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Consumption growth and time-varying expected stock returns

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Author Info
Stig Vinther Møller () (School of Economics and Management, University of Aarhus, Denmark and CREATES)
Abstract

When the consumption growth rate is measured based upon fourth quarter data, it tracks predictable variation in future excess stock returns. Low fourth quarter consumption growth rates predict high future excess stock returns such that expected returns are high at business cycle troughs and low at business cycle peaks. The consumption growth rate loses predictive power when it is measured based upon other quarters. This is consistent with the insight of Jagannathan and Wang (2007) that investors tend to review their consumption and investment plans during the end of each calendar year, and at possibly random times in be- tween. The consumption growth rate measured based upon fourth quarter data is a much stronger predictive variable than benchmark predictive variables such as the dividend-price ratio, the term spread, and the default spread.

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Publisher Info
Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2008-40.

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Length: 13
Date of creation: 02 Sep 2008
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Handle: RePEc:aah:create:2008-40

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Web page: http://www.econ.au.dk/afn/

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Related research
Keywords: Return predictability; Consumption growth;

Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
E21 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

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  1. Newey, Whitney K & West, Kenneth D, 1987. "A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, Econometric Society, vol. 55(3), pages 703-08, May. [Downloadable!] (restricted)
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  2. Robert F. Stambaugh, 1999. "Predictive Regressions," NBER Technical Working Papers 0240, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  3. Kothari, S. P. & Shanken, Jay, 1997. "Book-to-market, dividend yield, and expected market returns: A time-series analysis," Journal of Financial Economics, Elsevier, vol. 44(2), pages 169-203, May. [Downloadable!] (restricted)
  4. Nelson, Charles R & Kim, Myung J, 1993. " Predictable Stock Returns: The Role of Small Sample Bias," Journal of Finance, American Finance Association, vol. 48(2), pages 641-61, June. [Downloadable!] (restricted)
  5. Goetzmann, W.N., 1990. "Testing The Predictive Power Of Dividend Yields," Papers fb-_90-12, Columbia - Graduate School of Business.
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  6. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November. [Downloadable!] (restricted)
  7. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October. [Downloadable!] (restricted)
  8. Ravi Jagannathan & Yong Wang, 2007. "Lazy Investors, Discretionary Consumption, and the Cross-Section of Stock Returns," Journal of Finance, American Finance Association, vol. 62(4), pages 1623-1661, 08. [Downloadable!] (restricted)
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