Predicting the likelihood that a company become the target of an activist investor

Project description

A public company can be the target of a campaign of activist investors. The activity can be in a friendly or hostile manner. The following steps are used to build the supervised ML model.

Data scources:

Purchased data source that provides the pricing data of public companies, the historical campaigns that has been attacked to the companies.

Feature Engineering : Fundamentals, technicals, market cap, competitors and industry of companies are calculated in order to be used as input features for the modeling.

Modeling: This project falls into the category of time series, since there are different campaigns that has been attacked the public companies in the past 10 years and the trend is time varying. Furthermore, the dataset is very skewed in a means that a few perecent of companies has been attacked (few positive examples).

For further details, please contact me at: sa677@njit.edu.