This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Efficient Prediction of Excess Returns

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Jon Faust
Jonathan H. Wright

Additional information is available for the following registered author(s):

Abstract

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.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. 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
File Format: application/pdf
File Function:
Download Restriction: Access to the full text is generally limited to series subscribers, however if the top level domain of the client browser is in a developing country or transition economy free access is provided. More information about subscriptions and free access is available at http://www.nber.org/wwphelp.html.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

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

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: Jul 2008
Date of revision:
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
Email:
Web page: http://www.nber.org
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: ().

Related research
Keywords:

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies

This paper has been announced in the following NEP Reports:

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.:
  1. 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. [Downloadable!] (restricted)
    Other versions:
  2. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Vega, Clara, 2007. "Real-time price discovery in global stock, bond and foreign exchange markets," Journal of International Economics, Elsevier, vol. 73(2), pages 251-277, November. [Downloadable!] (restricted)
    Other versions:
  3. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, 07. [Downloadable!] (restricted)
    Other versions:
  4. 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. [Downloadable!]
  5. Christina D. Romer & David H. Romer, 2000. "Federal Reserve Information and the Behavior of Interest Rates," American Economic Review, American Economic Association, vol. 90(3), pages 429-457, June. [Downloadable!] (restricted)
  6. John H. Cochrane & Monika Piazzesi, 2005. "Bond Risk Premia," American Economic Review, American Economic Association, vol. 95(1), pages 138-160, March. [Downloadable!]
    Other versions:
  7. Andrew Ang & Geert Bekaert, 2001. "Stock Return Predictability: Is it There?," NBER Working Papers 8207, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  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-.
    Other versions:
  9. 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. [Downloadable!] (restricted)
  10. 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. [Downloadable!] (restricted)
  11. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 5(3), pages 357-86. [Downloadable!] (restricted)
  12. Robert F. Stambaugh, 1999. "Predictive Regressions," NBER Technical Working Papers 0240, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  13. 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. [Downloadable!]
    Other versions:
  14. Lutz Kilian, 2008. "Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy?," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 216-240, 03. [Downloadable!] (restricted)
    Other versions:
  15. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May. [Downloadable!] (restricted)
    Other versions:
  16. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July. [Downloadable!] (restricted)
    Other versions:
Full references

Statistics
Access and download statistics

Did you know? RePEc encourages publishers to make their bibliographic data freely available to the public.

This page was last updated on 2009-11-14.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.