Predicting Greek mergers and acquisitions: a new approach

Athanasios Tsagkanos, Antonios Georgopoulos and Costas Siriopoulos ()

International Journal of Financial Services Management, 2007, vol. 2, issue 4, 289-303

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.

Keywords: mergers; acquisitions; recursive partitioning techniques; Greece; financial services management; takeover targets; takeover prediction. (search for similar items in EconPapers)
Date: 2007
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