| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP13426 |
| DP13426 New testing approaches for mean-variance predictability | |
| Gabriele Fiorentini; ENRIQUE SENTANA | |
| 发表日期 | 2019-01-04 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | We propose tests for smooth but persistent serial correlation in risk premia and volatilities that exploit the non-normality of financial returns. Our parametric tests are robust to distributional misspecification, while our semiparametric tests are as powerful as if we knew the true return distribution. Local power analyses confirm their gains over existing methods, while Monte Carlo exercises assess their finite sample reliability. We apply our tests to quarterly returns on the five Fama-French factors for international stocks, whose distributions are mostly symmetric and fat-tailed. Our results highlight noticeable differences across regions and factors and confirm the fragility of Gaussian tests. |
| 主题 | Financial Economics |
| 关键词 | Financial forecasting Moment tests Misspecification Robustness Volatility |
| URL | https://cepr.org/publications/dp13426 |
| 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/542242 |
| 推荐引用方式 GB/T 7714 | Gabriele Fiorentini,ENRIQUE SENTANA. DP13426 New testing approaches for mean-variance predictability. 2019. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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