manuscript.revised.pdf (445.59 kB)
The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests
journal contribution
posted on 2018-10-09, 15:07 authored by Rangan Gupta, Christian Pierdzioch, Andrew VivianAndrew Vivian, Mark WoharWe 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 LettersCitation
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
© ElsevierVersion
- 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
2018-08-14Publication date
2018-08-21ISSN
1544-6123Publisher version
Language
- en