IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Efficient Prediction of Excess Returns

  • Jon Faust
  • Jonathan H. Wright

It is well known that augmenting a standard linear regression model with variables that are correlated with the error term but uncorrelated with the original regressors will increase asymptotic efficiency of the original coefficients. We argue that in the context of predicting excess returns, valid augmenting variables exist and are likely to yield substantial gains in estimation efficiency and, hence, predictive accuracy. The proposed augmenting variables are ex post measures of an unforecastable component of excess returns: ex post errors from macroeconomic survey forecasts and the surprise components of asset price movements around macroeconomic news announcements. These "surprises" cannot be used directly in forecasting--they are not observed at the time that the forecast is made--but can nonetheless improve forecasting accuracy by reducing parameter estimation uncertainty. We derive formal results about the benefits and limits of this approach and apply it to standard examples of forecasting excess bond and equity returns. We find substantial improvements in out-of-sample forecast accuracy for standard excess bond return regressions; gains for forecasting excess stock returns are much smaller.

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://www.nber.org/papers/w14169.pdf
Download Restriction: no

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 14169.

as
in new window

Length:
Date of creation: Jul 2008
Date of revision:
Publication status: published as May 2011, Vol. 93, No. 2, Pages 647-659 Posted Online April 26, 2011. (doi:10.1162/REST_a_00092) © 2011 The President and Fellows of Harvard College and the Massachusetts Institute of Technology Efficient Prediction of Excess Returns Jon Faust Johns Hopkins University Jonathan H. Wright Johns Hopkins University
Handle: RePEc:nbr:nberwo:14169
Note: AP ME
Contact details of provider: Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
Phone: 617-868-3900
Web page: http://www.nber.org
Email:


More information through EDIRC

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. Froot, Kenneth A, 1989. " New Hope for the Expectations Hypothesis of the Term Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 44(2), pages 283-305, June.
  2. Goetzmann, William Nelson & Jorion, Philippe, 1993. " Testing the Predictive Power of Dividend Yields," Journal of Finance, American Finance Association, vol. 48(2), pages 663-79, June.
  3. Kilian, Lutz, 2005. "Exogenous Oil Supply Shocks: How Big Are They and How Much do they Matter for the US Economy?," CEPR Discussion Papers 5131, C.E.P.R. Discussion Papers.
  4. Evan Koenig & Sheila Dolmas & Jeremy M. Piger, 2002. "The use and abuse of 'real-time' data in economic forecasting," Working Papers 2001-015, Federal Reserve Bank of St. Louis.
  5. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2007. "Real-Time Price Discovery in Global Stock, Bond and Foreign Exchange Markets," CREATES Research Papers 2007-20, School of Economics and Management, University of Aarhus.
  6. Bruce E. Hansen, 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Boston College Working Papers in Economics 300., Boston College Department of Economics.
  7. Robert F. Stambaugh, 1999. "Predictive Regressions," NBER Technical Working Papers 0240, National Bureau of Economic Research, Inc.
  8. Pierluigi Balduzzi & Edwin J. Elton & T. Clifton Green, 1997. "Economic News and the Yield Curve: Evidence from the U.S. Treasury Market," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-005, New York University, Leonard N. Stern School of Business-.
  9. Andrew Ang & Geert Bekaert & Min Wei, 2006. "Do macro variables, asset markets, or surveys forecast inflation better?," Finance and Economics Discussion Series 2006-15, Board of Governors of the Federal Reserve System (U.S.).
  10. Andrew Ang & Geert Bekaert, 2001. "Stock Return Predictability: Is it There?," NBER Working Papers 8207, National Bureau of Economic Research, Inc.
  11. Campbell, John & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Scholarly Articles 3122601, Harvard University Department of Economics.
  12. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Real-Time Price Discovery in Stock, Bond and Foreign Exchange Markets," PIER Working Paper Archive 04-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 28 Jun 2004.
  13. Shiller, Robert & Campbell, John, 1991. "Yield Spreads and Interest Rate Movements: A Bird's Eye View," Scholarly Articles 3221490, Harvard University Department of Economics.
  14. Elliott, Graham & Stock, James H., 1994. "Inference in Time Series Regression When the Order of Integration of a Regressor is Unknown," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 672-700, August.
  15. David H. Romer & Christina D. Romer, 2000. "Federal Reserve Information and the Behavior of Interest Rates," American Economic Review, American Economic Association, vol. 90(3), pages 429-457, June.
  16. John H. Cochrane & Monika Piazzesi, 2002. "Bond Risk Premia," NBER Working Papers 9178, National Bureau of Economic Research, Inc.
  17. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
  18. Yash P. Mehra, 2002. "Survey measures of expected inflation : revisiting the issues of predictive content and rationality," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 17-36.
  19. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-86.
Full references (including those not matched with items on IDEAS)

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

When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:14169. 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: ()

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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.