Welcome to EventStudyTools: Research Apps for Event Studies

This website facilitates the dissemination and use of scientific methods and tools (i.e., event study methodology & news analytics) that help to study discrete events, either as single units of analysis or as parts of larger event sequences. Specifically, the website provides research apps to support a broad range of academic and practical applications.

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What is the purpose of this website?

EventStudyTools provides research apps to conduct event studies, news analytics, or other event-centric research - e.g., based on the event history methodology or optimal matching. Our research apps empower hundreds of research projects every day all over the globe. Several papers from past projects have received internationally recognized awards and got published in renown journals. Please refer to our research tracker to gain an understanding of how our apps can be combined to drive innovative research.



How to conduct event studies with www.eventstudytools.com?

Conducting event studies with this website is very simple. It implies a short sequence of steps illustrated in Figure 1. The only step specific to conducting event studies with this website is the transformation of your data into the format required by the website's abnormal return calculators. Irrespective of whether you use the free basic (bARC) or the access-restricted advanced abnormal return calculator (aARC - beta, purchase a passkey), you need to upload three CSV-data files: One file specifying the analysis parameters (i.e., the request file) and two files holding your stock and reference index price information (example files for bARC and aARC, macro for Yahoo! Finance data retrieval, help in file construction, help in defining your research question). After uploading these files, the research app will perform your event study and prompt you results through CSV files.

Figure 1: Conducting Event Studies with EventStudyTools

What is news analytics and how to perform it?

News analytics is concerned with the quantitative analysis of news streams (e.g., Das, 2010; Kimbrough, Kimbrough et al. 2011). It also implies the procedural steps needed to turn news items into quantitative metrics and time-series. News analytics allows three major applications: (a) the scientific consideration of qualitative dimensions that have previously been ignored in the study of individual events, (b) the repeated longitudinal consideration of similar sequences of events (e.g., characterizing organizational behaviors), and (c) from a practical perspective, novel trading strategies and other practical applications that draw on the capability to plot firm behaviors (e.g., business intelligence). Figure 1 sketches the analytical framework implemented on this website (please also view this step-by-step tutorial).

What features do the event study research apps of this website support?

Short- and Long-Term Event Studies

Parametric and Non-Parametric Test Statistics


Averaged Abnormal Returns

Cumulative Abnormal Returns


Fama-French Calender Time Portfolios*

Time-series t-Test

Cross-sectional t-Test

(adj.) Patell Test

(adj.) BMP Test

Corrado Rank Test

GRANK T & Z-Test




Skewness-Adjusted Test*

Market Model

Market Adjusted

Constant Mean

Scholes/Williams Model*


Multifactor Models*

Matching Models*

Stocks and Bonds*

* to be launched soon