dc.contributor.author
Mitsiolidou, Olga
en
dc.contributor.author
Kritsa, Maria
en
dc.date.accessioned
2017-05-08T12:08:06Z
dc.date.available
2017-05-09T00:00:31Z
dc.date.issued
2017-05-08
dc.identifier.uri
https://repository.ihu.edu.gr//xmlui/handle/11544/15304
dc.rights
Default License
dc.title
Bankruptcy Prediction For European Banks
en
heal.type
masterThesis
en_US
heal.keywordURI.LCSH
Banks and banking--Europe, Eastern
heal.keywordURI.LCSH
Banks and banking--Europe, Western
heal.keywordURI.LCSH
Banks and banking--European Union countries
heal.keywordURI.LCSH
Bankruptcy
heal.keywordURI.LCSH
Bank failures
heal.license
http://creativecommons.org/licenses/by-nc/4.0
en_US
heal.recordProvider
School of Economics, Business Administration and Legal Studies, Executive MBA
en_US
heal.publicationDate
2017-05-08
heal.abstract
The main purpose of this Dissertation is to examine a sample data of 108
matched
pairs of failed and non
-
failed banks of Eastern and Western Europe., according to the
size of total assets, over the 2006
-
2016 period. Techniques such as Multiple Logistic
Regression and Multiple Discriminant Analysis based on Camel Rating System
were
applied on report data for one, two and three years prior to failure so as to determine
the robustness of bankruptcy prediction models for European Banks.
The logit Model predicts bank failure with 81,75% accuracy in comparison with the
79,55% for the
MDA Model, one year prior to bankruptcy. Nonetheless, MDA Model
outperforms the Logit Model showing 72,44% accuracy two years prior to failure and
67,06% accuracy three years prior to failure.
en
heal.advisorName
Prof. Charitou, Andreas
en
heal.committeeMemberName
Dr. Grose, Christos
en
heal.committeeMemberName
Dr. Sikalidis, Alexandros
en
heal.committeeMemberName
Prof. Charitou, Andreas
en
heal.academicPublisher
IHU
en
heal.academicPublisherID
ihu
en_US
heal.numberOfPages
62
en_US
heal.spatialCoverage
Europe
en
heal.temporalCoverage
2006 - 2016
en