Series on Computers and Operations Research - Vol. 5
APPLICATION OF QUANTITATIVE TECHNIQUES FOR THE PREDICTION OF BANK ACQUISITION TARGETS
by Fotios Pasiouras (Coventry University, UK & Technical University of Crete, Greece), Sailesh Tanna (Coventry University, UK) & Constantin Zopounidis (Technical University of Crete, Greece)
Table of Contents (17k)
Preface (20k)
Chapter 1: Bank M&As - Motives and Evidence (154k)
In 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.
Contents:
- Banks M&As: Motives and Evidence
- Studies on the Prediction of
Acquisition Targets
- Methodological Framework for the Development of Acquisition Targets Prediction Model
- Data and Preliminary Analysis
- Development of Acquisitions Prediction Models
- Integration of Prediction Models
Readership: Academics, operational researchers, management scientists,
financial managers, bank managers, investors and policy-makers.
| 292pp |
Pub. date: Oct 2005 |
|
