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Models for assessing the probability of default play an important role in the risk management systems of commercial banks, as they allow assessing the creditworthiness of various counterparties and transactions. Many Russian banks are trying to switch to an advanced approach based on internal...
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We propose a coherent framework using support vector regression (SRV) for generating and ranking a set of high quality models for predicting emerging market sovereign credit spreads. Our framework adapts a global optimization algorithm employing an hv-block cross-validation metric, pertinent for...
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This paper proposes a methodology for default probability estimation for low default portfolios, where the statistical inference may become troublesome. The author suggests using logistic regression models with the Bayesian estimation of parameters. The piecewise logistic regression model and...
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