Reliability of corporate failure prediction models during periods
of intense financial disturbances

Στάικου, Ελένη; Staikou, Eleni

dc.contributor.author	Στάικου, Ελένη	el
dc.contributor.author	Staikou, Eleni	en
dc.date.accessioned	2023-05-12T07:58:01Z
dc.date.available	2023-05-12T07:58:01Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/57682
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.25379
dc.rights	Default License
dc.subject	Εταιρική αποτυχία	el
dc.subject	Πρόβλεψη	el
dc.subject	Πτώχευση	el
dc.subject	Πολυμεταβλητή Διακριτική Ανάλυση	el
dc.subject	Χρηματοοικονομικοί Αριθμοδείκτες	el
dc.subject	Corporate Failure	en
dc.subject	Z-score	en
dc.subject	Prediction	en
dc.subject	Multivariate Discriminant Analysis	en
dc.subject	Bankruptcy	en
dc.title	Reliability of corporate failure prediction models during periods of intense financial disturbances	en
dc.title	Η αξιοπιστία των υποδειγμάτων πρόβλεψης της εταιρικής αποτυχίας σε περιόδους έντονων οικονομικών διαταραχών	el
heal.type	masterThesis
heal.classification	Mathematics, Economics	en
heal.classification	Μαθηματικά, Χρηματοοικονομικά	el
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2020-05-11
heal.abstract	The study entitled “Reliability of corporate failure prediction models during periods of intense financial disturbances”, is the diploma thesis of Staikou Eleni and was conducted for the purpose of the Interdisciplinary Postgraduate Specialization Programme, in the specialty of Financial Engineering, with the title “Mathematical Modeling in Modern Technologies and Financial Engineering”, organized by the School of Applied Mathematics and Physical Sciences of the National Technical University of Athens. The purpose of this thesis was to create a model which would predict corporate failure and was based on Multivariate Discriminant Analysis. The data sample which was used, derived from Greek companies listed on the Athens Stock Exchange during the period 2005-2018. Through the officially published financial statements, various financial ratios were calculated and their simultaneous combination, revealed useful financial characteristics between bankrupt and non-bankrupt companies. The analysis was performed via the statistical programme SPSS and a discriminant function was created which included as independent variables these ratios which provided the highest discrimination ability. Through that function, we were able to predict corporate failure, fours year prior to bankruptcy. Early acknowledgement of warning signs of bankruptcy is a very useful tool for the companies as it gives the opportunity to management of evaluating the financial state of a company at any moment so that the necessary corrective actions can be made under the possibility of bankruptcy.	en
heal.advisorName	Ντόκας, Ιωάννης	el
heal.committeeMemberName	Tsironi, Theofania	en
heal.committeeMemberName	Karakizi, Christina	en
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Εφαρμοσμένων Μαθηματικών και Φυσικών Επιστημών	el
heal.academicPublisherID	ntua
heal.fullTextAvailability	false
heal.fullTextAvailability	false