May 1997

Earnings Forecasts and the Predictability of Stock Returns: Evidence from Trading the S&P

Joel Lander, Athanasios Orphanides, and Martha Douvogiannis


We develop a simple error-correction model, based on a well-known theory, espoused by Benjamin Graham and David Dodd and others, which presumes stock returns tend to restore an equilibrium relationship between the forecasted earnings yield on common stocks and the yield on bonds. The estimation uses I/B/E/S analysts forecasts of S&P earnings. To evaluate the model, we use rolling regressions to obtain out-of-sample forecasts of excess returns. Tests of association show the implicit timing signals to be statistically significant. Further, a strategy of investing in cash, when the excess return forecast is negative, and investing in the S&P, when the excess return forecast is positive, outperforms the S&P with higher returns and smaller volatility. Using the bootstrap methodology, we demonstrate that the findings are statistically significant.

Full paper (436 KB Postscript)

Keywords: Asset allocation, earnings yield, analyst earnings forecasts, I/B/E/S, S&P 500, market timing, regression models

PDF: Full Paper

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