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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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Cited by:
  1. repec:ipg:wpaper:28 is not listed on IDEAS
  2. Pakos, Michal, 2013. "Long-Run Risk and Hidden Growth Persistence," MPRA Paper 47217, University Library of Munich, Germany.
  3. Marc Joëts, 2013. "Energy price transmissions during extreme movements," Working Papers 2013-028, Department of Research, Ipag Business School.
  4. 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.
  5. Mordecai Kurz & Maurizio Motolese, 2007. "Diverse Beliefs and Time Variability of Risk Premia," Discussion Papers, Stanford Institute for Economic Policy Research 06-044, Stanford Institute for Economic Policy Research.
  6. 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.
  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. Baetje, Fabian & Menkhoff, Lukas, 2013. "Macro determinants of U.S. stock market risk premia in bull and bear markets," Hannover Economic Papers (HEP) dp-520, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  9. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
  10. Nuno Silva, 2013. "Equity Premia Predictability in the EuroZone," GEMF Working Papers 2013-22, GEMF - Faculdade de Economia, Universidade de Coimbra.
  11. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  12. 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.
  13. M. Barari & Brian Lucey & S. Voronkova, 2008. "Reassessing co-movements among G7 equity markets: evidence from iShares," Applied Financial Economics, Taylor & Francis Journals, vol. 18(11), pages 863-877.
  14. 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.
  15. Fong, Wai Mun, 2012. "Do expected business conditions explain the value premium?," Journal of Financial Markets, Elsevier, Elsevier, vol. 15(2), pages 181-206.

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