Free apps for event studies and news analytics
This website allows you to easily perform event studies and news analytics analyses. Beyond this analytical support, it holds reviews of methodological literature, access to event study experts, and an API and R-package with which you can integrate our capabilities directly in your own solutions. We are driven by our goal to help you get published.
Use our Award-winning research apps - for free!
How to conduct event studies with www.eventstudytools.com?
This website's research apps make it simple to conduct event studies: Specify your research parameters, retrieve the data you need for your analysis from a financial data provider (e.g., Yahoo!Finance), bring the data into the right structure, and upload it to the respective research app (see Figure 1). As for event studies, we currently offer three research apps, or "abnormal effect calculators". The one most often used is the abnormal return calculator (ARC). For trading volume event studies, we offer the abnormal volume calculator (AVC), and for volatiltiy event studies, the abnormal volatility calculator (AVyC). All research apps are free-of-charge and perform for you various test statistics. You can upload your analysis data in various input formats, including XLS, XLSX, and CSV - zipped or unzipped. You receive all results by email and/or as a direct download on the website.
Figure 1: Conducting Event Studies with EventStudyTools
What is news analytics and how to apply it?
The quantitative analysis of news streams is labeled as news analytics. It typically describes the full sequence of steps needed to turn news releases into quantitative metrics and time-series. There is a multitude of news analytics applications: First, the scientific analysis of qualitative dimensions of news that have previously been left unexplored. Second, the comparative analysis of event sequences. And finally, various practical applications, such as news-based trading strategies, that trace actual firm behaviors. The figure beneath sketches the analytical framework that is implemented on this website (see step-by-step tutorial) and has been used in various research publications.