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Economic Cycles and Expected Stock Returns

  • Beber, Alessandro
  • Brandt, Michael
  • Luisi, Maurizio

We construct daily real-time indices capturing the public information on realized and anticipated economic activity. The one-month change in realized fundamentals predicts US stock returns across horizons with strongest results between a month and a quarter. The information in anticipated fundamentals that is orthogonal to the realized data predicts returns even more strongly particularly at longer horizons up to two quarters. Splitting the sample into times of high versus low uncertainty, as measured by the cross-sectional dispersion of economist forecasts, we show that the predictability is largely concentrated in high-uncertainty times. Finally, extending the analysis internationally, we find similar results that are curiously much stronger when US data are used as predictors than global composites or local data.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 9528.

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Date of creation: Jun 2013
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Handle: RePEc:cpr:ceprdp:9528
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  1. Tim Bollerslev & Tzuo Hao & George Tauchen, 2008. "Expected Stock Returns and Variance Risk Premia," CREATES Research Papers 2008-48, Department of Economics and Business Economics, Aarhus University.
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  7. John Y. Campbell & Robert J. Shiller, 1988. "Stock Prices, Earnings and Expected Dividends," Cowles Foundation Discussion Papers 858, Cowles Foundation for Research in Economics, Yale University.
  8. Bollerslev, Tim & Marrone, James & Xu, Lai & Zhou, Hao, 2014. "Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(03), pages 633-661, June.
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  12. G. William Schwert, 1988. "Why Does Stock Market Volatility Change Over Time?," NBER Working Papers 2798, National Bureau of Economic Research, Inc.
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  14. Yacine Ait-Sahalia & Per A. Mykland, 2003. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," NBER Working Papers 9611, National Bureau of Economic Research, Inc.
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