Compute Acquisition Quality of Fortune 500 companies

Phase 1: M&A data mining

This phase currently involves using files containing html tables manually copied from wikipedia pages such as this one

to turn this into a more readable file run (under the current implementation):
python m_and_a_crawl\table_converter -f m_and_a_crawl\tables\wiki_apple_acq.html -t Date Company -o out.txt -k AAPL
from the F500 directory or
python m_and_a_crawl\table_converter -h for help

Phase 2: Stock historical values

This phase is currently under construction under the m_and_a_quality module

Phase 3: Quality quantification stage

While this stage is not yet implemented, the heurisitc used to measure quality of an aquisition is based on the market's reaction to the acquisition announcement:

Let us define:

• Pre7: the average value of the stock during the 7 days prior to the acquisition

• Pre30: the average value of the stock during the 30 days prior to the acquisition

• Pre23: the average value of the stock during the 23 days prior to 7 days before the acquisition (intuitively, Pre30 without Pre7)

• Post7: the average value of the stock during the 7 days after the acquisition

• PreTrend: (Pre7-Pre23)/Pre30

• PostTrend: (Post7-Pre30)/Pre30

• Quality: (PostTrend-PreTrend)/PreTrend

Phase 4: Visualization

This phase is not yet under construction.