A Forecast Evaluation of Expected Equity Return Measures
42 Pages Posted: 17 Jan 2015 Last revised: 21 Jan 2015
Date Written: January 16, 2015
Recent studies find evidence in favour of return predictability, and argue that their positive findings result from their ability to capture expected returns. We assess the forecasting performance of two popular approaches to estimating expected equity returns, a dividend discount model (DDM) commonly used to estimate 'implied cost of capital', and a vector autoregression (VAR) model commonly used to decompose equity returns. In line with recent evidence, in-sample tests show that both estimates generate substantially lower forecast errors compared to traditional predictor variables such as price-earnings ratios and dividend yields. Out-of-sample, the VAR and DDM estimates generate economically and statistically significant forecast improvements relative to a historical average benchmark. Our results tentatively suggest that the VAR approach better captures expected returns compared to the DDM.
Keywords: Expected returns, implied cost of capital, dividend discount model, return predictability, forecasting
JEL Classification: G10, G11, G12, G17
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