交易故事的另一面:来自纽约证券交易所的证据

W. Wong, L. Copeland, Ralph Lu
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引用次数: 1

摘要

我们分析了纽约证交所著名的TORQ数据集,该数据集记录了3个月期间的交易,并根据交易的主动方、被动方是机构方还是私人方对交易进行了分解。这使我们能够比较不同贸易类别的回报。我们发现,无论我们如何分析结果,机构在与个人作为交易对手方进行交易时,信息最灵通,收益最高。我们也确认了在其他文献中发现的结论,即知情的交易者经常下限价单,特别是在一天结束时(正如Bloomfield, O.Hara和Saar(2005)的实验室实验所预测的那样)。最后,我们发现机构之间的交易占交易量的大部分,但信息很少,似乎主要是流动性驱动的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Other Side of the Trading Story: Evidence from NYSE
We analyse the well-known TORQ dataset of trades on the NYSE over a 3-month period, breaking down transactions depending on whether the active or passive side was institutional or private. This allows us to compare the returns on the different trade categories. We find that, however we analyse the results, institutions are best informed, and earn highest returns when trading with individuals as counter party. We also confirm the conclusions found elsewhere in the literature that informed traders often place limit orders, especially towards the end of the day (as predicted on the basis of laboratory experiments in Bloomfield, O.Hara, and Saar (2005)). Finally, we find that trading between institutions accounts for the bulk of trading volume, but carries little information and seems to be largely liquidity-driven.
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