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What is the chance that the equity premium varies over time? evidence from predictive regressions

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  • Missaka Warusawitharana
  • Jessica A. Wachter

Abstract

We examine the evidence on excess stock return predictability in a Bayesian setting in which the investor faces uncertainty about both the existence and strength of predictability. Departing from previous studies, we allow the regressor to be stochastic. When we apply our methods to the dividend-price ratio and payout yield, we find that even investors who are quite skeptical about the existence of predictability sharply modify their views in favor of predictability when confronted by the historical time series of returns and predictor variables. We find that taking into account the stochastic properties of the regressor has a substantial impact on the investor's inference about returns.

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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2009-26.

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Date of creation: 2009
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Handle: RePEc:fip:fedgfe:2009-26

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  1. Brennan, Michael J. & Schwartz, Eduardo S. & Lagnado, Ronald, 1997. "Strategic asset allocation," Journal of Economic Dynamics and Control, Elsevier, vol. 21(8-9), pages 1377-1403, June.
  2. John Y. Campbell & Motohiro Yogo, 2003. "Efficient Tests of Stock Return Predictability," NBER Working Papers 10026, National Bureau of Economic Research, Inc.
  3. John Y. Campbell & Luis M. Viceira, 1996. "Consumption and Portfolio Decisions When Expected Returns are Time Varying," NBER Working Papers 5857, National Bureau of Economic Research, Inc.
  4. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, 02.
  5. Zengjing Chen & Larry Epstein, 2002. "Ambiguity, Risk, and Asset Returns in Continuous Time," Econometrica, Econometric Society, vol. 70(4), pages 1403-1443, July.
  6. Klaas P. Baks, 2001. "Should Investors Avoid All Actively Managed Mutual Funds? A Study in Bayesian Performance Evaluation," Journal of Finance, American Finance Association, vol. 56(1), pages 45-85, 02.
  7. Avramov, Doron, 2002. "Stock return predictability and model uncertainty," Journal of Financial Economics, Elsevier, vol. 64(3), pages 423-458, June.
  8. Jacob Boudoukh & Roni Michaely & Matthew Richardson & Michael Roberts, 2004. "On the Importance of Measuring Payout Yield: Implications for Empirical Asset Pricing," NBER Working Papers 10651, National Bureau of Economic Research, Inc.
  9. Hui Chen & Nengjiu Ju & Jianjun Miao, . "Dynamic Asset Allocation with Ambiguous Return Predictability," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics.
  10. Michael W. Brandt & Amit Goyal & Pedro Santa-Clara & Jonathan Storud, 2004. "A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability," NBER Working Papers 10934, National Bureau of Economic Research, Inc.
  11. Cavanagh, Christopher L. & Elliott, Graham & Stock, James H., 1995. "Inference in Models with Nearly Integrated Regressors," Econometric Theory, Cambridge University Press, vol. 11(05), pages 1131-1147, October.
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Cited by:
  1. Jessica A. Wachter, 2010. "Asset Allocation," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 175-206, December.
  2. Missaka Warusawitharana, 2011. "The expected real return to equity," Finance and Economics Discussion Series 2011-14, Board of Governors of the Federal Reserve System (U.S.).

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