Wealth-to-Income Ratio and Stock Market Movements: Evidence from a Nonparametric Causality Test
Mehmet Balcilar,
Rangan Gupta,
Ricardo Sousa and
Mark Wohar ()
No 201731, Working Papers from University of Pretoria, Department of Economics
Abstract:
We use a nonparametric causality-in-quantiles test to analyze the predictive ability of the wealth-to-income ratio (wy) for excess stock returns and their volatility. Our results reveal that the wealth-to-income ratio is nonlinearly related with excess stock returns, and hence, results from linear Granger causality tests cannot be deemed robust. When we apply the nonparametric causality-in-quantiles test, we find that the wealth-to-income ratio can predict excess stock returns over the majority of the conditional distribution, with the exception being the extreme ends, i.e. when the market is in deep bear or bull phases. However, the wealth-to-income ratio has no predictability for the volatility of excess stock returns.
Keywords: stock returns; volatility; nonparametric causality-in-quantiles test (search for similar items in EconPapers)
JEL-codes: C22 G10 (search for similar items in EconPapers)
Pages: 15 pages
Date: 2017-05
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Citations: View citations in EconPapers (2)
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Journal Article: Wealth‐to‐Income Ratio and Stock Market Movements: Evidence from a Nonparametric Causality Test (2018) 
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