A New Test for Multiple Predictive Regression

Abstract We consider inference for predictive regressions with multiple predictors. Extant tests for predictability (especially for joint predictability) may perform unsatisfactorily and tend to discover spurious predictability as the number of predictors increases. We propose a battery of new instr...

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Bibliographic Details
Published in:Journal of financial econometrics 2024, Vol.22 (1), p.119-156
Main Authors: Xu, Ke-Li, Guo, Junjie
Format: Article
Language:English
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Summary:Abstract We consider inference for predictive regressions with multiple predictors. Extant tests for predictability (especially for joint predictability) may perform unsatisfactorily and tend to discover spurious predictability as the number of predictors increases. We propose a battery of new instrumental variables-based tests which involve enforcement or partial enforcement of the null hypothesis in variance estimation. A test based on the few-predictors-at-a-time parsimonious system approach is recommended. Empirical Monte Carlos demonstrates the remarkable finite-sample performance regardless of numerosity of predictors and their persistence properties. Empirical application to equity premium predictability is provided.
ISSN:1479-8409
1479-8417
DOI:10.1093/jjfinec/nbac030