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Fitting and forecasting yield curves with a mixed-frequency affine model: Evidence from China

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  • Shang, Yuhuang
  • Zheng, Tingguo

Abstract

This paper proposes a novel mixed-frequency affine term structure model to improving the fit and forecasting ability of yield curves. We also show the Bayesian estimation method related to this mixed-frequency model. Then we conduct an empirical study using Chinese macro and financial data. The empirical results show that compared with the traditional same-frequency affine model, the mixed-frequency affine model offers superior performance for fitting the yield curve and term structure factors. Specifically, this mixed-frequency affine model can provide more accurate out-of-sample forecast results of the yield curve.

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  • Shang, Yuhuang & Zheng, Tingguo, 2018. "Fitting and forecasting yield curves with a mixed-frequency affine model: Evidence from China," Economic Modelling, Elsevier, vol. 68(C), pages 145-154.
    • Handle: RePEc:eee:ecmode:v:68:y:2018:i:c:p:145-154
    DOI: 10.1016/j.econmod.2017.07.002
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    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. 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.
    3. 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.
    4. Paccagnini, Alessia, 2016. "The macroeconomic determinants of the US term structure during the Great Moderation," Economic Modelling, Elsevier, vol. 52(PA), pages 216-225.
    5. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    6. 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.
    7. Scott Joslin & Marcel Priebsch & Kenneth J. Singleton, 2014. "Risk Premiums in Dynamic Term Structure Models with Unspanned Macro Risks," Journal of Finance, American Finance Association, vol. 69(3), pages 1197-1233, June.
    8. Glenn D. 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.
    9. Peter Fuleky & Carl S. Bonham, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 201316, University of Hawaii at Manoa, Department of Economics.
    10. Kaya, Huseyin, 2013. "Forecasting the yield curve and the role of macroeconomic information in Turkey," Economic Modelling, Elsevier, vol. 33(C), pages 1-7.
    11. Carlo A. Favero & Linlin Niu & Luca Sala, 2012. "Term Structure Forecasting: No‐Arbitrage Restrictions versus Large Information Set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(2), pages 124-156, March.
    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. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    14. Peter Spreij & Enno Veerman & Peter Vlaar, 2011. "An Affine Two-Factor Heteroskedastic Macro-Finance Term Structure Model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 18(4), pages 331-352.
    15. 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.
    16. 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.
    17. Darrell Duffie & Rui Kan, 1996. "A Yield‐Factor Model Of Interest Rates," Mathematical Finance, Wiley Blackwell, vol. 6(4), pages 379-406, October.
    18. 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.
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    4. Candelon, Bertrand & Moura, Rubens, 2023. "Sovereign yield curves and the COVID-19 in emerging markets," Economic Modelling, Elsevier, vol. 127(C).

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