Identifying Merger and Takeover Targets Using a Self-Organising Map

This study examines the potential of a selforganising map for classifying corporate takeover and merger targets using a range of financial information about companies. A sample of 200 US quoted companies, half which were merger or takeover targets and half which were not, are used to train and test the model. The best self-organised map correctly classified 94.8% of the firms in the training set one year prior to the takeover or merger event, and 95.2% in the out-ofsample validation set, averaged over five recuts of the data. The results provide support for a hypothesis that merger and takeover targets can be predicted, and that self-organised maps can be useful for this purpose.

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