Predicting returns and dividend growth — The role of non-Gaussian innovations

Tamas Kiss, Stepan Mazur and Hoang Nguyen

Finance Research Letters, 2022, vol. 46, issue PA

Abstract: In this paper we assess whether flexible modelling of innovations impact the predictive performance of the dividend price ratio for returns and dividend growth. Using Bayesian vector autoregressions we allow for stochastic volatility, heavy tails and skewness in the innovations. Our results suggest that point forecasts are barely affected by these features, suggesting that workhorse models on predictability are sufficient. For density forecasts, however, we find that stochastic volatility substantially improves the forecasting performance.

Keywords: Bayesian VAR; Dividend growth predictability; Predictive regression; Return predictability (search for similar items in EconPapers)
JEL-codes: C11 C58 G12 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Working Paper: Predicting returns and dividend growth - the role of non-Gaussian innovations (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:46:y:2022:i:pa:s1544612321003445

DOI: 10.1016/j.frl.2021.102315

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