman, Siem Jan & Mallee, Max I. P. & Van der Wel, Michel, 2010. "Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson–Siegel Model With Time-Varying Parameters," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(3), pages 329-343.
    14. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    15. Wali Ullah & Yasumasa Matsuda & Yoshihiko Tsukuda, 2013. "Term Structure Modeling and Forecasting of Government Bond Yields," Economic Papers, The Economic Society of Australia, vol. 32(4), pages 535-560, December.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    4. P. Byrne, Joseph & Cao, Shuo & Korobilis, Dimitris, 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," SIRE Discussion Papers 2015-71, Scottish Institute for Research in Economics (SIRE).
    5. 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.
    6. Wali Ullah, 2020. "The arbitrage-free generalized Nelson–Siegel term structure model: Does a good in-sample fit imply better out-of-sample forecasts?," Empirical Economics, Springer, vol. 59(3), pages 1243-1284, September.
    7. 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.
    8. Wali ULLAH & Khadija Malik BARI, 2018. "The Term Structure of Government Bond Yields in an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-28, September.
    9. P. Byrne, Joseph & Cao, Shuo & Korobilis, Dimitris, 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-71, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. 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.
    11. Dang-Nguyen, Stéphane & Le Caillec, Jean-Marc & Hillion, Alain, 2014. "The deterministic shift extension and the affine dynamic Nelson–Siegel model," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 402-417.
    12. Laurini, Márcio P. & Caldeira, João F., 2016. "A macro-finance term structure model with multivariate stochastic volatility," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 68-90.
    13. 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.
    14. Bruno Feunou & Jean-Sébastien Fontaine & Anh Le & Christian Lundblad, 2022. "Tractable Term Structure Models," Management Science, INFORMS, vol. 68(11), pages 8411-8429, November.
    15. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 1-33.
    16. 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.
    17. Levant, Jared & Ma, Jun, 2017. "A dynamic Nelson-Siegel yield curve model with Markov switching," Economic Modelling, Elsevier, vol. 67(C), pages 73-87.
    18. João F. Caldeira & Guilherme V. Moura & , Fabricio Tourrucôo, 2016. "Forecasting the yield curve with the arbitrage-free dynamic Nelson-Siegel model: Brazilian evidence," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 17(2), pages 221-237.
    19. Molenaars, Tomas K. & Reinerink, Nick H. & Hemminga, Marcus A., 2013. "Forecasting the yield curve - Forecast performance of the dynamic Nelson-Siegel model from 1971 to 2008," MPRA Paper 61862, University Library of Munich, Germany.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    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:taf:japsta:v:42:y:2015:i:4:p:876-904. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.