IDEAS home Printed from https://ideas.repec.org/p/bok/wpaper/1419.html
   My bibliography  Save this paper

Forecasting the Term Structure of Government Bond Yields Using Credit Spreads and Structural Breaks

Author

Listed:
  • Azamat Abdymomunov

    (The Federal Reserve Bank of Richmond)

  • Kyu Ho Kang

    (Department of Economics, Korea University)

  • Ki Jeong Kim

    (The Bank of Korea)

Abstract

In this paper, we investigate whether credit spread curve information helps forecast the government bond yield curve and whether the joint dynamics of the government bond yields and credit spreads have structural changes. For this purpose, we use a joint dynamic Nelson-Siegel (DNS) model of the term structures of U.S. Treasury interest rates and credit spreads. We find that this joint model produces substantially more accurate out-of-sample Treasury yields forecasts compared with a standard DNS yield curve only model. We also find that the predictive gain from incorporating the credit spread curve information substantially increases if the joint model accounts for structural changes in the dynamics of yield and credit spread curves. In addition, our model incorporates a zero lower bound restriction ensuring that our predictions are economically plausible.

Suggested Citation

  • Azamat Abdymomunov & Kyu Ho Kang & Ki Jeong Kim, 2014. "Forecasting the Term Structure of Government Bond Yields Using Credit Spreads and Structural Breaks," Working Papers 2014-19, Economic Research Institute, Bank of Korea.
  • Handle: RePEc:bok:wpaper:1419
    as

    Download full text from publisher

    File URL: http://papers.bok.or.kr/RePEc_attach/wpaper/english/wp-2014-19.pdf
    File Function: Working Paper, 2014
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Morten L Bech & Yvan Lengwiler, 2012. "The financial crisis and the changing dynamics of the yield curve," BIS Papers chapters, in: Bank for International Settlements (ed.), Threat of fiscal dominance?, volume 65, pages 257-276, Bank for International Settlements.
    3. Chib, Siddhartha & Ergashev, Bakhodir, 2009. "Analysis of Multifactor Affine Yield Curve Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1324-1337.
    4. Hamilton, James D & Kim, Dong Heon, 2002. "A Reexamination of the Predictability of Economic Activity Using the Yield Spread," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 340-360, May.
    5. 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.
    6. Qiang Dai & Kenneth J. Singleton & Wei Yang, 2007. "Regime Shifts in a Dynamic Term Structure Model of U.S. Treasury Bond Yields," Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1669-1706, 2007 12.
    7. Simon Gilchrist & Egon Zakrajsek, 2012. "Credit Spreads and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 102(4), pages 1692-1720, June.
    8. Andrew Ang & Geert Bekaert & Min Wei, 2008. "The Term Structure of Real Rates and Expected Inflation," Journal of Finance, American Finance Association, vol. 63(2), pages 797-849, April.
    9. Bill Bassin, 2007. "Book Review of Mirror, Mirror, Who’s the Best Forecaster of Them All? (by Michael F. Bryan and Linsey Molloy of the Federal Reserve Bank of Cleveland)," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 45-46, Fall.
    10. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    11. Zantedeschi, Daniel & Damien, Paul & Polson, Nicholas G., 2011. "Predictive Macro-Finance With Dynamic Partition Models," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 427-439.
    12. Gregory R. Duffee, 1998. "The Relation Between Treasury Yields and Corporate Bond Yield Spreads," Journal of Finance, American Finance Association, vol. 53(6), pages 2225-2241, December.
    13. Davies, Andrew, 2008. "Credit spread determinants: An 85 year perspective," Journal of Financial Markets, Elsevier, vol. 11(2), pages 180-197, May.
    14. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
    15. Siddhartha Chib & Kyu Ho Kang, 2013. "Change-Points in Affine Arbitrage-Free Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 302-334, March.
    16. Longstaff, Francis A & Schwartz, Eduardo S, 1995. "A Simple Approach to Valuing Risky Fixed and Floating Rate Debt," Journal of Finance, American Finance Association, vol. 50(3), pages 789-819, July.
    17. Pierre Collin-Dufresn & Robert S. Goldstein & J. Spencer Martin, 2001. "The Determinants of Credit Spread Changes," Journal of Finance, American Finance Association, vol. 56(6), pages 2177-2207, 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. Abdymomunov, Azamat & Kang, Kyu Ho & Kim, Ki Jeong, 2016. "Can credit spreads help predict a yield curve?," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 39-61.
    2. Kim, Young Min & Kang, Kyu Ho & Ka, Kook, 2020. "Do bond markets find inflation targets credible? Evidence from five inflation-targeting countries," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 66-84.
    3. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    4. Jiang, Yong & Liu, Cenjie & Xie, Rui, 2021. "Oil price shocks and credit spread: Structural effect and dynamic spillover," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    5. Richard K. Crump & Stefano Eusepi & Emanuel Moench, 2016. "The term structure of expectations and bond yields," Staff Reports 775, Federal Reserve Bank of New York.
    6. Zhu, Xiaoneng & Rahman, Shahidur, 2015. "A regime-switching Nelson–Siegel term structure model of the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 1-17.
    7. Abdymomunov, Azamat & Gerlach, Jeffrey, 2014. "Stress testing interest rate risk exposure," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 287-301.
    8. 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.
    9. Maalaoui Chun, Olfa & Dionne, Georges & François, Pascal, 2014. "Credit spread changes within switching regimes," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 41-55.
    10. Okimoto, Tatsuyoshi & Takaoka, Sumiko, 2020. "No-arbitrage determinants of credit spread curves under the unconventional monetary policy regime in Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 64(C).
    11. Shi, Yukun & Stasinakis, Charalampos & Xu, Yaofei & Yan, Cheng, 2022. "Market co-movement between credit default swap curves and option volatility surfaces," International Review of Financial Analysis, Elsevier, vol. 82(C).
    12. Huang, Xiaoyong & Yu, Cong & Chen, Yunping & Jia, Fei & Xu, Xiangyun, 2022. "Rigid payment breaking, default spread and yields of Chinese treasury bonds," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    13. Avino, Davide & Nneji, Ogonna, 2014. "Are CDS spreads predictable? An analysis of linear and non-linear forecasting models," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 262-274.
    14. Doshi, Hitesh & Jacobs, Kris & Liu, Rui, 2018. "Macroeconomic determinants of the term structure: Long-run and short-run dynamics," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 99-122.
    15. Gilchrist, Simon & Yankov, Vladimir & Zakrajsek, Egon, 2009. "Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 471-493, May.
    16. Ephraim Clark & Selima Baccar, 2018. "Modelling credit spreads with time volatility, skewness, and kurtosis," Annals of Operations Research, Springer, vol. 262(2), pages 431-461, March.
    17. OKIMOTO Tatsuyoshi & TAKAOKA Sumiko, 2017. "No-arbitrage Determinants of Japanese Government Bond Yield and Credit Spread Curves," Discussion papers 17104, Research Institute of Economy, Trade and Industry (RIETI).
    18. Okimoto, Tatsuyoshi & Takaoka, Sumiko, 2017. "The term structure of credit spreads and business cycle in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 45(C), pages 27-36.
    19. Batten, Jonathan A. & Jacoby, Gady & Liao, Rose C., 2014. "Corporate yield spreads and real interest rates," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 89-100.
    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

    Keywords

    Out-of-sample forecasting; term structure; credit spread; Nelson-Siegel model; Bayesian MCMC estimation;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

    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:bok:wpaper:1419. 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: Economic Research Institute (email available below). General contact details of provider: https://edirc.repec.org/data/imbokkr.html .

    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.