# Predicting stock returns and volatility using consumption-aggregate wealth ratios: A nonlinear approach

*Stelios Bekiros* and
*Rangan Gupta* ()

*Economics Letters*, 2015, vol. 131, issue C, 83-85

**Abstract:**
Recent empirical evidence based on a linear framework tends to suggest that a Markov-switching version of the consumption-aggregate wealth ratio (cayMS), developed to account for structural breaks, is a better predictor of stock returns than the conventional measure (cay)—a finding we confirm as well. Using quarterly data over 1952:Q1–2013:Q3, we however provide statistical evidence that the relationship between stock returns and cay or cayMS is in fact nonlinear. Then, given this evidence of nonlinearity, using a nonparametric Granger causality test, we show that it is in fact cay and not cayMS which is a stronger predictor of not only stock returns, but also volatility.

**Keywords:** Cay; Stock markets; Volatility; Nonlinear causality (search for similar items in EconPapers)

**JEL-codes:** C32 C58 G10 G17 (search for similar items in EconPapers)

**Date:** 2015

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Working Paper: Predicting Stock Returns and Volatility Using Consumption-Aggregate Wealth Ratios: A Nonlinear Approach (2015)

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**Persistent link:** https://EconPapers.repec.org/RePEc:eee:ecolet:v:131:y:2015:i:c:p:83-85

**DOI:** 10.1016/j.econlet.2015.03.019

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