This paper studies the predictability of ultra high-frequency stock returns and durations to relevant price, volume and transactions events, using machine learning methods. We find that, contrary to low frequency and long horizon returns, where predictability is rare and inconsistent,...

We examine abnormal stock returns surrounding contemporaneous earnings and dividend announcements in order to determine whether investors evaluate the two announcements in relation to each other.We find that there is a statistically significant interaction effect.The abnormal return...

An exclusive focus on bottom-line income misses important information about the quality of earnings. Accruals (the difference between accounting earnings and cash flow) are reliably, negatively associated with future stock returns. Earnings increases that are accompanied by high accruals,...

Savings increasingly flow to low-cost index funds, which simply buy and hold the stocks in a major index, such as the S&P 500. Increased indexing impedes incorporation of idiosyncratic information into stock prices. We limit endogeneity bias by showing that exogenous idiosyncratic currency...

We find that procyclical stocks, whose returns comove with business cycles, earn higher average returns than countercyclical stocks. We use almost a three-quarter century of real GDP growth expectations from economists' surveys to determine forecasted economic states. This approach largely...

We provide evidence for a causal link between the US economy and the global financial cycle. Using intraday data, we show that US macroeconomic news releases have large and significant effects on global risky asset prices. Stock price indexes of 27 countries, the VIX, and commodity prices all...

We study strategic disclosure timing by correlated firms in the presence of risk-averse investors. Firms delay disclosures in the hope that positively correlated firms will announce especially good news and lift their own price. Risk premia rise before disclosures, drop when disclosures occur,...

This paper relates jumps in high frequency stock prices to firm-level, industry and macroeconomic news, in the form of machine-readable releases from Thomson Reuters News Analytics. We find that most relevant news, both idiosyncratic and systematic, lead quickly to price jumps, as market...

We characterize how risk evolves during a crisis. Using high-frequency data, we find that the first two principal components (PCs) of the covariance matrix of global asset returns experience large, sudden, and temporary spikes coinciding with well-known crises - Covid-19 pandemic, Global...