IDEAS home Printed from
   My bibliography  Save this paper

Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields


  • Hautsch, Nikolaus
  • Ou, Yangguoyi


We propose a Nelson-Siegel type interest rate term structure model where the underlying yield factors follow autoregressive processes with stochastic volatility. The factor volatilities parsimoniously capture risk inherent to the term structure and are associated with the time-varying uncertainty of the yield curve's level, slope and curvature. Estimating the model based on U.S. government bond yields applying Markov chain Monte Carlo techniques we find that the factor volatilities follow highly persistent processes. We show that slope and curvature risk have explanatory power for bond excess returns and illustrate that the yield and volatility factors are closely related to industrial capacity utilization, inflation, monetary policy and employment growth.

Suggested Citation

  • Hautsch, Nikolaus & Ou, Yangguoyi, 2009. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," CFS Working Paper Series 2009/03, Center for Financial Studies (CFS).
  • Handle: RePEc:zbw:cfswop:200903

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. Hordahl, Peter & Tristani, Oreste & Vestin, David, 2006. "A joint econometric model of macroeconomic and term-structure dynamics," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 405-444.
    2. Hansen, Lars Peter & Hodrick, Robert J, 1980. "Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric Analysis," Journal of Political Economy, University of Chicago Press, vol. 88(5), pages 829-853, October.
    3. Evans, Charles L. & Marshall, David A., 2007. "Economic determinants of the nominal treasury yield curve," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 1986-2003, October.
    4. John C. Cox & Jonathan E. Ingersoll Jr. & Stephen A. Ross, 2005. "A Theory Of The Term Structure Of Interest Rates," World Scientific Book Chapters,in: Theory Of Valuation, chapter 5, pages 129-164 World Scientific Publishing Co. Pte. Ltd..
    5. GlennD. Rudebusch & Tao Wu, 2008. "A Macro-Finance Model of the Term Structure, Monetary Policy and the Economy," Economic Journal, Royal Economic Society, vol. 118(530), pages 906-926, July.
    6. John H. Cochrane & Monika Piazzesi, 2005. "Bond Risk Premia," American Economic Review, American Economic Association, vol. 95(1), pages 138-160, March.
    7. Engle, Robert F & Ng, Victor K, 1993. "Time-Varying Volatility and the Dynamic Behavior of the Term Structure," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 25(3), pages 336-349, August.
    8. Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
    9. Vasicek, Oldrich, 1977. "An equilibrium characterization of the term structure," Journal of Financial Economics, Elsevier, vol. 5(2), pages 177-188, November.
    10. Andrew C. Harvey, 1990. "The Econometric Analysis of Time Series, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026208189x, January.
    11. 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.
    12. Hautsch, Nikolaus & Yang, Fuyu, 2012. "Bayesian inference in a Stochastic Volatility Nelson–Siegel model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3774-3792.
    13. John Y. Campbell & Robert J. Shiller, 1991. "Yield Spreads and Interest Rate Movements: A Bird's Eye View," Review of Economic Studies, Oxford University Press, vol. 58(3), pages 495-514.
    14. 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.
    15. 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.
    16. Engle, Robert F. & Ng, Victor K. & Rothschild, Michael, 1990. "Asset pricing with a factor-arch covariance structure : Empirical estimates for treasury bills," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 213-237.
    17. 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.
    18. 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..
    19. 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.
    20. Darrell Duffie & Rui Kan, 1996. "A Yield-Factor Model Of Interest Rates," Mathematical Finance, Wiley Blackwell, vol. 6(4), pages 379-406.
    21. 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.
    22. Hull, John & White, Alan, 1990. "Valuing Derivative Securities Using the Explicit Finite Difference Method," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(01), pages 87-100, March.
    23. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    24. repec:pit:wpaper:321 is not listed on IDEAS
    25. Vasicek, Oldrich Alfonso, 1977. "Abstract: An Equilibrium Characterization of the Term Structure," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(04), pages 627-627, November.
    26. Richard, Jean-Francois & Zhang, Wei, 2007. "Efficient high-dimensional importance sampling," Journal of Econometrics, Elsevier, vol. 141(2), pages 1385-1411, December.
    27. Fama, Eugene F & Bliss, Robert R, 1987. "The Information in Long-Maturity Forward Rates," American Economic Review, American Economic Association, vol. 77(4), pages 680-692, September.
    28. Dai, Qiang & Singleton, Kenneth J., 2002. "Expectation puzzles, time-varying risk premia, and affine models of the term structure," Journal of Financial Economics, Elsevier, vol. 63(3), pages 415-441, March.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. repec:eee:ejores:v:262:y:2017:i:3:p:1116-1135 is not listed on IDEAS
    2. Shin, Minchul & Zhong, Molin, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    3. Christensen, Jens H.E. & Lopez, Jose A. & Rudebusch, Glenn D., 2014. "Can Spanned Term Structure Factors Drive Stochastic Yield Volatility?," Working Paper Series 2014-3, Federal Reserve Bank of San Francisco.
    4. Minchul Shin & Molin Zhong, 2013. "Does realized volatility help bond yield density prediction?," PIER Working Paper Archive 13-064, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    5. Maria Cristina Recchioni & Gabriele Tedeschi, 2016. "From bond yield to macroeconomic instability: The effect of negative interest rates," Working Papers 2016/06, Economics Department, Universitat Jaume I, Castellón (Spain).
    6. Shin, Minchul & Zhong, Molin, 2017. "Does realized volatility help bond yield density prediction?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 373-389.

    More about this item


    Term Structure Modelling; Yield Curve Risk; Stochastic Volatility; Factor Models; Macroeconomic Fundamentals;

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • G1 - Financial Economics - - General Financial Markets


    Access and download statistics


    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:zbw:cfswop:200903. 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: (ZBW - German National Library of Economics). General contact details of provider: .

    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.