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What does the Yield Curve imply about Investor Expectations?

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Abstract

We find that investors' expectations of U.S. nominal yields, at different maturities and forecast horizons, exhibit significant time-variation during the Great Moderation. Nominal zero-coupon bond yields for the U.S. are used to fit the yield curve using a latent factor model. In the benchmark model, the VAR process used to characterize the conditional forecasts of yields has constant coefficients. The alternative class of models assume that investors use adaptive learning, in the form of a constant gain algorithm and different endogenous gain algorithms, which we propose here. Our results indicate that incorporating time-varying coefficients in the conditional forecasts of yields lead to large improvements in forecasting performance, at different maturities and horizons. These improvements are even more substantial during the Great Recession. We conclude that our results provide strong empirical motivation to use the class of adaptive learning models considered here, for modeling potential investor expectation formation in periods of low and high volatility, and the endogenous learning model leads to significant improvements over the benchmark in periods of high volatility. A policy experiment, which simulates a surprise shock to the level of the yield curve, illustrates that the conditional forecasts of yields implied by the learning models do significantly better at capturing the response observed in the realized yield curve, relative to the constant-coefficients model. Furthermore, the endogenous learning algorithm does well at matching the time-series patterns observed in expected excess returns implied by the Survey of Professional Forecasters.

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  • Eric Gaus & Arunima Sinha, 2014. "What does the Yield Curve imply about Investor Expectations?," Working Papers 14-02, Ursinus College, Department of Economics.
  • Handle: RePEc:urs:urswps:14-02
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    File URL: http://webpages.ursinus.edu/egaus/Research/GSYields.pdf
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    1. Stefano Eusepi & Bruce Preston, 2011. "Expectations, Learning, and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 101(6), pages 2844-2872, October.
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    5. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    6. Jeffrey C. Fuhrer, 1996. "Monetary Policy Shifts and Long-Term Interest Rates," The Quarterly Journal of Economics, Oxford University Press, vol. 111(4), pages 1183-1209.
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    13. Bianchi, Francesco & Mumtaz, Haroon & Surico, Paolo, 2009. "The great moderation of the term structure of UK interest rates," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 856-871, September.
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    Keywords

    Adaptive learning; Investor beliefs; Monetary policy; Excess returns;

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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