Prediction of Acquisition Targets in the UK: A Multicriteria Approach

Operational Research: An International Journal, Vol. 4, No. 2, pp. 191-211, 2004

Posted: 27 Jul 2006

See all articles by Michael Doumpos

Michael Doumpos

Technical University of Crete (TUC) - Department of Production Engineering and Management

Kyriaki Kosmidou

Technical University of Crete (TUC) - Department of Production Engineering and Management

Fotios Pasiouras

GSCM-Montpellier Business School

Abstract

This paper illustrates the use of a multicriteria decision aid technique for the development of a model for the prediction of acquisition targets. A sample of 76 UK firms acquired over the period 2000-2002 matched with 76 non-acquired firms is used to develop a model that discriminates between acquired and non-acquired firms. Back-testing results on the discriminating ability of the model for up to three years prior to acquisition are reported along with a comparison with model developed with other well-known classification techniques, namely discriminant analysis, logistic regression and artificial neural networks. The results indicate that the proposed multicriteria approach is well suited in predicting corporate acquisitions compared to other techniques.

Keywords: Acquisitions, Discrimination, Mergers, Multicriteria Decision Aid

JEL Classification: G34, C6

Suggested Citation

Doumpos, Michael and Kosmidou, Kyriaki and Pasiouras, Fotios, Prediction of Acquisition Targets in the UK: A Multicriteria Approach. Operational Research: An International Journal, Vol. 4, No. 2, pp. 191-211, 2004, Available at SSRN: https://ssrn.com/abstract=920442

Michael Doumpos (Contact Author)

Technical University of Crete (TUC) - Department of Production Engineering and Management ( email )

University Campus
Chania
Crete, 73100
Greece
+30 28210 37318 (Phone)
+30 28210 69410 (Fax)

Kyriaki Kosmidou

Technical University of Crete (TUC) - Department of Production Engineering and Management ( email )

University Campus
Chania
Crete, 73100
Greece

Fotios Pasiouras

GSCM-Montpellier Business School ( email )

2300, Avenue des Moulins
Montpellier, 34185
France

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