The University of Southampton
University of Southampton Institutional Repository

Predicting the equity premium with dividend ratios: reconciling the evidence. [Lead article]

Record type: Article

This paper evaluates the ability of dividend ratios to predict the equity premium. We conduct an in and out-of-sample comparative study and apply the Goyal and Welch (2003) graphical method to equity premia derived from the UK FTSE All-Share and the S&P 500 indices. Preliminary in-sample univariate regressions reveal that in both markets the equity premium contains an element of predictability. However, the considered out-of-sample models outperform the historical moving average only in the UK context. This is confirmed by the graphical diagnostic which further indicates that dividend ratios are useful predictors of UK excess returns. Our paper provides a possible explanation of why dividend ratios might be more informative in the UK market by linking these findings to the disappearing dividend phenomenon. Finally, Campbell and Shiller (1988) identities are employed to account for the time-varying properties of the dividend ratio and dividend growth processes. It is shown that by instrumenting the models with the identities, forecasting ability can be further improved.

PDF Kellard_et_al_2010_JEF_corrected_proof.pdf - Version of Record
Restricted to Repository staff only
Download (564kB)

Citation

Kellard, Neil M., Nankervis, John C. and Papadimitriou, Fotios I. (2010) Predicting the equity premium with dividend ratios: reconciling the evidence. [Lead article] Journal of Empirical Finance, 17, (4), pp. 539-551. (doi:10.1016/j.jempfin.2010.04.002).

More information

e-pub ahead of print date: 11 April 2010
Published date: September 2010
Keywords: equity premium, stock return predictability, dividend ratios, out-of-sample prediction

Identifiers

Local EPrints ID: 154593
URI: http://eprints.soton.ac.uk/id/eprint/154593
ISSN: 0927-5398
PURE UUID: 165affb2-d02b-4bbc-83b9-b80a68a91685

Catalogue record

Date deposited: 25 May 2010 14:57
Last modified: 18 Jul 2017 12:46

Export record

Altmetrics

Contributors

Author: Neil M. Kellard
Author: John C. Nankervis

University divisions


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×