Application of Quantitative Techniques for the Prediction of Bank Acquisition TargetsIn recent years, the banking industry has faced significant challenges due to deregulation, globalization, financial innovation, and intensified global competition. In response to these challenges, banks have adopted strategies to grow and expand their activities, with mergers and acquisitions (M & As) being one of the most popular over the last decade. This unique book thus discusses the use of quantitative classification methods for the prediction of bank acquisitions. With an overview of the M & A trends in the EU banking industry and a survey of the motives for M & As, the authors compare various statistical and computational methodologies used to analyze and predict bank acquisitions. The material constitutes a useful basis for researchers and practitioners in banking management to develop and analyze investment decisions related to M & As. |
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Common terms and phrases
abnormal returns acquired and non-acquired acquired banks acquired firms Acquisition probabilities acquisition targets acquisitions prediction average accuracy average classification accuracy Average Cohen's PABAK bank M&As bank mergers bank's Barnes capital classification methods classifying correct Cohen's Kappa combined compared correct classification cost cross-validation cut-off point discriminant analysis discriminant model diversification double matched Doumpos Economics economies of scale efficiency equity error Espahbodi estimation European banking evaluation event studies examined factors financial ratios financial variables holdout testing increase k-NN logit analysis logit models market power measures mergers and acquisitions MHDIS models developed motives Non-Acq non-acquired banks non-acquired firms non-targets outperforms output Overall Average Cohen's overall classification Palepu Panel performance period prediction ability prediction models prediction of acquisition profitability Research rough sets sector selection shareholders stacked model sub-sample support vector machines SVMs Table takeover targets techniques testing samples total assets training sample UTADIS utility functions validation Zopounidis
References to this book
Handbook of Financial Engineering Constantin Zopounidis,Michael Doumpos,Panos M. Pardalos Limited preview - 2008 |