Advanced Search
MyIDEAS: Login to save this paper or follow this series

What does the Yield Curve imply about Investor Expectations?

Contents:

Author Info

  • Eric Gaus

    ()
    (Ursinus College)

  • Arunima Sinha

    ()
    (Santa Clara Univerisity)

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.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://webpages.ursinus.edu/egaus/Research/GSYields.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Ursinus College, Department of Economics in its series Working Papers with number 14-02.

as in new window
Length: pages
Date of creation: 10 Apr 2014
Date of revision:
Handle: RePEc:urs:urswps:14-02

Contact details of provider:
Postal: Ursinus College 601 East Main St. Collegeville, PA 19426
Web page: http://webpages.ursinus.edu/ecba/
More information through EDIRC

Related research

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

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Diebold, Francis X. & Li, Canlin, 2003. "Forecasting the term structure of government bond yields," CFS Working Paper Series 2004/09, Center for Financial Studies (CFS).
  2. Fabio Milani, 2005. "Expectations, Learning and Macroeconomic Persistence," Working Papers 050608, University of California-Irvine, Department of Economics.
  3. Hans Dewachter, 2004. "Macro factors and the term structure of interest rates," Money Macro and Finance (MMF) Research Group Conference 2003 25, Money Macro and Finance Research Group.
  4. Albert Marcet & Juan P. Nicolini, 1995. "Recurrent hyperinflations and learning," Economics Working Papers 244, Department of Economics and Business, Universitat Pompeu Fabra, revised Nov 2001.
  5. Sharon Kozicki & P.A. Tinsley, 1997. "Shifting endpoints in the term structure of interest rates," Research Working Paper 97-08, Federal Reserve Bank of Kansas City.
  6. 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.
  7. Eric Gaus, 2013. "Time-Varying Parameters and Endogenous Learning Algorithms," Working Papers 13-02, Ursinus College, Department of Economics.
  8. Thomas Laubach & Robert J. Tetlow & John C. Williams, 2007. "Learning and the Role of Macroeconomic Factors in the Term Structure of Interest Rates," 2007 Meeting Papers 476, Society for Economic Dynamics.
  9. Stefano Eusepi & Bruce Preston, 2008. "Expectations, Learning And Business Cycle Fluctuations," CAMA Working Papers 2008-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  10. 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.
  11. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-89, October.
  12. Glenn D. Rudebusch & Tao Wu, 2007. "Accounting for a Shift in Term Structure Behavior with No-Arbitrage and Macro-Finance Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(2-3), pages 395-422, 03.
  13. Fuhrer, Jeffrey C, 1996. "Monetary Policy Shifts and Long-Term Interest Rates," The Quarterly Journal of Economics, MIT Press, vol. 111(4), pages 1183-1209, November.
Full references (including those not matched with items on IDEAS)

Citations

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:urs:urswps:14-02. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Eric Gaus).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.