| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w30366 |
| 来源ID | Working Paper 30366 |
| How and When are High-Frequency Stock Returns Predictable? | |
| Yacine Aït-Sahalia; Jianqing Fan; Lirong Xue; Yifeng Zhou | |
| 发表日期 | 2022-08-22 |
| 出版年 | 2022 |
| 语种 | 英语 |
| 摘要 | This paper studies the predictability of ultra high-frequency stock returns and durations to relevant price, volume and transactions events, using machine learning methods. We find that, contrary to low frequency and long horizon returns, where predictability is rare and inconsistent, predictability in high frequency returns and durations is large, systematic and pervasive over short horizons. We identify the relevant predictors constructed from trades and quotes data and examine what determines the variation in predictability across different stock's own characteristics and market environments. Next, we compute how the predictability improves with the timeliness of the data on a scale of milliseconds, providing a valuation of each millisecond gained. Finally, we simulate the impact of getting an (imperfect) peek at the incoming order flow, a look ahead ability that is often attributed to the fastest high frequency traders, in terms of improving the predictability of the following returns and durations. |
| 主题 | Econometrics ; Estimation Methods ; Financial Economics ; Portfolio Selection and Asset Pricing ; Financial Markets |
| URL | https://www.nber.org/papers/w30366 |
| 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/588038 |
| 推荐引用方式 GB/T 7714 | Yacine Aït-Sahalia,Jianqing Fan,Lirong Xue,et al. How and When are High-Frequency Stock Returns Predictable?. 2022. |
| 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 | ||
| w30366.pdf（746KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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