We use earnings forecasts from a cross-sectional model to proxy for cash flow expectations and estimate the implied cost of capital (ICC) for a large sample of firms over 1968-2008. The earnings forecasts generated by the cross-sectional model are superior to analysts' forecasts in terms of...

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 investigate the relation between two market anomalies to provide insights into analysts' role as information intermediaries. Prior research finds that accruals and analyst earnings forecast revisions predict future returns. We find that the accrual and forecast revision strategies generate...

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'...

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...

We exploit information in option prices in order to study whether the ex post responsiveness of tock prices to earnings information is reflected from an ex ante, firm- and quarter-specific perspective. Specifically, we develop a measure of anticipated information content (AIC) that isolates the...

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....

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...

Large earnings surprises and negative earnings surprises represent more egregious errors in analysts' earnings forecasts. We find evidence consistent with our expectation that egregious forecast errors motivate analysts to work harder to develop or acquire relatively more private information in...

This paper tests several predictions from an information diffusion framework in the quarterly earnings announcement setting. First, post-announcement drift is documented only for earnings announcements that have high information content (uncertainty), measured by high abnormal trading volume and...