This research aims to obtain empirical evidence regarding financial performance's role in disseminating components that affect the stock holding period. Companies listed in the LQ-45 index from the 2013 to 2017 period on the Indonesia Stock Exchange were the study samples. The sample selection...

An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the...

Ricks [1982] found that stock returns near the earnings disclosure dates of 1974 LIFO adopters were negative and significantly lower than returns near the earnings disclosure dates of firms not using LIFO.Given that firms adopting LIFO in 1974 were voluntarily switching to an accounting method...

This paper is an empirical investigation of the relation between the dispersion on analysts' earnings forecasts and the future performance following a change in the nominal price of shares. On a sample of US splits occurred from 1993 to 2013, we observe a change in the distribution of analysts'...

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...

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 constructed forecasts of earnings forecasts using data on 406 firms and forecasts made by 5419 individuals with on average 25 forecasts per individual. We verified previously found predictors, which are the average of the most recent available forecast for each forecaster and the difference...

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...

Previous research finds that historical seasonal earnings rank negatively predicts stock returns surrounding earnings announcements (EAs) in China’s A-share markets. We examine whether management earnings forecasts (MEFs) help reduce the stock return seasonality associated with earnings...