The University of Southampton
University of Southampton Institutional Repository

Regime specific predictability in predictive regressions

Record type: Article

Predictive regressions are linear specifications linking a noisy variable such as stock returns to past values of a very persistent regressor with the aim of assessing the presence of predictability. Key complications that arise are the potential presence of endogeneity and the poor adequacy of asymptotic approximations. In this paper we develop tests for uncovering the presence of predictability in such models when the strength or direction of predictability may alternate across different economically meaningful episodes. An empirical application reconsiders the Dividend Yield based return predictability and documents a strong predictability that is countercyclical, occurring solely during bad economic times.

Full text not available from this repository.

Citation

Pitarakis, Jean-Yves and Gonzalo, Jesus (2012) Regime specific predictability in predictive regressions Journal of Business and Economic Statistics, 30, (2), pp. 229-241. (doi:10.1080/07350015.2011.652053).

More information

Published date: April 2012
Organisations: Economics

Identifiers

Local EPrints ID: 300508
URI: http://eprints.soton.ac.uk/id/eprint/300508
ISSN: 0735-0015
PURE UUID: 686139c2-cdc2-4f4d-98c4-d584bdd0c8e7

Catalogue record

Date deposited: 22 Feb 2012 12:24
Last modified: 18 Jul 2017 06:14

Export record

Altmetrics

Contributors

Author: Jean-Yves Pitarakis
Author: Jesus Gonzalo

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.

×