交易量能验证高算法交易活动时代的极端价格走势吗?

Yu-Jung L. Avis, Chingfu Chang, Dandan Wu
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引用次数: 0

摘要

我们采取实践者的观点,专注于跟踪特定股票的纵向表现,并调查交易量是否可以在极端价格波动的日子里提供指导。对于价格极端上涨(赢家)和价格极端下跌(输家)的日子,我们表明,极低的成交量与未来的回报反转有关,而极高的成交量并不一定导致未来的回报持续。我们查看了1989年至2014年的每日数据,我们认为2004年是算法交易活动开始加剧的一年。我们发现,自2004年以来,极低交易量在否定极端价格变动方面的作用一直在减弱。在某种程度上,极低的交易量可能仍然适用于拒绝极端的价格变动,从业者可能会限制他或她的范围,以低交易量的赢家和小资本的输家。此外,我们使用1992年至2014年的中国数据来重复测试。我们发现,同样的特征在那里没有显示出来,这表明我们从美国数据中得出的结论缺乏普遍性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Can Trading Volume Validate Extreme Price Movements in the Age of Higher Algorithmic Trading Activities?
We take the perspective of the practitioner who focuses on following the longitudinal performance of specific stocks and investigate whether volume may provide guidance on days of extreme price movements. For days of extreme price increases (the winners) and extreme price decreases (the losers), we show that extreme low volume is associated with future return reversal, whereas extreme high volume does not necessarily lead to future return persistence. We look at daily data from 1989 to 2014, and we consider 2004 to be the year when algorithmic trading activities began to intensify. We find that the usefulness of extreme low volume in repudiating extreme price movements has been diminishing since 2004. To the extent that extreme low volume may still be applied to repudiate extreme price movements, a practitioner may limit his or her scope to the low-volume winners and losers of small capitalization. In addition, we use Chinese data from 1992 to 2014 to replicate the tests. We find that the same characteristics are not shown there, indicating a lack of universality of the conclusions we derived from the U.S. data.
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