Regime specific predictability in predictive regressions
Regime specific predictability in predictive regressions
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.
229-241
Pitarakis, Jean-Yves
ee5519ae-9c0f-4d79-8a3a-c25db105bd51
Gonzalo, Jesus
57637a0a-f7da-417f-9d2e-3a33a7082504
April 2012
Pitarakis, Jean-Yves
ee5519ae-9c0f-4d79-8a3a-c25db105bd51
Gonzalo, Jesus
57637a0a-f7da-417f-9d2e-3a33a7082504
Pitarakis, Jean-Yves and Gonzalo, Jesus
(2012)
Regime specific predictability in predictive regressions.
Journal of Business and Economic Statistics, 30 (2), .
(doi:10.1080/07350015.2011.652053).
Abstract
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.
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Published date: April 2012
Organisations:
Economics
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Local EPrints ID: 300508
URI: http://eprints.soton.ac.uk/id/eprint/300508
ISSN: 0735-0015
PURE UUID: 686139c2-cdc2-4f4d-98c4-d584bdd0c8e7
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Date deposited: 22 Feb 2012 12:24
Last modified: 15 Mar 2024 03:16
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Author:
Jesus Gonzalo
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