We develop a measure of how information events impact investors' perceptions of risk that is broadly applicable and simple to implement. We derive this measure from an option-pricing model where investors anticipate an announcement that simultaneously conveys information on the announcer's...

We provide evidence that equity investors with limited attention are slow to incorporate how current oil price changes affect future earnings announcements. A cross-sectional equity trading strategy that exploits this inefficiency yields an annualized Sharpe Ratio of 0.57. Stock prices respond...

We provide a psychological explanation for the delayed price response to news about economically linked firms. We show that the return predictability of economically linked firms depends on the nearness to the 52-week high stock price. The interaction between news about economically linked firms...

The enterprise multiple (EM) effect has been documented across global stock markets. EM is a robust predictor of expected average returns and generates a stronger value effect than traditional value metrics. We find evidence the EM effect is primarily attributable to mispricing and cannot be...

We introduce a new measure of stock misevaluation, 𝑄, which is consistent with the Gordon growth model for firm valuation. In our empirical application, we use 𝑄 to relate analyst forecasts to stock returns and measure the profitability of investment strategies that rely on information in...

What is the market impact of predictable order flow? Leveraged exchange-traded products are useful for answering this question because they generate daily rebalancing flows whose size, sign and timing are predictable. This paper presents new evidence from the market for leveraged volatility...

This paper shows that investments based on deep learning signals extract profitability from difficult-to-arbitrage stocks and during high limits-to-arbitrage market states. In particular, excluding microcaps, distressed stocks, or episodes of high market volatility considerably attenuates...

We construct a measure of analyst-level distraction based on analysts' exposure to exogenous attention-grabbing events affecting firms under coverage. We find that temporarily distracted analysts achieve lower forecast accuracy, revise forecasts less frequently, and publish less informative...

We study how 9 different market participants trade with respect to 130 different stock return anomalies and how each participant's trades predict returns. Retail investors trade against anomalies, while firms' and short sellers' trades agree with anomalies. Institutional portfolios are weighted...

Stock momentum, long-term reversal, and other past return characteristics that predict future returns also predict future realized betas, suggesting these characteristics capture time-varying risk compensation. We formalize this argument with a conditional factor pricing model. Using...