This paper uses stochastic frontier analysis to provide international evidence on the impact of the regulatory and supervision framework on bank efficiency. Our dataset consists of 2853 observations from 615 publicly quoted commercial banks operating in 74 countries during the period 2000-2004....

This paper uses discriminant and logit analyses to develop prediction models to identify bank acquisition targets. We consider several methodological issues, such as whether the choice of the estimation technique, the selection of variables, the use of raw versus industry relative data, the...

This paper uses stochastic frontier analysis to provide international evidence on the impact of the regulatory and supervision framework on bank efficiency. Our dataset consists of 2,853 observations from 615 publicly quoted commercial banks operating in 74 countries during the period 2000-2004....

We examine a sample of 18 banks operating in the UK between 2001 and 2006 to provide for the first time evidence on the association between the efficiency of UK banks and two important aspects of board structure, namely board size and composition. We first use data envelopment analysis to...

In this paper, we investigate the relative performance of both linear and non-linear support vector machines (SVMs) models with a polynomial and an RBF kernel in the development of classification models for the prediction of EU bank acquisition targets. The training sample consists of 274 banks,...

We study the determinants of commercial bank acquisitions that occurred over the period 1997-2002 in the European Union single market, by evaluating the impact of bank-specific measures, such as size, growth and efficiency of banks, and external influences reflecting industry level differences...