Informed Trading Intensity
Journal of Finance, Forthcoming
93 Pages Posted: 15 Jun 2021 Last revised: 11 Jul 2023
Date Written: June 27, 2023
We train a machine learning method on a class of informed trades to develop a new measure of informed trading, the Informed Trading Intensity (``ITI''). ITI increases before earnings, M&A, and news announcements, and has implications for return reversal and asset pricing. ITI is effective because it captures nonlinearities and interactions between informed trading, volume, and volatility. This data-driven approach can shed light on the economics of informed trading, including impatient informed trading, commonality in informed trading, and models of informed trading. Overall, learning from informed trading data can generate an effective informed trading measure.
Keywords: Informed trading, machine learning, adverse selection, stock returns, intraday data
JEL Classification: G10, G12, G14
Suggested Citation: Suggested Citation