We examine the role of concurrent information in the striking increase in investor response to earnings announcements from 2001 to 2016, as measured by return variability and volume following Beaver (1968). We find management guidance, analyst forecasts, and disaggregated financial statement...

We find that small innovators earn higher returns than small non-innovators for up to five years. We find no such innovation premium among large firms. A battery of tests shows that this innovation premium among small firms is explained by risk. Our findings, which are based on a simple measure...

Intangible assets have always been part of the economic landscape. In this study we examine the impact of intangibles, both internally developed and externally acquired, on our ability to identify differences in expected stock returns. Our research does not find compelling evidence that we...

This study examines the value relevance of book value, earnings and dividends for a sample of all non-financial firms listed on the Kuwait Stock Exchange (KSE) over the period 2003–2009. After controlling for the impact of the global financial crisis, empirical results provide evidence on the...

In this study, we examine how analysts are affected by the public actions of investors and other analysts by closely examining how analysts revise their earnings forecasts after an earnings announcement. In particular, we hypothesize that analysts observe the actions of investors and other...

We use the recent disappearance of the accrual anomaly to investigate analysts' contribution to improved information processing by investors. Prior research finds that investors and analysts made accrual-related pricing and forecast errors, respectively, in the anomaly period. As sophisticated...

This study compares the information content of funds from operation (FFO) and net income (NI) in the real estate investment trust (REIT) industry. We find that models using FFO explain more of the variance in cumulative abnormal returns around earnings announcement dates than models using NI do....

We show that actively managed U.S. hedge funds, on average, trade on the post-earnings announcement drift anomaly more aggressively than mutual funds. Both mutual and hedge funds that actively trade on drift anomaly face higher arbitrage risk. However arbitrage risk reduces mutual funds'...

I estimate a theory-based behavioral momentum using analysts' predictable underreaction (APU) as a proxy for newswatchers underreaction. The results show that APU strongly predicts analysts' errors and, more importantly, stock returns. A long-short strategy based on APU generates a...

We examine the out-of-sample performance of 240 stock market anomalies enhanced by 49 machine learning algorithms and over 260 individually trained models across an international data sample of nearly 1.9 billion stock-month-anomaly observations from 1980 to 2019. We demonstrate significant...