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 Vivian (a.j.vivian@lboro.ac.uk) and Mark Wohar (mwohar@unomaha.edu)
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Andrew Vivian: School of Business and Economics, Loughborough University, Leicestershire, UK

No 201809, Working Papers from University of Pretoria, Department of Economics

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 the various inequality measures across the quantiles of the conditional distribution of stock returns. Second, we examine whether various measures of consumption-based and income-based inequality, measured at a quarterly frequency, have out-of-sample predictive value for stock returns at various forecast horizons. Our results suggest that the inequality measures being studied 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)
Pages: 18 pages
Date: 2018-02
New Economics Papers: this item is included in nep-big, nep-for and nep-ltv
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Citations: View citations in EconPapers (5)

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Journal Article: The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests (2019)
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