Corporate credit default models: a mixed logit approach

Corporate credit default models: a mixed logit approach The popular logit model is extended to allow for varying stochastic parameters (mixed logit) and non-linearities of regressor variables while analysing a cross-sectional sample of German corporate credit defaults. With respect to economic interpretability and goodness of probability forecasts according to disriminatory power and calibration, empirical results favor the extended specifications. The mixed logit model is particularly useful with respect to interpretability. However, probability forecasts based on the mixed logit model are not distinctively preferred to extended logit models allowing for non-linearities in variables. Further potential improvements with the help of the mixed logit approach for panel data are shown in a Monte Carlo study. Review of Quantitative Finance and Accounting Springer Journals

Corporate credit default models: a mixed logit approach

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Springer US
Copyright © 2012 by Springer Science+Business Media, LLC
Economics / Management Science; Finance/Investment/Banking; Accounting/Auditing; Econometrics; Operations Research/Decision Theory
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  • Financial ratios, discriminant analysis, and the prediction of corporate bankruptcy
    Altman, EI
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    Aziz, MA; Dar, HA

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