Expert Dialog

Question #57: Scope of Service & Data Inputs

I would like to use your server app to conduct an event study and trying to find out if the app can completely replace an analysis with a statistics software like Stata or R? Also, I was wondering if you offer further advice or forums to better understand the preparations of the datasets before one is able to upload the request files? Is it also possible to use own (rather specific) indices as benchmark returns for CAARs and to use non-Yahoo or Google Finance sources but data from commercial data providers like Datastream for the share price data to be analyzed with the app?

Answer by Dr. Markus Schimmer:
EST's server-side research apps replace the use of other statistical software for the defined scopes of each individual research app. For the case of an event study, this means the following: As long as want to perform an event study only and are interested only in ARs, AARs, CARs, CAARs, and the respective test statistics, you are all set. Instead, if you want to explain the abnormal returns using multiple regression analysis, you will need another statistical software package for the regression. EST only provides analytics and no data. Hence, you are free to choose whatever financial data you can organize and put into the apps. Simply make sure the data lives up to the requirements of the respective research app - as described on the introductions to the individual apps.
Question #56: AR vs. AAR / CAR vs. CAAR


Answer by Dr. Markus Schimmer:
Question #55: Importance of currency


Answer by Dr. Markus Schimmer:
Question #54: Large scale event study

I am currently conducting a large-scale event study. I am using R and the EventStudy package. It turns out that I am only able to upload around 2000 stock prices otherwise I receive the error code:

Request Status Code: 500
Error: Argument 'txt' must be a JSON string, URL or file

Is there any way to use the package for a large amount of data e.g. 200k stock prices in the overall analysis?

Answer by Dr. Markus Schimmer:
We strongly recommend using the API directly for large-scale studies. This will give you also some additional flexibility in structuring the analysis - if needed.
Question #53: can not calculate event window before event day

I can not calculate event window before event day like -7, -1. System force me to write the last day of event window bigger than 0.

Answer by Dr. Markus Schimmer:
Yes, for technical reasons, we need to enforce that the event date needs to be in your event window. You can conceptually circumvent this requirement by changing the calendar date of your event accordingly.
Question #52: What's your current API key?
Answer by Dr. Markus Schimmer:
You find the API key on this page:
Question #51: length of event window

I am working on a study of biopharma stock prices's responses to receiving "breakthrough therapy designation" (BTD) from the FDA. Our hypothesis is that pre-commercial biotechs will experience a transient stock bump, but excess returns will dissipate by ~90 days. My question relates to the appropriate / maximum length of the event window. What's the maximum or optimal length of the event window, and what factors might dictate the appropriateness of a longer vs. shorter one? We have seen papers with 5-30 day windows, but have not seen a good discussion of how to select the length.

Answer by Dr. Markus Schimmer:
The appropriate length of the event window is driven by your research assumptions on how the capital market is processing the information that is released by the event studied. From what you wrote I assume you have the following assumptions: (1) Prior to the BTD release, there is no information leakage (2) You are studying companies in the US, which means that we should assume semi-strong market efficiency (3) You have the hypothesis that during the 90 days subsequent to the BTD release, abnormal returns are negative and undo the positive effect surrounding the BTD release This will give you the following type of parameters to your event study: + Short event window around the BTD date to capture the positive effect: [0,2] if you are certain that there is no information leakage or [-2,2] if you assume some leakage. You choose the second number based on how opaque the news might be to the capital markets. BTD releases sound quite clear, so you wouldn't assume the US capital market to take more than 2 days to price it in. Note: the smaller your companies, the less coverage they have, the long it may take... + Then, for your 90 day hypothesis you obviously will take a 90 day event window. Most likely, you would ground the calculation on the same estimation window as your [-2,2] window, meaning on the period prior to the BTD event - this will ensure twofold: one, your second analysis uses the same presumed relationship of your firms to the stock markets, and two, you overrule the effect of the BTD event on the stock market-company relationship, which you factually negate given your hypothesis (meaning, this choice is in line with your hypothesis)
Question #50: Event Study about rating changes

Dear Event study tools,


Many thanks in advance for your kind attention

Answer by Dr. Markus Schimmer:
Question #49: t-test fpr CAAR

Dear Dr. Müller,



I am confused and need some help.

Thanks in advance.

Answer by Dr. Simon Müller:
Question #48: Test statistic formula for CARs




What is meant by L2?
Is it the number of days of the event period?


I would be very happy to receive an answer?

Best Wolfgang

Answer by Dr. Simon Müller: