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Forecasting through the rear-view mirror: data revisions and bond return predictability

Author

Listed:
  • Eric Ghysels
  • Casidhe Horan
  • Emanuel Moench

Abstract

Real-time macroeconomic data reflect the information available to market participants, whereas final data—containing revisions and released with a delay—overstate the information set available to them. We document that the in-sample and out-of-sample Treasury return predictability is significantly diminished when real-time as opposed to revised macroeconomic data are used. In fact, much of the predictive information in macroeconomic time series is due to the data revision and publication lag components.

Suggested Citation

  • Eric Ghysels & Casidhe Horan & Emanuel Moench, 2012. "Forecasting through the rear-view mirror: data revisions and bond return predictability," Staff Reports 581, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:581
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    References listed on IDEAS

    as
    1. 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, August.
    2. S. Boragan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 319-340, March.
    3. Moench, Emanuel, 2008. "Forecasting the yield curve in a data-rich environment: A no-arbitrage factor-augmented VAR approach," Journal of Econometrics, Elsevier, vol. 146(1), pages 26-43, September.
    4. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    5. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    6. Stark, Tom & Croushore, Dean, 2002. "Reply to the comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 563-567, December.
    7. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    8. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    9. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    10. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    11. Christoffersen, Peter & Ghysels, Eric & Swanson, Norman R., 2002. "Let's get "real" about using economic data," Journal of Empirical Finance, Elsevier, vol. 9(3), pages 343-360, August.
    12. Gilbert, Thomas, 2011. "Information aggregation around macroeconomic announcements: Revisions matter," Journal of Financial Economics, Elsevier, vol. 101(1), pages 114-131, July.
    13. Scott Joslin & Kenneth J. Singleton & Haoxiang Zhu, 2011. "A New Perspective on Gaussian Dynamic Term Structure Models," Review of Financial Studies, Society for Financial Studies, vol. 24(3), pages 926-970.
    14. Adrian, Tobias & Crump, Richard K. & Moench, Emanuel, 2013. "Pricing the term structure with linear regressions," Journal of Financial Economics, Elsevier, vol. 110(1), pages 110-138.
    15. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    16. John H. Cochrane & Monika Piazzesi, 2005. "Bond Risk Premia," American Economic Review, American Economic Association, vol. 95(1), pages 138-160, March.
    17. Ludvigson, Sydney C. & Ng, Serena, 2007. "The empirical risk-return relation: A factor analysis approach," Journal of Financial Economics, Elsevier, vol. 83(1), pages 171-222, January.
    18. Fama, Eugene F & Bliss, Robert R, 1987. "The Information in Long-Maturity Forward Rates," American Economic Review, American Economic Association, vol. 77(4), pages 680-692, September.
    19. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    20. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
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    Cited by:

    1. Beber, Alessandro & Brandt, Michael & Luisi, Maurizio, 2013. "Eurozone Sovereign Yield Spreads and Diverging Economic Fundamentals," CEPR Discussion Papers 9538, C.E.P.R. Discussion Papers.
    2. Alessandro Beber & Michael W. Brandt & Maurizio Luisi, 2013. "Distilling the Macroeconomic News Flow," NBER Working Papers 19650, National Bureau of Economic Research, Inc.
    3. Leo Krippner & Michelle Lewis, 2018. "Real-time forecasting with macro-finance models in the presence of a zero lower bound," Reserve Bank of New Zealand Discussion Paper Series DP2018/04, Reserve Bank of New Zealand.
    4. Beber, Alessandro & Brandt, Michael W. & Luisi, Maurizio, 2015. "Distilling the macroeconomic news flow," Journal of Financial Economics, Elsevier, vol. 117(3), pages 489-507.
    5. Beber, Alessandro & Brandt, Michael & Luisi, Maurizio, 2013. "Economic Cycles and Expected Stock Returns," CEPR Discussion Papers 9528, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Real-time data ; Treasury bonds ; Government securities ; Time-series analysis ; Rate of return ; Macroeconomics;

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