We measure investors' short- and long-term stock-return expectations using both options and survey data. These expectations at different horizons reveal what investors think their own short-term expectations will be in the future, or forward return expectations. While contemporaneous short-term...

This paper investigates how the stock market reacts to firm level liquidity shocks. We find that negative and persistent liquidity shocks not only lead to lower contemporaneous returns, but also predict negative returns for up to six months in the future. Long-short portfolios sorted on past...

I study the market for lending and borrowing securities in the United States. I find that by making securities available for borrowing, mutual funds acquire information about short selling, which they exploit for trading. Funds with discretion in their investment choices rebalance their...

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 study the use of firms' book-to-market ratios (B/M) in value investing and its implications for comovements in firms’ stock returns and trading volumes. We show B/M has become increasingly detached from common alternative valuation ratios over time while also becoming worse at forecasting...

We propose a new methodology to build portfolios that hedge the economic and financial risks from climate change. Our quantity-based approach exploits information on how mutual fund managers trade in response to idiosyncratic changes in their climate risk beliefs. We exploit two types of...

In this work, I study the impact of high-frequency trading (HFT) on price discovery and volatility in the Bund futures market. Using a new dataset based on microseconds, the focus of the study is on the reaction of high-frequency traders (HFTs) to major macroeconomic news events. I show that...

We propose a nonparametric Bayesian approach for the estimation of the pricing kernel. Historical stock returns and option market data are combined through the Dirichlet Process (DP) to construct an option-adjusted physical measure. The precision parameter of the DP process is calibrated to the...

Trading activity surges associated with latency arbitrage are costly, as they lead to both lower liquidity and inefficient investments in order processing capacity that remains idle 90% of the time. A congestion message fee on liquidity-taking orders alleviates both concerns. The fee surges...

We examine initial public offerings (IPOs) with single, multiple, and no credit ratings. We document a beneficial effect of credit ratings on IPO underpricing, which is amplified by the existence of multiple credit ratings. Multiple ratings also reduce the extent of filing price revisions....