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Stock Returns and Expected Business Conditions: Half a Century of Direct Evidence

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  • Sean D. Campbell

    ()
    (Risk Analysis Section, Division of Research and Statistics, Federal Reserve Board)

  • Francis X. Diebold

    ()
    (Department of Economics, University of Pennsylvania)

Abstract

We explore the macro/finance interface in the context of equity markets. In particular, using half a century of Livingston expected business conditions data we characterize directly the impact of expected business conditions on expected excess stock returns. Expected business conditions consistently affect expected excess returns in a statistically and economically significant counter-cyclical fashion: depressed expected business conditions are associated with high expected excess returns. Moreover, inclusion of expected business conditions in otherwise standard predictive return regressions substantially reduces the explanatory power of the conventional financial predictors, including the dividend yield, default premium, and term premium, while simultaneously increasing. Expected business conditions retain predictive power even after controlling for an important and recently introduced non-financial predictor, the generalized consumption/wealth ratio, which accords with the view that expected business conditions play a role in asset pricing different from and complementary to that of the consumption/wealth ratio. We argue that time-varying expected business conditions likely capture time-varying risk, while time-varying consumption/wealth may capture time-varying risk aversion.

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Bibliographic Info

Paper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 05-025.

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Length: 28 pages
Date of creation: 01 May 2005
Date of revision: 16 Sep 2005
Handle: RePEc:pen:papers:05-025

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Keywords: Business cycle; expected equity returns; prediction; Livingston survey; risk aversion; equity premium; risk premium;

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References

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Citations

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Cited by:
  1. Nuno Silva, 2013. "Equity Premia Predictability in the EuroZone," GEMF Working Papers 2013-22, GEMF - Faculdade de Economia, Universidade de Coimbra.
  2. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, School of Economics and Management, University of Aarhus.
  3. Marc Joëts, 2013. "Energy price transmissions during extreme movements," Working Papers, Department of Research, Ipag Business School 2013-028, Department of Research, Ipag Business School.
  4. Pakos, Michal, 2013. "Long-Run Risk and Hidden Growth Persistence," MPRA Paper 47217, University Library of Munich, Germany.
  5. Paye, Bradley S., 2012. "‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables," Journal of Financial Economics, Elsevier, Elsevier, vol. 106(3), pages 527-546.
  6. van den Hauwe, Sjoerd & Paap, Richard & van Dijk, Dick, 2013. "Bayesian forecasting of federal funds target rate decisions," Journal of Macroeconomics, Elsevier, Elsevier, vol. 37(C), pages 19-40.
  7. Sjoerd van den Hauwe & Dick van Dijk & Richard Paap, 2011. "Bayesian Forecasting of Federal Funds Target Rate Decisions," Tinbergen Institute Discussion Papers 11-093/4, Tinbergen Institute.
  8. Fong, Wai Mun, 2012. "Do expected business conditions explain the value premium?," Journal of Financial Markets, Elsevier, Elsevier, vol. 15(2), pages 181-206.
  9. Cem Cakmakli & Dick van Dijk, 2010. "Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility," Tinbergen Institute Discussion Papers 10-115/4, Tinbergen Institute.
  10. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
  11. repec:ipg:wpaper:28 is not listed on IDEAS
  12. Mordecai Kurz & Maurizio Motolese, 2011. "Diverse beliefs and time variability of risk premia," Economic Theory, Springer, Springer, vol. 47(2), pages 293-335, June.
  13. Baetje, Fabian & Menkhoff, Lukas, 2013. "Macro determinants of U.S. stock market risk premia in bull and bear markets," Hannover Economic Papers (HEP), Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät dp-520, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  14. M. Barari & Brian Lucey & S. Voronkova, 2008. "Reassessing co-movements among G7 equity markets: evidence from iShares," Applied Financial Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 18(11), pages 863-877.
  15. Safari, Meysam & TahmooresPour, Reza, 2011. "Moderation Effect of Market Condition on the Relationship between Dividend Yield and Stock Return," MPRA Paper 28913, University Library of Munich, Germany.

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