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Microstructure-Based Manipulation: Strategic Behavior and Performance of Spoofing Traders
16/16 checkable references clean · checked 2026-08-05
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The 16 checked references that resolve
resolves10.1016/0014-2921(92)90120-l
Stock price manipulation, market microstructure and asymmetric information
resolves10.1016/0378-4266(94)00105-7
Salomon brothers and the May 1991 Treasury auction: Analysis of a market corner
The 6 references without a DOI — listed, not checked
no DOI — not checkedref5
no DOI — not checkedref6
no DOI — not checkedMarket microstructure in the Korean financial markets: a survey
no DOI — not checkedThe profitability of active stock traders
no DOI — not checkedref21
no DOI — not checkedOur spoofing traders can be classified into two groups: spoofing traders who were not day traders (57.8%) and spoofing traders who were day traders (42.2%). Panel B shows descriptive statistics on extra profit for these two groups. Panel C shows descriptive statistics on extra profit for day traders; the left column represents the day traders who were also spoofers, whereas the right column represents all day traders, regardless of whether they were spoofers. Day trading is defined as the purchase and sale of the same stock by the same investor on the same day. Korea imposes a tax of 30 basis points on the sale of securities paid by the seller. Trading fees during our data period consisted of a fee of approximately one basis point to the exchange, and about seven basis points to online brokers on executed buy and sell orders. Thus, for example, each day-trading strategy costs 46 basis points. All statistics in Part 1 are measured without clustering by day. All statistics in Part 2 are measured by the Fama and MacBeth (1973) approach: average all the observations on a given day, then assume independence across days
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