Inferring the predictability induced by a persistent regressor in a predictive threshold model
Inferring the predictability induced by a persistent regressor in a predictive threshold model
We develop tests for detecting possibly episodic predictability induced by a persistent predictor. Our framework is that of a predictive regression model with threshold effects and our goal is to develop operational and easily implementable inferences when one does not wish to impose à priori restrictions on the parameters of the model other than the slopes corresponding to the persistent predictor. Differently put our tests for the null hypothesis of no predictability against threshold predictability remain valid without the need to know whether the remaining parameters of the model are characterised by threshold effects or not (e.g. shifting versus non-shifting intercepts). One interesting feature of our setting is that our test statistics remain unaffected by whether some nuisance parameters are identified or not. We subsequently apply our methodology to the predictability of aggregate stock returns with valuation ratios and document a robust countercyclicality in the ability of some valuation ratios to predict returns in addition to highlighting a strong sensitivity of predictability based results to the time period under consideration.
predictive regressions, threshold effects, predictability of stock returns
202-217
Gonzalo, Jesùs
0ec956ab-f13e-4466-bff4-4b2923290ae5
Pitarakis, Jean-Yves
ee5519ae-9c0f-4d79-8a3a-c25db105bd51
13 March 2017
Gonzalo, Jesùs
0ec956ab-f13e-4466-bff4-4b2923290ae5
Pitarakis, Jean-Yves
ee5519ae-9c0f-4d79-8a3a-c25db105bd51
Gonzalo, Jesùs and Pitarakis, Jean-Yves
(2017)
Inferring the predictability induced by a persistent regressor in a predictive threshold model.
Journal of Business and Economic Statistics, 35 (2), .
(doi:10.1080/07350015.2016.1164054).
Abstract
We develop tests for detecting possibly episodic predictability induced by a persistent predictor. Our framework is that of a predictive regression model with threshold effects and our goal is to develop operational and easily implementable inferences when one does not wish to impose à priori restrictions on the parameters of the model other than the slopes corresponding to the persistent predictor. Differently put our tests for the null hypothesis of no predictability against threshold predictability remain valid without the need to know whether the remaining parameters of the model are characterised by threshold effects or not (e.g. shifting versus non-shifting intercepts). One interesting feature of our setting is that our test statistics remain unaffected by whether some nuisance parameters are identified or not. We subsequently apply our methodology to the predictability of aggregate stock returns with valuation ratios and document a robust countercyclicality in the ability of some valuation ratios to predict returns in addition to highlighting a strong sensitivity of predictability based results to the time period under consideration.
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Inferring the Predictability Induced by a Persistent Regressor in a Predictive Threshold Model.pdf
- Accepted Manuscript
More information
Accepted/In Press date: 28 February 2016
e-pub ahead of print date: 13 March 2017
Published date: 13 March 2017
Keywords:
predictive regressions, threshold effects, predictability of stock returns
Organisations:
Economics
Identifiers
Local EPrints ID: 390672
URI: http://eprints.soton.ac.uk/id/eprint/390672
ISSN: 0735-0015
PURE UUID: c9678560-de11-4ac6-898a-891bb11ab96e
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Date deposited: 04 Apr 2016 16:10
Last modified: 15 Mar 2024 05:27
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Author:
Jesùs Gonzalo
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