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

DOI10.1016/j.amc.2014.02.028zbMath1298.91178OpenAlexW3124238945MaRDI QIDQ470747

Michael Doumpos, Dimitrios Niklis, Constantin Zopounidis

Publication date: 13 November 2014

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2014.02.028

zbMATH Keywords

credit risksupport vector machinescredit ratingBlack-Scholes-Merton model

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Learning and adaptive systems in artificial intelligence (68T05) Credit risk (91G40)

Related Items (2)

A new decision-making approach for multiple criteria sorting with an imbalanced set of assignment examples ⋮ Enterprise credit risk portrait and evaluation from the perspective of the supply chain

Cites Work

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• The Pricing of Options and Corporate Liabilities
• Comprehensible credit scoring models using rule extraction from support vector machines
• Credit Scoring and Its Applications

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