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The Equity Premium and the Business Cycle: the Role of Demand and Supply Shocks

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  • Wickens, Michael R.
  • Smith, Peter N
  • Sorensen, Steffen

Abstract

This paper explores the effects of the US business cycle on US stock market returns through an analysis of the equity risk premium. We propose a new methodology based on the SDF approach to asset pricing that allows us to uncover the different effects of aggregate demand and supply shocks. We find that negative shocks are more important that positive shocks, and that supply shocks have a much greater impact than demand shocks.

Suggested Citation

  • Wickens, Michael R. & Smith, Peter N & Sorensen, Steffen, 2009. "The Equity Premium and the Business Cycle: the Role of Demand and Supply Shocks," CEPR Discussion Papers 7227, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:7227
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    1. Paul Harrison & Harold H. Zhang, 1999. "An Investigation Of The Risk And Return Relation At Long Horizons," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 399-408, August.
    2. Peter Smith & Michael Wickens, 2002. "Asset Pricing with Observable Stochastic Discount Factors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 397-446, July.
    3. Chauvet, Marcelle & Potter, Simon, 2001. "Nonlinear Risk," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 621-646, September.
    4. Baillie, Richard T. & DeGennaro, Ramon P., 1990. "Stock Returns and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(2), pages 203-214, June.
    5. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    6. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," The Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    7. Scruggs, John T. & Glabadanidis, Paskalis, 2003. "Risk Premia and the Dynamic Covariance between Stock and Bond Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(2), pages 295-316, June.
    8. repec:bla:jfinan:v:44:y:1989:i:5:p:1115-53 is not listed on IDEAS
    9. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    10. G. William Schwert, 1997. "Stock Market Volatility: Ten Years After the Crash," Center for Financial Institutions Working Papers 97-51, Wharton School Center for Financial Institutions, University of Pennsylvania.
    11. Robertson, Donald & Wickens, M R, 1997. "Measuring Real and Nominal Macroeconomic Shocks and Their International Transmission under Different Monetary Systems," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(1), pages 5-27, February.
    12. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    13. Harvey, Campbell R., 1989. "Time-varying conditional covariances in tests of asset pricing models," Journal of Financial Economics, Elsevier, vol. 24(2), pages 289-317.
    14. Keating, John W., 2000. "Macroeconomic Modeling with Asymmetric Vector Autoregressions," Journal of Macroeconomics, Elsevier, vol. 22(1), pages 1-28, January.
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    Cited by:

    1. Abhakorn, Pongrapeeporn & Smith, Peter N. & Wickens, Michael R., 2016. "Can stochastic discount factor models explain the cross-section of equity returns?," Review of Financial Economics, Elsevier, vol. 28(C), pages 56-68.
    2. Alfonso Mendoza Velázquez & Peter N. Smith, 2013. "Equity Returns and the Business Cycle: the Role of Supply and Demand Shocks," Manchester School, University of Manchester, vol. 81, pages 100-124, September.
    3. Abhakorn, Pongrapeeporn & Smith, Peter N. & Wickens, Michael R., 2016. "Can stochastic discount factor models explain the cross-section of equity returns?," Review of Financial Economics, Elsevier, vol. 28(C), pages 56-68.
    4. Chien-Chiang Lee & Chin-Yu Wang & Jhih-Hong Zeng, 2017. "Housing price–volume correlations and boom–bust cycles," Empirical Economics, Springer, vol. 52(4), pages 1423-1450, June.
    5. John Nkwoma Inekwe, 2020. "Market uncertainty, risk aversion, and macroeconomic expectations," Empirical Economics, Springer, vol. 59(4), pages 1977-1995, October.
    6. Kizys, Renatas & Pierdzioch, Christian, 2010. "The business cycle and the equity risk premium in real time," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 711-722, October.

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    More about this item

    Keywords

    Business cycles; Demand and supply shocks; Equity premium; Stock returns;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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