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Combining market and accounting-based models for credit scoring using a classification scheme based on support vector machines

Niklis Dimitrios, Michael Doumpos, Zopounidis Konstantinos

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URIhttp://purl.tuc.gr/dl/dias/C25E661D-AAB9-4380-BBA2-ECDD5723E69D-
Αναγνωριστικόhttp://www.sciencedirect.com/science/article/pii/S0096300314002677-
Αναγνωριστικόhttps://doi.org/10.1016/j.amc.2014.02.028-
Γλώσσαen-
Μέγεθος13 pagesen
ΤίτλοςCombining market and accounting-based models for credit scoring using a classification scheme based on support vector machinesen
ΔημιουργόςNiklis Dimitriosen
ΔημιουργόςΝικλης Δημητριοςel
ΔημιουργόςMichael Doumposen
ΔημιουργόςΔουμπος Μιχαληςel
ΔημιουργόςZopounidis Konstantinosen
ΔημιουργόςΖοπουνιδης Κωνσταντινοςel
ΕκδότηςElsevieren
ΠερίληψηCredit risk rating is an important issue for both financial institutions and companies, especially in periods of economic recession. There are many different approaches and methods which have been developed over the years. The aim of this paper is to create a credit risk rating model, using a machine learning methodology that combines accounting data with the option-based approach of Black, Scholes, and Merton. The model is built on data for companies listed in the Greek stock exchange, but it is also shown to provide accurate results for non-listed firms as well. Linear and nonlinear support vector machines are used for model building, as well as an innovative additive modeling approach, which enables the construction of comprehensible and accurate credit scoring models.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-11-05-
Ημερομηνία Δημοσίευσης2014-
Θεματική ΚατηγορίαCredit risken
Θεματική ΚατηγορίαBlack–Scholes–Merton modelen
Θεματική ΚατηγορίαCredit ratingen
Θεματική ΚατηγορίαSupport vector machinesen
Βιβλιογραφική ΑναφοράD. Niklis, M. Doumpos and C. Zopounidis, "Combining market and accounting-based models for credit scoring using a classification scheme based on support vector machines," Appl. Math. Computat., vol. 234, pp. 69-81, May 2014. doi:10.1016/j.amc.2014.02.028en

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