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A Comprehensive Look at the Empirical Performance of Equity Premium Prediction

  • Amit Goval
  • Ivo Welch

Given the historically high equity premium, is it now a good time to invest in the stock market? Economists have suggested a whole range of variables that investors could or should use to predict: dividend price ratios, dividend yields, earnings-price ratios, dividend payout ratios, net issuing ratios, book-market ratios, interest rates (in various guises), and consumption-based macroeconomic ratios (cay). The typical paper reports that the variable predicted well in an *in-sample* regression, implying forecasting ability. Our paper explores the *out-of-sample* performance of these variables, and finds that not a single one would have helped a real-world investor outpredicting the then-prevailing historical equity premium mean. Most would have outright hurt. Therefore, we find that, for all practical purposes, the equity premium has not been predictable, and any belief about whether the stock market is now too high or too low has to be based on theoretical prior, not on the empirically variables we have explored.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 10483.

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Date of creation: May 2004
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Publication status: published as Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
Handle: RePEc:nbr:nberwo:10483
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  1. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
  2. Nelson, Charles R & Kim, Myung J, 1993. " Predictable Stock Returns: The Role of Small Sample Bias," Journal of Finance, American Finance Association, vol. 48(2), pages 641-61, June.
  3. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  4. Malcolm Baker & Jeffrey Wurgler, 2000. "The Equity Share in New Issues and Aggregate Stock Returns," Journal of Finance, American Finance Association, vol. 55(5), pages 2219-2257, October.
  5. Goetzmann, William Nelson & Jorion, Philippe, 1993. " Testing the Predictive Power of Dividend Yields," Journal of Finance, American Finance Association, vol. 48(2), pages 663-79, June.
  6. Campbell, John & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Scholarly Articles 3122601, Harvard University Department of Economics.
  7. Andrew Ang & Geert Bekaert, 2001. "Stock Return Predictability: Is it There?," NBER Working Papers 8207, National Bureau of Economic Research, Inc.
  8. Cochrane, John H, 1991. " Production-Based Asset Pricing and the Link between Stock Returns and Economic Fluctuations," Journal of Finance, American Finance Association, vol. 46(1), pages 209-37, March.
  9. Campbell, John Y. & Viceira, Luis M., 2002. "Strategic Asset Allocation: Portfolio Choice for Long-Term Investors," OUP Catalogue, Oxford University Press, number 9780198296942, March.
  10. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
  11. Fama, Eugene F. & Schwert, G. William, 1977. "Asset returns and inflation," Journal of Financial Economics, Elsevier, vol. 5(2), pages 115-146, November.
  12. Bossaerts, Peter & Hillion, Pierre, 1999. "Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?," Review of Financial Studies, Society for Financial Studies, vol. 12(2), pages 405-28.
  13. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-86.
  14. Amit Goyal & Ivo Welch, 1999. "Predicting the Equity Premium with Dividend Ratios," Yale School of Management Working Papers amz2437, Yale School of Management, revised 01 Nov 2002.
  15. Kothari, S. P. & Shanken, Jay, 1997. "Book-to-market, dividend yield, and expected market returns: A time-series analysis," Journal of Financial Economics, Elsevier, vol. 44(2), pages 169-203, May.
  16. Kilian, Lutz, 1999. "Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 491-510, Sept.-Oct.
  17. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
  18. Hui Guo, 2003. "On the out-of-sample predictability of stock market returns," Working Papers 2002-008, Federal Reserve Bank of St. Louis.
  19. Malcolm P. Baker & Ryan Taliaferro & Jeffrey Wurgler, 2004. "Pseudo Market Timing and Predictive Regressions," NBER Working Papers 10823, National Bureau of Economic Research, Inc.
  20. Lettau, Martin & Ludvigson, Sydney, 1999. "Consumption, Aggregate Wealth and Expected Stock Returns," CEPR Discussion Papers 2223, C.E.P.R. Discussion Papers.
  21. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-18, March.
  22. Alexander W. Butler & Gustavo Grullon & James P. Weston, 2005. "Can Managers Forecast Aggregate Market Returns?," Journal of Finance, American Finance Association, vol. 60(2), pages 963-986, 04.
  23. Lintner, John, 1975. "Inflation and Security Returns," Journal of Finance, American Finance Association, vol. 30(2), pages 259-80, May.
  24. John H. Cochrane, 1998. "Where is the Market Going? Uncertain Facts and Novel Theories," NBER Working Papers 6207, National Bureau of Economic Research, Inc.
  25. Campbell, John Y & Shiller, Robert J, 1988. " Stock Prices, Earnings, and Expected Dividends," Journal of Finance, American Finance Association, vol. 43(3), pages 661-76, July.
  26. Owen Lamont, 1996. "Earnings and Expected Returns," NBER Working Papers 5671, National Bureau of Economic Research, Inc.
  27. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
  28. Valkanov, Rossen, 2003. "Long-horizon regressions: theoretical results and applications," Journal of Financial Economics, Elsevier, vol. 68(2), pages 201-232, May.
  29. Avramov, Doron, 2002. "Stock return predictability and model uncertainty," Journal of Financial Economics, Elsevier, vol. 64(3), pages 423-458, June.
  30. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  31. Fama, Eugene F, 1981. "Stock Returns, Real Activity, Inflation, and Money," American Economic Review, American Economic Association, vol. 71(4), pages 545-65, September.
  32. Donald B. Keim & Robert F. Stambaugh, . "Predicting Returns in the Stock and Bond Markets," Rodney L. White Center for Financial Research Working Papers 15-85, Wharton School Rodney L. White Center for Financial Research.
  33. Torous, Walter & Valkanov, Rossen, 2000. "Boundaries of Predictability: Noisy Predictive Regressions," University of California at Los Angeles, Anderson Graduate School of Management qt33p7672z, Anderson Graduate School of Management, UCLA.
  34. Keim, Donald B. & Madhavan, Ananth, 1997. "Transactions costs and investment style: an inter-exchange analysis of institutional equity trades," Journal of Financial Economics, Elsevier, vol. 46(3), pages 265-292, December.
  35. John Y. Campbell & Samuel B. Thompson, 2005. "Predicting the Equity Premium Out of Sample: Can Anything Beat the Historical Average?," NBER Working Papers 11468, National Bureau of Economic Research, Inc.
  36. Pontiff, Jeffrey & Schall, Lawrence D., 1998. "Book-to-market ratios as predictors of market returns," Journal of Financial Economics, Elsevier, vol. 49(2), pages 141-160, August.
  37. Lior Menzly & Tano Santos & Pietro Veronesi, 2004. "Understanding Predictability," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 1-47, February.
  38. Robert J. Shiller, 1984. "Stock Prices and Social Dynamics," Cowles Foundation Discussion Papers 719R, Cowles Foundation for Research in Economics, Yale University.
  39. Polk, Christopher & Thompson, Samuel & Vuolteenaho, Tuomo, 2006. "Cross-sectional forecasts of the equity premium," Journal of Financial Economics, Elsevier, vol. 81(1), pages 101-141, July.
  40. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
  41. Breen, William & Glosten, Lawrence R & Jagannathan, Ravi, 1989. " Economic Significance of Predictable Variations in Stock Index Returns," Journal of Finance, American Finance Association, vol. 44(5), pages 1177-89, December.
  42. Wayne E. Ferson & Sergei Sarkissian & Timothy Simin, 2002. "Spurious Regressions in Financial Economics?," NBER Working Papers 9143, National Bureau of Economic Research, Inc.
  43. K. J. Martijn Cremers, 2002. "Stock Return Predictability: A Bayesian Model Selection Perspective," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1223-1249.
  44. Jonathan Lewellen & Jay Shanken, 2002. "Learning, Asset-Pricing Tests, and Market Efficiency," Journal of Finance, American Finance Association, vol. 57(3), pages 1113-1145, 06.
  45. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
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