Dividend Growth Predictability and the Price-Dividend Ratio

Ilaria Piatti and Fabio Trojani ()

No 12-42, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: Conventional tests of present-value models over-reject the null of no predictability. In order to better account for the intrinsic probability of detecting predictive relations by chance alone, we develop a new nonparametric Monte Carlo testing method, which does not rely on distributional assumptions to aggregate the information from the time series of price-dividend ratios and dividend growth. We find evidence of return predictability, but no apparent evidence of dividend growth predictability in postwar US data, thus reconciling the diverging conclusions in the literature. Our findings are robust to the specification of the predictive information set, the choice of the sample period and the use of different cash-flow proxies.

Keywords: Predictability; Predictive regression; Present-value model; State-space model; Bootstrap; Likelihood ratio test (search for similar items in EconPapers)
JEL-codes: C12 C14 C22 G12 (search for similar items in EconPapers)
Pages: 74 pages
Date: 2012-06
New Economics Papers: this item is included in nep-acc and nep-cfn
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Journal Article: Dividend Growth Predictability and the Price–Dividend Ratio (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp1242

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