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Conducting Event Studies in R

For conducting own event studies in R, please install our EventStudy R-package from the CRAN repository:

Alternatively, you can also develop your own R code building on top of an earlier set of R-files we created (currently not available). Similar as when using our server-side research apps, you will need three CSV input files: one for stock returns, one for market returns, and the third one with the events of interests. The analysis is structured in five steps:

  1. Load the data with correct measurement scale
  2. Filtering firm and market data by the information from the event file, calculate returns
  3. Get the estimation and event window for firm and market data
  4. Fit the linear model on the estimation window
  5. Calculate the abnormal return, t-statistics and two-sided p-value for each abnormal return in the event window

Based on the results, you will be able to plot the abnormal return with 95%-confidence interval (see Figure 1).

If you need more advanced analysis or help with graphics, please make use of our R-package. It posesses the same capabilities as our server-side research apps and continues to evolve with these. Currently our R package is just available on github (CRAN submission is already done). You are able to install it from github:

# you need to install devtools first


-- Please consider using our free server-side abnormal return calculators to perform your event study, including all test statistics --

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Dr. Simon Müller

Dr. Simon Müller studied mathematics and technical mechanics at the University of Stuttgart, Germany. He holds a Ph. D. in mathematics from the University of Stuttgart. After his Ph.D. thesis Simon worked as a Postdoc at the Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology in Stuttgart. Since 2012 he works as an independent statistical consultant. He is an expert R programmer and has working knowledge on statistic software SAS Base/Stat/Graph, and SPSS Statistics.