Modeling default risk with support vector machines

DOI10.1080/14697680903410015zbMath1210.91148OpenAlexW2125943170MaRDI QIDQ2994860

Shiyi Chen, Russ A. Moro, Wolfgang Karl Härdle

Publication date: 29 April 2011

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697680903410015

zbMATH Keywords

statistical learning theorycapital asset pricingeconomics of riskapplications to default risk

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Numerical methods (including Monte Carlo methods) (91G60) Statistical methods; risk measures (91G70) Credit risk (91G40)

Related Items (6)

Credit risk classification: an integrated predictive accuracy algorithm using artificial and deep neural networks ⋮ Bayesian regularized artificial neural networks for the estimation of the probability of default ⋮ Adjusting covariance matrix for risk management ⋮ The Bayesian additive classification tree applied to credit risk modelling ⋮ Exploiting social media with higher-order Factorization Machines: statistical arbitrage on high-frequency data of the S&P 500 ⋮ Can machine learning approaches predict corporate bankruptcy? Evidence from a qualitative experimental design

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