I am trying to use M&A data from Eventvestor is Research Notebook. One can pull the whole dataset of M&A data into a python dataframe with no problems for the whole historical period from 2011 to 2017 . Each row in the dataset is one news event, which can be an announcement or closing or rejection or termination. However the data is poorly structured as there is absolutely no linkage of termination /rejection/closing events to the announcement events. Basically what we want from M&A dataset is a sequence of all events pertaining to one M&A deal , starting from announcement. So there needs to be an index that uniquely labels all deals and all events should refer to a deal. Eventvestor data does not have any deal index , why is it so? This does not seem to be a professional way to present the data.
In practical terms , is there a workaround for this problem? Trying to link rejections/terminations/closings to announcements using 'symbol', 'related_entity' and 'related_symbol' fields produces a lot of failures when no matches are found.
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