Dividend momentum and stock return predictability: A Bayesian approach

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Paper ; No. 2021-25

Classification and Topics

• Classification: 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
• Subject: CS restrictions ; Bayesian VAR ; optimal allocation ; Dividende ; Börsenkurs ; Bayes-Statistik ; Prognoseverfahren ; USA

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Antolín-Díaz, Juan ; Petrella, Ivan ; Rubio-Ramírez, Juan Francisco
• Event: Veröffentlichung
• (who): Federal Reserve Bank of Atlanta
• (where): Atlanta, GA
• (when): 2021

Further information

• DOI: doi:10.29338/wp2021-25
• Handle: http://hdl.handle.net/10419/249861
• Last update: 10.03.2025, 11:42 AM CET