✍ Scribed by Chrysovalantis Gaganis; Fotios Pasiouras; Constantin Zopounidis
No coin nor oath required. For personal study only.
In this paper, we use a sample of 894 banks from 79 countries to develop a multicriteria decision aid model, for the classification of banks into three groups on the basis of their soundness. The model is developed with the UTilités Additives DIScriminantes (UTADIS) method, through a 10‐fold cross‐validation procedure using six financial and four non‐financial variables. The ratings of Fitch form the basis for assigning banks into the three groups. The results indicate that the asset quality (as measured by loan loss provisions), capitalization, and the market where banks operate are the most important criteria (in terms of weights) in classifying the banks. Profitability and efficiency in expenses management are also important attributes, whereas size and listing in a stock exchange are the least important ones. UTADIS achieves higher classification accuracies than discriminant analysis and ordinary logistic regression which are used for benchmarking purposes. Copyright © 2007 John Wiley & Sons, Ltd.
📜 SIMILAR VOLUMES
Decision making is one of the most important activities for human beings. Complex decision making problems are full of uncertainty and ambiguities. A large amount of data is needed and several strategies must be applied at the same time in order to get a good decision. Research about decision suppor