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The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests

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journal contribution
posted on 09.10.2018, 15:07 by Rangan Gupta, Christian Pierdzioch, Andrew Vivian, Mark Wohar
We contribute to research on the predictability of stock returns in two ways. First, we use quantile random forests to study the predictive value of various consumption-based and income-based inequality measures across the quantiles of the conditional distribution of stock returns. Second, we examine whether the inequality measures, measured at a quarterly frequency, have out-of-sample predictive value for stock returns at three different forecast horizons. Our results suggest that the inequality measures have predictive value for stock returns in sample, but do not systematically predict stock returns out of sample.

Funding

We thank the German Science Foundation for financial support (Project Macroeconomic Forecasting in Great Crises; Grant number: FR 2677/4-1).

History

School

  • Business and Economics

Department

  • Business

Published in

Finance Research Letters

Citation

GUPTA, R. ... et al, 2018. The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests. Finance Research Letters, 29, pp.315-322.

Publisher

© Elsevier

Version

AM (Accepted Manuscript)

Publisher statement

This paper was accepted for publication in the journal Finance Research Letters and the definitive published version is available at https://doi.org/10.1016/j.frl.2018.08.013.

Acceptance date

14/08/2018

Publication date

2018-08-21

ISSN

1544-6123

Language

en

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