We apply state-of-the-art financial machine learning to assess the return-predictive value of more than 45,000 earnings announcements on a majority of S&P1500 constituents. To represent the diverse information content of earnings announcements, we generate predictor variables based on various...

We propose a tone-based event study to reveal the aggregate abnormal tone dynamics in media articles around earnings announcements. We test whether they convey incremental information that is useful for price discovery for non financial S&P 500 firms. The positive relationship found between the...

On September 20, 2016, the Japan Securities Dealers Association implemented guidelines that prohibited securities sell-side analysts to obtain an earnings preview before the earnings' official release. We examine the unique impact of the guidelines on market behavior and analyst forecasts in the...

The purpose of this paper is to analyse the predictability of earnings information before the quarterly disclosure date. Two categories of firms are contrasted: the firms that announce better quarterly earnings than the prior period and the firms that do not. The paper uses a sample of 67...

We explore the impact of earnings announcements on equity markets, using intraday price data for the DJIA stocks. We find on a daily basis, an abnormally high volatility only within one day following the overnight announcement. On an intraday basis, a striking volatility spike stands out during...

I hypothesize that the stock market overreacts to management earnings forecasts because of the uncertainty surrounding them. I find that negative management forecast surprises lead to a –5.9% abnormal return around the forecast and a 1.9% correction in the 2-month period after earnings are...