Mergers and Acquisitions are becoming more frequent and the possibility of a deal cancellation imposes risk on potential investors, who bought stock of the target companies. Motivated by prior literature which uses financial ratios in order to predict the possibility of a company being a takeover target and studies which assess risk associated with a company by measuring financial analyst forecast dispersion, this project aims at developing a prediction model for merger success on the basis of these variables. Statistical data exploration and several different logistic regression models are used in the analyses. We find, that on the side of the financial variables the relative size between target and acquirer, the target leverage and the time between announcement and completion or withdrawal of a merger are good predictors of takeover success. Successful mergers appear between companies that have a large size difference, targets with low leverage are more likely to be acquired, and a short completion time of the merger contributes to success. On the side of the analyst forecasting variables,the number of analysts following a target company and several different measures of the dispersion among analyst forecasts for acquisition targets showed to be strong predictors of takeover success.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Dueckert, Thilo

Publisher

• Worcester Polytechnic Institute

Identifier

• 00E001M

Advisor

• Higgins, Huong N.
• Wilkens, Kathryn A.

Year

• 2000

Date created

• 2000-01-01

Resource type

• Major Qualifying Project

Rights statement

• In Copyright