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Forecasting Interest Rates

In: Handbook of Economic Forecasting

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  • Duffee, Gregory

Abstract

This chapter discusses what the asset-pricing literature concludes about the forecastability of interest rates. It outlines forecasting methodologies implied by this literature, including dynamic, no-arbitrage term structure models and their macro-finance extensions. It also reviews the empirical evidence concerning the predictability of future yields on Treasury bonds and future excess returns to holding these bonds. In particular, it critically evaluates theory and evidence that variables other than current bond yields are useful in forecasting.

Suggested Citation

  • Duffee, Gregory, 2013. "Forecasting Interest Rates," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 385-426, Elsevier.
  • Handle: RePEc:eee:ecofch:2-385
    DOI: 10.1016/B978-0-444-53683-9.00007-4
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    7. Antonio Gargano & Davide Pettenuzzo & Allan Timmermann, 2019. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Management Science, INFORMS, vol. 65(2), pages 508-540, February.
    8. Kaminska, Iryna & Mumtaz, Haroon & Šustek, Roman, 2021. "Monetary policy surprises and their transmission through term premia and expected interest rates," Journal of Monetary Economics, Elsevier, vol. 124(C), pages 48-65.
    9. Rasmus Fatum & Naoko Hara & Yohei Yamamoto, 2019. "Negative Interest Rate Policy and the Influence of Macroeconomic News on Yields," GRU Working Paper Series GRU_2019_006, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    10. Horváth, Lajos & Liu, Zhenya & Rice, Gregory & Wang, Shixuan, 2020. "A functional time series analysis of forward curves derived from commodity futures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 646-665.
    11. Samuel G Hanson & David O Lucca & Jonathan H Wright, 2021. "Rate-Amplifying Demand and the Excess Sensitivity of Long-Term Rates," The Quarterly Journal of Economics, Oxford University Press, vol. 136(3), pages 1719-1781.
    12. Chernov, Mikhail & Creal, Drew & Hördahl, Peter, 2020. "Sovereign credit and exchange rate risks: Evidence from Asia-Pacific local currency bonds," CEPR Discussion Papers 14986, C.E.P.R. Discussion Papers.
    13. Stolyarov, Dmitriy & Tesar, Linda L., 2021. "Interest rate trends in a global context," Economic Modelling, Elsevier, vol. 101(C).
    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. Zhang, Yugui & Zhu, Jie & Zhu, Xiaoneng, 2021. "Global bond risk premia under falling stars," Finance Research Letters, Elsevier, vol. 42(C).
    16. Zura Kakushadze & Willie Yu, 2020. "Machine Learning Treasury Yields," Bulletin of Applied Economics, Risk Market Journals, vol. 7(1), pages 1-65.
    17. Peter Feldhütter, 2016. "Can Affine Models Match the Moments in Bond Yields?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 1-56, June.
    18. Zura Kakushadze & Willie Yu, 2020. "Machine Learning Treasury Yields," Papers 2003.05095, arXiv.org.
    19. Giuseppe Arbia & Michele Di Marcantonio, 2015. "Forecasting Interest Rates Using Geostatistical Techniques," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    20. Bretscher, Lorenzo & Hsu, Alex & Tamoni, Andrea, 2020. "Fiscal policy driven bond risk premia," Journal of Financial Economics, Elsevier, vol. 138(1), pages 53-73.

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