机器学习模型在预测银行信用风险方面是否比逻辑回归更有效

Q3 Economics, Econometrics and Finance
M. Tessmann, A. Carvalho, Alex Pinto, A. Lima
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Are Machine Learning models more effective than logistic regressions in predicting bank credit risk An assessment from the Brazilian financial markets
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来源期刊
International Journal of Monetary Economics and Finance
International Journal of Monetary Economics and Finance Economics, Econometrics and Finance-Finance
CiteScore
1.20
自引率
0.00%
发文量
25
期刊介绍: International money, banking and finance have become central to understanding how modern open economies and national economic policies work and interact. IJMEF is an international, peer-reviewed journal at the forefront of economic research, fostering discussion on advances in research which have a significant, long-term impact. With articles from both economists and finance experts, IJMEF represents a focal point for understanding issues involved in economic growth, providing a truly global perspective on monetary and financial questions at national and international levels. Topics covered include: -International financial institutions- Monetary theory- Exchange rates and interest rates- Bank services and development- Central banking- International banking- Credit and financial markets- Open economy macroeconomics- Macroeconometrics- International finance- Financial markets and institutions- Corporate governance- Financial liberalisation- Financial performance- Credit channels.
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