An application of multicriteria decision aid models in the prediction of open market share repurchases

An application of multicriteria decision aid models in the prediction of open market share repurchases

0.00 Avg rating0 Votes
Article ID: iaor20123182
Volume: 40
Issue: 6
Start Page Number: 882
End Page Number: 890
Publication Date: Dec 2012
Journal: Omega
Authors: , , ,
Keywords: statistics: inference, statistics: regression
Abstract:

This study presents the first attempt to develop classification models for the prediction of share repurchase announcements using multicriteria decision aid (MCDA) techniques. We use three samples consisting of 434 UK firms, 330 French firms, and 296 German firms, to develop country‐specific models. The MCDA techniques that are applied for the development of the models are the UTilités Additives DIScriminantes (UTADIS) and the ELimination and Choice Expressing REality (ELECTRE) TRI. We adopt a 10‐fold cross validation approach, a re‐sampling technique that allows us to split the datasets in training and validation sub‐samples. Thus, at the first stage of the analysis the aim is the development of a model capable of reproducing the classification of the firms considered in the training samples. Once this stage is completed, the model can be used for the classification of new firms not included in the training samples (i.e. validation stage). The results show that both MCDA models achieve quite satisfactory classification accuracies in the validation sample and they outperform both logistic regression and chance predictions. The developed models could provide the basis for a decision tool for various stakeholders such as managers, shareholders, and investment analysts.

Reviews

Required fields are marked *. Your email address will not be published.