Working Paper: NBER ID: w14571
Authors: Miguel A. Ferreira; Pedro Santaclara
Abstract: 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.
Keywords: Stock Market Returns; Forecasting; Predictive Regressions; Economic Gains; Investment Strategies
JEL Codes: G1; G17
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| sum-of-the-parts method (C59) | out-of-sample R-squared values (C52) |
| sum-of-the-parts method (C59) | predictive capability (C52) |
| sum-of-the-parts method (C59) | certainty equivalent gain (D50) |
| sum-of-the-parts method (C59) | Sharpe ratio (G11) |
| predictability of returns (G17) | effective market timing strategies (G14) |
| sum-of-the-parts method (C59) | market timing (G14) |