Using high-frequency transaction data to estimate the probability of informed trading

• المؤلفون الرئيسيون: TAY, Anthony S., TING, Christopher, TSE, Yiu Kuen, WARACHKA, Mitchell
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2009
• الموضوعات: autoregressive conditional duration; market microstructure; probability of informed trading; transaction data; Weibull distribution; Econometrics; Finance; Finance and Financial Management
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/soe_research/519; https://ink.library.smu.edu.sg/context/soe_research/article/1518/viewcontent/UsingHighFreqTransactionData_2009_JFE.pdf

This paper applies the asymmetric autoregressive conditional duration (AACD) model of Bauwens and Giot (2003) to estimate the probability of informed trading (PIN) using irregularly spaced transaction data. We model trade direction (buy versus sell orders) and the duration between trades jointly. Un...