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Efficient Prediction of Excess Returns

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  • Jon Faust

    (Johns Hopkins University)

  • Jonathan H. Wright

    (Johns Hopkins University)

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 the 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, the surprise components of asset price movements around macroeconomic news announcements, or even the weather. 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. © 2011 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Jon Faust & Jonathan H. Wright, 2011. "Efficient Prediction of Excess Returns," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 647-659, May.
  • Handle: RePEc:tpr:restat:v:93:y:2011:i:2:p:647-659
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    Cited by:

    1. Coen N. Teulings & Nikolay Zubanov, 2014. "Is Economic Recovery A Myth? Robust Estimation Of Impulse Responses," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 497-514, April.
    2. Wachter, Jessica A. & Warusawitharana, Missaka, 2015. "What is the chance that the equity premium varies over time? Evidence from regressions on the dividend-price ratio," Journal of Econometrics, Elsevier, vol. 186(1), pages 74-93.
    3. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, Elsevier.
    4. Yan Carriere-Swallow & Bertrand Gruss & Nicolas E Magud & Fabian Valencia, 2016. "Monetary Policy Credibility and Exchange Rate Pass-Through," IMF Working Papers 16/240, International Monetary Fund.

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