Predicting stock returns and volatility using consumption-aggregate wealth ratios : a nonlinear approach
Title: Predicting stock returns and volatility using consumption-aggregate wealth ratios : a nonlinear approach
Citation: Economics letters, 2015, Vol. 131, pp. 83-85
ISSN: 0165-1765; 1873-7374
Recent empirical evidence based on a linear framework tends to suggest that a Markov-switching version of the consumption-aggregate wealth ratio (View the MathML source), 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 View the MathML source 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 View the MathML source which is a stronger predictor of not only stock returns, but also volatility.
Subject: Cay; Stock markets; Volatility; Nonlinear causality; C32; C58; G10; G17
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