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Trade‐size clustering and informed trading in global markets
Author(s) -
Chen Tao
Publication year - 2020
Publication title -
international journal of finance and economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.505
H-Index - 39
eISSN - 1099-1158
pISSN - 1076-9307
DOI - 10.1002/ijfe.1768
Subject(s) - cluster analysis , exploit , economics , financial economics , computer science , computer security , machine learning
Based on intraday data across 41 markets, this study examines whether informed traders exploit trade‐size clustering. Clustering trades are documented to predict price movements, to generate perpetual return impact, and to improve informational efficiency. Collectively, these findings suggest that the clustering strategy is leveraged by the informed to cover up their activities in global markets. In addition, the cross‐country analysis indicates that larger market capacity and better legal protection, as two predominant institutional features, are associated with a lower level of informed‐trade clustering. Finally, such negative interaction attenuates in countries with lot‐size regulations and at bellwether stocks.