The aim of this paper is to conduct market
segmentation of Arab banks and suggest a model to classify them into cohesive
segments on the basis of their financial ratios as a guideline for future
consolidation. Twelve financial ratios taken from Bankscope Database have been
retrieved for 92 Arab banks for the year 2015. In view of the sensitivity of
multivariate analysis to the normality assumption, it was decided to use the
common log transformation. Factor analysis is used as a data reduction
technique to find twelve financial ratios. Cluster analysis is then used to
separate the 92 Arab banks into five different performance groups (segments). Multi-discriminant
statistical analysis is used to answer the question: can a combination of
financial ratios be used to predict bank’s group membership? Findings of the
study show that multidiscriminant analysis reveals that coverage ratio,
profitability and efficiency separate the groups more widely than other
financial ratios. The classification matrix shows that 98.9% of original banks
are correctly classified. What’s more, to go after a more efficient risk
policy, this paper recommends merging big banks with small Arab banks that are
less profitable, less efficient, and in weaker condition than their
non-acquired peers in addition to merging huge banks operating in different
Arab countries. Results of this study should provide insight for future researchers.
Also, this piece of research bridges the gap between financial ratio analysis
and multivariate statistical analysis for Arab banks.
Article by Suzanne
Charbaji,from American University of Beirut, Beirut, Lebanon
Full access: http://mrw.so/RLDmj
Image from Flickr-cc. |
评论
发表评论