The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests
Rangan Gupta,
Christian Pierdzioch,
Andrew J. Vivian and
Mark Wohar ()
Finance Research Letters, 2019, vol. 29, issue C, 315-322
Abstract:
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.
Keywords: Stock returns; Predictability; Inequality measures; Quantile random forests (search for similar items in EconPapers)
JEL-codes: C53 G17 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612318300928
Full text for ScienceDirect subscribers only
Related works:
Working Paper: The Predictive Value of Inequality Measures for Stock Returns: An Analysis of Long-Span UK Data Using Quantile Random Forests (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:29:y:2019:i:c:p:315-322
DOI: 10.1016/j.frl.2018.08.013
Access Statistics for this article
Finance Research Letters is currently edited by R. Gençay
More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().