Work

Comparison of Machine Learning Techniques for Analyzing Banks’ Financial Distress

Year: 2016

Type: article

Abstract: Analyzing banks’ financial distress has gained great importance due to their importance in national economy and caused sociological and economic results. Support Vector Machines SVM and Neural Networks NN , known as machine learning methods, are applied for classifying banks as an early warning of financial distress. A case study which is taking thirty private equity commercial banks’ five year data and financial ratios, is carried out. As a result SVM obtains better classification ratio than NNs

Source: Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi

DOI: 10.31795/baunsobed.645223

Authors: Serpil ALTINIRMAK, Çağlar KARAMAŞA

Institution: Anadolu University

Language: English

Topic: Financial Distress and Bankruptcy Prediction

Subfield: Accounting

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W2994866031

FWCI: 1.228

Cites: 21

Cited by: 6

Related to: 10