Abstract: 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.
Keywords: Asset allocation, earnings yield, analyst earnings forecasts, I/B/E/S, S&P 500, market timing, regression models.
Full paper (421 KB PDF)
| Full paper (436 KB Postscript)
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