Predicting Greek mergers and acquisitions: a new approach
by Athanasios Tsagkanos, Antonios Georgopoulos, Costas Siriopoulos
International Journal of Financial Services Management (IJFSM), Vol. 2, No. 4, 2007

Abstract: In this paper, we investigate the possibility of predicting takeover targets in Greece, which is an incipient market for acquisitions. Our work is based on recursive partitioning techniques, that is decision-tree models, given that takeover likelihood models (such as logit) are not robust over time (Powell, 1997). However, we adopt a new technique with respect to Espahbodi and Espahbodi (2003), the machine learning algorithm J4.8 that is a new application in the sector of mergers and acquisitions. The results show that J4.8 outperforms the classical regression tree, although the predictive accuracy is not promising.

Online publication date: Sat, 15-Dec-2007

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