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...

We investigate the impact of an exogenous trading glitch at a high-frequency market-making firm on standard measures of stock liquidity (spreads, price impact, turnover, and depth) and institutional trading costs (implementation shortfall and VWAP slippage). Stocks in which the firm accumulates...

Despite strong theoretical predictions based on disagreement, limited empirical evidence has linked short selling restrictions to higher prices. We test this relationship using quasi-experimental methods based on Rule 201, a threshold-based policy that restricts aggressive short selling when...

Amihud's (2002) stock (il)liquidity measure averages daily ratios of absolute close-to-close return to dollar volume, including overnight returns, while trading volumes come from regular hours. Our modified measure addresses this mismatch by using open-to-close returns. It is more strongly...

We document new intraday trading patterns indicative of the key roles of endogenous trading responses of investors to variations in imperfectly-competitive liquidity provision. When measured in trade times of fixed dollar values, price impacts and volatility fall sharply from open to close, and...

We identify Industry-Neutral Self-Financed Informed Trading (INSFIT) by long only fund managers who possess a positive short-lived private signal and self finance informed stock purchases by selling an equivalent dollar amount of stock in the same industry. INSFIT, which constitutes less than 1%...