IDEAS home Printed from https://ideas.repec.org/p/bcb/wpaper/288.html
   My bibliography  Save this paper

Forecasting Bond Yields with Segmented Term Structure Models

Author

Listed:
  • Caio Almeida
  • Axel Simonsen
  • José Vicente

Abstract

Recent empirical analysis of interest rate markets documents that bond demand and supply directly affect yield curve movements and bond risk premium. Motivated by those findings we propose a parametric interest rate model that allows for segmentation and local shocks in the term structure. We split the yield curve in segments presenting their own local movements that are globally interconnected by smoothing conditions. Two classes of segmented exponential models are derived and compared to successful term structure models based on a sequence of out-of-sample forecasting exercises. Adopting U.S. interest rates data available from 1985 to 2008, the segmented models present overall better forecasting performance suggesting that local shocks might indeed be important determinants of yield curve dynamics.

Suggested Citation

  • Caio Almeida & Axel Simonsen & José Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.
  • Handle: RePEc:bcb:wpaper:288
    as

    Download full text from publisher

    File URL: http://www.bcb.gov.br/pec/wps/ingl/wps288.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, pages 183-217.
    2. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    3. Almeida, Caio & Vicente, José, 2008. "The role of no-arbitrage on forecasting: Lessons from a parametric term structure model," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2695-2705, December.
    4. 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.
    5. Caio Almeida & Romeu Gomes & André Leite & José Vicente, 2007. "Does Curvature Enhance Forecasting?," Working Papers Series 155, Central Bank of Brazil, Research Department.
    6. Dennis, Richard & Ravenna, Federico, 2008. "Learning and optimal monetary policy," Journal of Economic Dynamics and Control, Elsevier, pages 1964-1994.
    7. John H. Cochrane & Monika Piazzesi, 2005. "Bond Risk Premia," American Economic Review, American Economic Association, pages 138-160.
    8. Andrea Carriero, 2011. "Forecasting The Yield Curve Using Priors From No‐Arbitrage Affine Term Structure Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(2), pages 425-459, May.
    9. 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.
    10. Matthieu Bussière & Jarko Fidrmuc & Bernd Schnatz, 2005. "Trade Integration of Central and Eastern European Countries: Lessons from a Gravity Model," Working Papers 105, Oesterreichische Nationalbank (Austrian Central Bank).
    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, pages 4-20.
    12. 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.
    13. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, pages 1509-1531.
    14. Barbara Rossi & Atsushi Inoue, 2011. "Out-of-Sample Forecast Tests Robust to Window Size Choice," Working Papers 11-04, Duke University, Department of Economics.
    15. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    16. 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, pages 1419-1437.
    17. Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
    18. Jang-Ting Guo & Kevin J. Lansing, 2008. "Capital-Labor Substitution, Equilibrium Indeterminacy, and the Cyclical Behavior of Labor Income," Working Papers 200804, University of California at Riverside, Department of Economics, revised Apr 2008.
    19. 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.
    20. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.
    21. J. M. Culbertson, 1957. "The Term Structure of Interest Rates," The Quarterly Journal of Economics, Oxford University Press, vol. 71(4), pages 485-517.
    22. 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.
    23. Carriero, Andrea & Giacomini, Raffaella, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Journal of Econometrics, Elsevier, pages 21-34.
    24. 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.
    25. Moench, Emanuel, 2008. "Forecasting the yield curve in a data-rich environment: A no-arbitrage factor-augmented VAR approach," Journal of Econometrics, Elsevier, vol. 146(1), pages 26-43, September.
    26. Svensson, L.E.O., 1993. "Monetary Policy with Flexible Exchange Rates and Foreward Interest Rates as Indicators," Papers 559, Stockholm - International Economic Studies.
    27. 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, February.
    28. 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.
    29. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    30. repec:wsi:ijtafx:v:12:y:2009:i:08:n:s0219024909005622 is not listed on IDEAS
    31. Darrell Duffie & Rui Kan, 1996. "A Yield-Factor Model Of Interest Rates," Mathematical Finance, Wiley Blackwell, vol. 6(4), pages 379-406.
    32. Almeida, Caio & Graveline, Jeremy J. & Joslin, Scott, 2011. "Do interest rate options contain information about excess returns?," Journal of Econometrics, Elsevier, vol. 164(1), pages 35-44, September.
    33. 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 116-126, February.
    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. Bruno Martins, 2012. "Local Market Structure and Bank Competition: evidence from the Brazilian auto loan market," Working Papers Series 299, Central Bank of Brazil, Research Department.
    2. Duffee, Gregory, 2013. "Forecasting Interest Rates," Handbook of Economic Forecasting, Elsevier.
    3. Papadimitriou, Theophilos & Gogas, Periklis & Tabak, Benjamin M., 2013. "Complex networks and banking systems supervision," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4429-4434.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bcb:wpaper:288. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Francisco Marcos Rodrigues Figueiredo). General contact details of provider: http://www.bcb.gov.br/?english .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.