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Parsimonious modeling and forecasting of corporate yield curve

Author

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  • Wei-Choun Yu

    (Economics and Finance Department, Winona State University, Winona, Minnesota, USA)

  • Donald M. Salyards

    (Economics and Finance Department, Winona State University, Winona, Minnesota, USA)

Abstract

This paper investigates the sensitivity of out-of-sample forecasting performance over a span of different parameters of l in the dynamic Nelson-Siegel three-factor AR(1) model. First, we find that the ad hoc selection of l is not optimal. Second, we find a substantial difference in factor dynamics between investment-grade and speculative-grade corporate bonds from 1994:12 to 2006: 4. Third, we suggest that the three-factor model is sufficient to explain the main variations of corporate yield changes. Finally, the parsimonious Nelson-Siegel three-factor AR(1) model remains competitive in the out-of-sample forecasting of corporate yields. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Wei-Choun Yu & Donald M. Salyards, 2009. "Parsimonious modeling and forecasting of corporate yield curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 73-88.
    • Handle: RePEc:jof:jforec:v:28:y:2009:i:1:p:73-88
    DOI: 10.1002/for.1092
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    References listed on IDEAS

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    Cited by:

    1. Yifeng Yan & Ju'e Guo, 2015. "The Sovereign Yield Curve and the Macroeconomy in China," Pacific Economic Review, Wiley Blackwell, vol. 20(3), pages 415-441, August.
    2. Yu, Wei-Choun & Zivot, Eric, 2011. "Forecasting the term structures of Treasury and corporate yields using dynamic Nelson-Siegel models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 579-591.
    3. Yasir Riaz & Choudhry T. Shehzad & Zaghum Umar, 2021. "The sovereign yield curve and credit ratings in GIIPS," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 895-916, September.
    4. David Y. Aharon & Zaghum Umar & Xuan Vinh Vo, 2021. "Dynamic spillovers between the term structure of interest rates, bitcoin, and safe-haven currencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-25, December.
    5. 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.
    6. Levant, Jared & Ma, Jun, 2017. "A dynamic Nelson-Siegel yield curve model with Markov switching," Economic Modelling, Elsevier, vol. 67(C), pages 73-87.
    7. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
    8. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Alexey Akimov & Simon Stevenson & Maxim Zagonov, 2015. "Public Real Estate and the Term Structure of Interest Rates: A Cross-Country Study," The Journal of Real Estate Finance and Economics, Springer, vol. 51(4), pages 503-540, November.
    10. Gerhart, Christoph & Lütkebohmert, Eva, 2020. "Empirical analysis and forecasting of multiple yield curves," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 59-78.

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