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This paper develops a specification of the credit scoring model with high discriminatory power to analyze data on loans at the retail banking market. Parametric and non- parametric approaches are employed to produce three models using logistic regression (parametric) and one model using...
Persistent link: https://www.econbiz.de/10003910674
Credit to the private sector has risen rapidly in European emerging markets but its risk evaluation has been largely neglected. Using retail-loan banking data from the Czech Republic we construct two credit risk models based on logistic regression and Classification and Regression Trees. Both...
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Accurate credit-granting decisions are crucial to the efficiency of the decentralized capital allocation mechanisms in modern market economies. Credit bureaus and many financial institutions have developed and used credit-scoring models to standardize and automate, to the extent possible, credit...
Persistent link: https://www.econbiz.de/10003728240
There has been heated debate regarding credit-rating agencies' (CRAs') reporting accuracy of corporate credit ratings, which is essential for investors because they rely on those crediting ratings to make investment decisions. We estimate the reporting accuracy using the data on corporate...
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Analyzing a comprehensive database of limited liability manufacturing firms this paper investigates the relation between a firm’s financial situation and its conditional expected growth rate. Specifically, using quantile regressions, we obtain a quantitative characterization of this relation...
Persistent link: https://www.econbiz.de/10009760791
The transformation of credit scores into probabilities of default plays an important role in credit risk estimation … linear logistic regression. Furthermore, we develop an approach in order to quantify the part of the general estimation error …
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