That's simple. Please use the grouping variable in the request file and label those lines that represent good news with "good" and those that represent bad news with "bad". Note: When you download the sample data, you will find the grouping variable to hold "addition" as a value since the sample data represents an excerpt of an index reconstitution study - unluckily, I only picked additions and missed out to pick a single deletion.

Each transaction is to be considered as an individual event. And each line in your request file has to have a unique ID as a reference in the first column. The error message you received suggests that you have used multiple times the same number/ID in this column. The company name is only used to retrieve the corresponding closing price data from the firm data file. Thus, if one firm has multiple events/lines in the request file, you should also list the company name multiple times.

You have to fully enumerate the events per each company. Your request file will thus hold a larger number of lines. You can use the grouping variable to create meaningful subsets from this overall universe of events.

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)