Predicting Corporate Takeover Outcomes Using Machine Learning
The aim of this thesis is to investigate if the machine learning based classification procedure, Random Forest, provides superior prediction performance compared to a logistic regression model fitted using the LASSO framework, when predicting outcomes in corporate takeover situations. This is done in the context of merger arbitrage, an event-driven investment strategy. The classification models ar