Date: 2015
Type: Article
Predicting stock returns and volatility using consumption-aggregate wealth ratios : a nonlinear approach
Economics letters, 2015, Vol. 131, pp. 83-85
BEKIROS, Stelios D., GUPTA, Rangan, Predicting stock returns and volatility using consumption-aggregate wealth ratios : a nonlinear approach, Economics letters, 2015, Vol. 131, pp. 83-85
- https://hdl.handle.net/1814/38370
Retrieved from Cadmus, EUI Research Repository
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.
Cadmus permanent link: https://hdl.handle.net/1814/38370
Full-text via DOI: 10.1016/j.econlet.2015.03.019
ISSN: 0165-1765; 1873-7374
Keyword(s): Cay Stock markets Volatility Nonlinear causality C32 C58 G10 G17
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