We propose a new measure of time-varying tail risk that is directly estimable from the cross section of returns. We exploit firm-level price crashes every month to identify common fluctuations in tail risk across stocks. Our tail measure is significantly correlated with tail risk measures...

This paper establishes a robust link between the trading behavior of institutions and the book-to-market effect. Building on work by Daniel and Titman (2006), who argue that the book-to-market effect is driven by the reversal of intangible returns, I find that institutions tend to buy (sell)...

This paper studies how the stock market perceives and prices cyber risk. To estimate the ex-ante likelihood that a firm will experience a cyber attack, we apply cross-validated logistic LASSO regressions to a set of firm and industry characteristics along with an estimate of a firm's...

This paper shows a strong link between granular information contained in individual stock prices and sectoral movements. Using machine learning algorithms, we find that a predictor that aggregates the price movements of a broad cross-section of individual stocks predicts sector ETF returns...

We show theoretically and empirically that flows into index funds raise the prices of large stocks in the index disproportionately more than the prices of small stocks. Conversely, flows predict a high future return of the small-minus-large index portfolio. This finding runs counter to the CAPM,...

We propose a new measure of time-varying tail risk that is directly estimable from the cross section of returns. We exploit firm-level price crashes every month to identify common fluctuations in tail risk across stocks. Our tail measure is significantly correlated with tail risk measures...