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Predicting stock market movements with a time-varying consumption-aggregate wealth ratio

Tsangyao Chang (), Rangan Gupta (), Anandamayee Majumdar and Christian Pierdzioch

International Review of Economics & Finance, 2019, vol. 59, issue C, 458-467

Abstract: We develop a time-varying measure of cay (cayTVP) using time-varying cointegration, and then compare the predictive ability of cayTVP with cay and a Markov-switching cay (cayMS) for excess stock returns and volatility in the US over the period 1952:Q2-2015:Q3, using a k-th order nonparametric causality-in-quantiles test. We find that time-varying cointegration exists between consumption, asset wealth, and labor income. In addition, while there is no evidence of predictability of volatility of excess returns from cay, cayMS, or cayTVP, they tend to act as strong predictors of stock returns, with cayTVP being important during the bearish phases of the equity market.

Keywords: Consumption-aggregate wealth ratio; Time-varying cointegration; Stock returns; Volatility; Nonparametric causality-in-quantiles test (search for similar items in EconPapers)
JEL-codes: C22 G10 (search for similar items in EconPapers)
Date: 2019
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Related works:
Working Paper: Predicting Stock Market Movements with a Time-Varying Consumption-Aggregate Wealth Ratio (2017)
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