| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w27410 |
| 来源ID | Working Paper 27410 |
| Biases in Long-Horizon Predictive Regressions | |
| Jacob Boudoukh; Ronen Israel; Matthew P. Richardson | |
| 发表日期 | 2020-06-22 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | Analogous to Stambaugh (1999), this paper derives the small sample bias of estimators in J-horizon predictive regressions, providing a plug-in adjustment for these estimators. A number of surprising results emerge, including (i) a higher bias for overlapping than nonoverlapping regressions despite the greater number of observations, and (ii) particularly higher bias for an alternative long-horizon predictive regression commonly advocated for in the literature. For large J, the bias is linear in (J/T) with a slope that depends on the predictive variable’s persistence. The bias adjustment substantially reduces the existing magnitude of long-horizon estimates of predictability. |
| 主题 | Econometrics ; Estimation Methods ; Financial Economics ; Portfolio Selection and Asset Pricing ; Financial Markets |
| URL | https://www.nber.org/papers/w27410 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/585083 |
| 推荐引用方式 GB/T 7714 | Jacob Boudoukh,Ronen Israel,Matthew P. Richardson. Biases in Long-Horizon Predictive Regressions. 2020. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w27410.pdf（857KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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