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Forecasting the term structures of Treasury and corporate yields using dynamic Nelson-Siegel models

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  • Yu, Wei-Choun
  • Zivot, Eric
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    Abstract

    We extend Diebold and Li’s dynamic Nelson-Siegel three-factor model to a broader empirical prospective by including the evaluation of the state space approach and by using nine different ratings for corporate bonds. We find that the dynamic Nelson-Siegel factor AR(1) model outperforms other competitors on the out-of-sample forecast accuracy, especially on the investment-grade bonds for the short-term forecast horizon and on the high-yield bonds for the long-term forecast horizon. The dynamic Nelson-Siegel factor state space model, however, becomes appealing on the high-yield bonds in the short-term forecast horizon, where the factor dynamics are more likely time-varying and parameter instability is more probable in the model specification.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0169207010000956
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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Forecasting.

    Volume (Year): 27 (2011)
    Issue (Month): 2 ()
    Pages: 579-591

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    Handle: RePEc:eee:intfor:v:27:y:2011:i:2:p:579-591

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    Web page: http://www.elsevier.com/locate/ijforecast

    Related research

    Keywords: Term structures; Treasury yields; Corporate yields; Nelson-Siegel model; Factor model; AR(1); VAR(1); Out-of-sample forecasting evaluations;

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    Cited by:
    1. Kaya, Huseyin, 2013. "Forecasting the yield curve and the role of macroeconomic information in Turkey," Economic Modelling, Elsevier, vol. 33(C), pages 1-7.
    2. Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper Series 59_12, The Rimini Centre for Economic Analysis, revised Sep 2012.

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