Informed Trading Intensity
用机器学习从知情交易数据中训练出一个新指标：知情交易强度（ITI），发现它在财报、并购等事件前上升，并能预测收益反转和资产定价，对研究知情交易的经济学含义很有用。
ABSTRACT We train a machine learning method on a class of informed trades to develop a new measure of informed trading, informed trading intensity (ITI). ITI increases before earnings, mergers and acquisitions, 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.