Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole
We propose forecasting separately the three components of stock market returns: dividend yield, earnings growth, and price-earnings ratio growth. We obtain out-of-sample R-square coefficients (relative to the historical mean) of nearly 1.6% with monthly data and 16.7% with yearly data using the most common predictors suggested in the literature. This compares with typically negative R-squares obtained in a similar experiment by Goyal and Welch (2008). An investor who timed the market with our approach would have had a certainty equivalent gain of as much as 2.3% per year and a Sharpe ratio 77% higher relative to the historical mean. We conclude that there is substantial predictability in equity returns and that it would have been possible to time the market in real time.
-
-
Copy CitationMiguel A. Ferreira and Pedro Santa-Clara, "Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole," NBER Working Paper 14571 (2008), https://doi.org/10.3386/w14571.Download Citation
Published Versions
Journal of Financial Economics Volume 100, Issue 3, June 2011, Pages 514–537 Cover image Forecasting stock market returns: The sum of the parts is more than the whole ☆ Miguel A. Ferreiraa, b, Pedro Santa-Claraa, c, Corresponding author contact information, E-mail the corresponding author citation courtesy of ![]()