Abstract
This chapter considers stock return and dividend (and earnings) growth predictability for a range of international stock markets. In contrast to the literature which focuses purely on the predictive equation, we consider both this and the underlying cointegrating regression. In addition, using a state-space modelling approach, we allow for time-variation within the cointegrating relation. The results show a strengthening of the results as we move from the usual predictive regression (which imposes a constant cointegrating vector of 1, −1) to an approach that allows the cointegrating parameter to be freely estimated and ultimately to an approach that allows this cointegrating parameter to fluctuate around a constant value. Of notable interest in our results is that greater evidence of stock return predictability is found for the markets of the UK, USA and Asia compared to European markets.
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Notes
- 1.
McMillan (2015) uses a state-space model for stock returns and introduces a range of explanatory variables that govern movement of the slope parameter on the dividend yield .
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- 3.
Although the shorter US series indicates non-stationarity.
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McMillan, D.G. (2018). Where Does Returns and Cash-Flow Predictability Occur? Evidence from Stock Prices, Earnings, Dividends and Cointegration. In: Predicting Stock Returns. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-319-69008-7_2
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DOI: https://doi.org/10.1007/978-3-319-69008-7_2
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