Arbeitspapier

Dividend momentum and stock return predictability: A Bayesian approach

A long tradition in macro finance studies the joint dynamics of aggregate stock returns and dividends using vector autoregressions (VARs), imposing the cross-equation restrictions implied by the Campbell-Shiller (CS) identity to sharpen inference. We take a Bayesian perspective and develop methods to draw from any posterior distribution of a VAR that encodes a priori skepticism about large amounts of return predictability while imposing the CS restrictions. In doing so, we show how a common empirical practice of omitting dividend growth from the system amounts to imposing the extra restriction that dividend growth is not persistent. We highlight that persistence in dividend growth induces a previously overlooked channel for return predictability, which we label "dividend momentum." Compared to estimation based on ordinary least squares, our restricted informative prior leads to a much more moderate, but still significant, degree of return predictability, with forecasts that are helpful out of sample and realistic asset allocation prescriptions with Sharpe ratios that outperform common benchmarks.

Sprache
Englisch

Erschienen in
Series: Working Paper ; No. 2021-25

Klassifikation
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Forecasting Models; Simulation Methods
Portfolio Choice; Investment Decisions
Asset Pricing; Trading Volume; Bond Interest Rates
Money and Interest Rates: Forecasting and Simulation: Models and Applications
Thema
CS restrictions
Bayesian VAR
optimal allocation
Dividende
Börsenkurs
Bayes-Statistik
Prognoseverfahren
USA

Ereignis
Geistige Schöpfung
(wer)
Antolín-Díaz, Juan
Petrella, Ivan
Rubio-Ramírez, Juan Francisco
Ereignis
Veröffentlichung
(wer)
Federal Reserve Bank of Atlanta
(wo)
Atlanta, GA
(wann)
2021

DOI
doi:10.29338/wp2021-25
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Antolín-Díaz, Juan
  • Petrella, Ivan
  • Rubio-Ramírez, Juan Francisco
  • Federal Reserve Bank of Atlanta

Entstanden

  • 2021

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