| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP16613 |
| DP16613 Dividend Momentum and Stock Return Predictability: A Bayesian Approach | |
| Juan Francisco Rubio-Ramírez; Ivan Petrella; Juan Antolin-Diaz | |
| 发表日期 | 2021-10-05 |
| 出版年 | 2021 |
| 语种 | 英语 |
| 摘要 | 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 OLS, our restricted informative prior leads to a much more moderate, but still signi cant, degree of return predictability, with forecasts that are helpful out-of-sample and realistic asset allocation prescriptions with Sharpe ratios that out-perform common benchmarks. |
| 主题 | Financial Economics |
| URL | https://cepr.org/publications/dp16613 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/545560 |
| 推荐引用方式 GB/T 7714 | Juan Francisco Rubio-Ramírez,Ivan Petrella,Juan Antolin-Diaz. DP16613 Dividend Momentum and Stock Return Predictability: A Bayesian Approach. 2021. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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