Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement

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ID: 294899
1992
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Abstract
Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the Hansen and Hodrick (1980) procedure is biased at long horizons, but the alternatives perform better. These include an estimator derived under the null hypothesis as in Richardson and Smith (1991), a reformulation of the regression as in Jegadeesh (1990), and a vector autoregression (VAR) as in Campbell and Shiller (1988), Kandel and Stambaugh (1988), and Campbell (1991). The statistical properties of long-horizon statistics generated from the VAR indicate interesting patterns in expected stock returns.
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openalex_W3124485385 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Robert J. Hodrick
Journal review of financial studies
Year 1992
DOI
10.1093/rfs/5.3.351
URL
https://doi.org/10.1093/rfs/5.3.351
Keywords Keywords not found

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