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Predicting returns ...
Predicting returns and dividend growth - The role of non-Gaussian innovations
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- Kiss, Tamás, 1988- (författare)
- Örebro universitet,Handelshögskolan vid Örebro Universitet
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- Mazur, Stepan, 1988- (författare)
- Örebro universitet,Handelshögskolan vid Örebro Universitet
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- Nguyen, Hoang, 1989- (författare)
- Örebro universitet,Handelshögskolan vid Örebro Universitet
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(creator_code:org_t)
- Elsevier, 2022
- 2022
- Engelska.
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Ingår i: Finance Research Letters. - : Elsevier. - 1544-6123 .- 1544-6131. ; 46:Part A
- Relaterad länk:
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https://doi.org/10.1...
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visa fler...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- SAMHÄLLSVETENSKAP -- Ekonomi och näringsliv -- Nationalekonomi (hsv//swe)
- SOCIAL SCIENCES -- Economics and Business -- Economics (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- Bayesian VAR
- Dividend Growth Predictability
- Predictive Regression
- Return Predictability
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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