Do Prices Reveal the Presence of Informed Trading?

Using a comprehensive sample of trades from Schedule 13D filings by activist investors, we study how measures of adverse selection respond to informed trading. We find that on days when activists accumulate shares, measures of adverse selection and of stock illiquidity are lower, even though prices are positively impacted. Two channels help explain this phenomenon: (1) activists select times of higher liquidity when they trade, and (2) activists use limit orders. We conclude that, when informed traders can select when and how to trade, standard measures of adverse selection may fail to capture the presence of informed trading.     

Informed Trading Intensity

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.     

Endogenous Cycles in Collateralized Credit

This paper presents a simple and tractable equilibrium model, where collateralized credit emerges under limited commitment. We show that even if there is no time variation in fundamentals, credit trade can fluctuate endogenously over time. In our theory, credit fragilities are associated with endogenous fluctuations in trade probabilities, collateral values, and lending volumes.