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来源类型Working Paper
规范类型报告
DOI10.3386/w30366
来源IDWorking 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
URLhttps://www.nber.org/papers/w30366
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/588038
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GB/T 7714
Yacine Aït-Sahalia,Jianqing Fan,Lirong Xue,et al. How and When are High-Frequency Stock Returns Predictable?. 2022.
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