Assessing influential trade effects via high-frequency market reactions

Meihui Guo, Yi Ting Guo, Chi Jeng Wang, Liang Ching Lin

研究成果: Article同行評審


In the literature, traders are often classified into informed and uninformed and the trades from informed traders have market impacts. We investigate these trades by first establishing a scheme to identify the influential trades from the ordinary trades under certain criteria. The differential properties between these two types of trades are examined via the four transaction states classified by the trade price, trade volume, quotes, and quoted depth. Marginal distribution of the four states and the transition probability between different states are shown to be distinct for informed trades and ordinary liquidity trades. Furthermore, four market reaction factors are introduced and logistic regression models of the influential trades are established based on these four factors. Empirical study on the high-frequency transaction data from the NYSE TAQ database show supportive evidence for high correct classification rates of the logistic regression models.

頁(從 - 到)1458-1471
期刊Journal of Applied Statistics
出版狀態Published - 2015 7月 3

All Science Journal Classification (ASJC) codes

  • 統計與概率
  • 統計、概率和不確定性


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