A note on takeover success prediction
AbstractA takeover success prediction model attempts to use information that is publicly available at the time of the announcement in order to predict the probability that a takeover attempt will succeed. This paper develops a takeover success prediction model by comparing two techniques: the traditional logistic regression model and the artificial neural network technology. To alleviate the problem of bias from the sampling variation, we validate our results through re-sampling. Our empirical results indicate that 1). Arbitrage spread, target resistance, deal structure and transaction size are the dominating factors that have impacts on the outcome of a takeover attempt. 2). Neural network model outperforms logistic regression in predicting failed takeover attempts and performs as well as logistic regression in predicting successful takeover attempts.
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Bibliographic InfoArticle provided by Elsevier in its journal International Review of Financial Analysis.
Volume (Year): 17 (2008)
Issue (Month): 5 (December)
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Web page: http://www.elsevier.com/locate/inca/620166
Takeover success prediction Artificial neural network Logistic regression;
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NBER Working Papers
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