Pre-earnings Announcement Strategies
Featuring Wall Street Horizon data in his research, Dr. Ernest Chan delves into pre-earnings announcement strategies...
Read MoreWall Street Horizon's data has been used as a primary source in several independent academic studies. Professors have investigated our data and have found corporate event data such as earnings date revisions can have a significant impact on investment returns.
While the academics listed made extensive use of Wall Street Horizon corporate event data, please note Wall Street Horizon does not sponsor academic research; all papers are conducted independently by the researchers and their teams at their respective organizations.
If you haven't read our white paper Exploring Corporate Event Data and Volatility:
Considerations for Academic and Financial Industry Research, it shares examples of how several academic researchers have leveraged high-quality data to conduct independent research and publish their results in academic journals. We recently updated it with seven additional studies that investigate how corporate event data impacts investment returns.
Offered within are examples of how several academic researchers have leveraged high-quality data to conduct independent research and publish their results in academic journals.
Seven additional studies from around the global that investigate how corporate event data impacts investment returns.
If you are a professor or student conducting research at your academic institution, please contact us.
Featuring Wall Street Horizon data in his research, Dr. Ernest Chan delves into pre-earnings announcement strategies...
Read MoreDo managers attempt to hide bad news by announcing earnings during periods of low market attention?
Read MoreWith Wall Street Horizon as the primary source of data for this study, the authors show that abnormal returns can be realized when tracking schedule earnings release dates...
Read MoreUsing Wall Street Horizons’ quarterly earnings announcement dates and annual meeting of shareholders dates, the authors provide evidence that option implied volatility-based measures predict future excess returns for stocks.
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