IN TERNATIONAL CONFERENCE ON - CIFBA 2020 DETECTING INFORMED TRADING IN HIGH FREQUENCY MARKETS Chan Wung Kim1*, Timothy T Perry2, Sangphill Kim1 University of Massachusetts Lowell, Manning School of Business, University of Tennessee Martin ABSTRACT We investigate the ability of the Volume-Synchronized Probability of Informed Trading (VPIN) metric, developed in Easley, Lopez de Prado, and O’Hara (2011) and (2012a), to detect and measure informed trading in the context of the June 23, 2011 surprise announcement of the release of strategic petroleum reserves by the International Energy Agency (IEA), where news leakage and insider trading occurred before the announcement Our results indicate that VPIN successfully detects informed trading and our analysis suggests that the VPIN methodology has advantages over the Probability of Informed Trading (PIN) methodology of Easley, Kiefer, O’Hara, and Paperman (1996) and Easley, Hvidkjaer, and O’Hara (2002) in modern high frequency trading (HFT) environments * Corresponding author Email address: chanwung_kim@uml.edu 74