Advances in credit risk modelling and corporate bankruptcy prediction:
The field of credit risk and corporate bankruptcy prediction has gained considerable momentum following the collapse of many large corporations around the world, and more recently through the sub-prime scandal in the United States. This book provides a thorough compendium of the different modelling...
Gespeichert in:
| Weitere beteiligte Personen: | , |
|---|---|
| Format: | E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2008
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| Schriftenreihe: | Quantitative methods for applied economics and business research
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| Links: | https://doi.org/10.1017/CBO9780511754197 |
| Zusammenfassung: | The field of credit risk and corporate bankruptcy prediction has gained considerable momentum following the collapse of many large corporations around the world, and more recently through the sub-prime scandal in the United States. This book provides a thorough compendium of the different modelling approaches available in the field, including several new techniques that extend the horizons of future research and practice. Topics covered include probit models (in particular bivariate probit modelling), advanced logistic regression models (in particular mixed logit, nested logit and latent class models), survival analysis models, non-parametric techniques (particularly neural networks and recursive partitioning models), structural models and reduced form (intensity) modelling. Models and techniques are illustrated with empirical examples and are accompanied by a careful explanation of model derivation issues. This practical and empirically-based approach makes the book an ideal resource for all those concerned with credit risk and corporate bankruptcy, including academics, practitioners and regulators. |
| Umfang: | 1 Online-Ressource (x, 298 Seiten) |
| ISBN: | 9780511754197 |
Internformat
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| 520 | |a The field of credit risk and corporate bankruptcy prediction has gained considerable momentum following the collapse of many large corporations around the world, and more recently through the sub-prime scandal in the United States. This book provides a thorough compendium of the different modelling approaches available in the field, including several new techniques that extend the horizons of future research and practice. Topics covered include probit models (in particular bivariate probit modelling), advanced logistic regression models (in particular mixed logit, nested logit and latent class models), survival analysis models, non-parametric techniques (particularly neural networks and recursive partitioning models), structural models and reduced form (intensity) modelling. Models and techniques are illustrated with empirical examples and are accompanied by a careful explanation of model derivation issues. This practical and empirically-based approach makes the book an ideal resource for all those concerned with credit risk and corporate bankruptcy, including academics, practitioners and regulators. | ||
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| 700 | 1 | |a Jones, Stewart |d 1964- | |
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| spelling | Advances in credit risk modelling and corporate bankruptcy prediction edited by Stewart Jones and David A. Hensher Advances in Credit Risk Modelling & Corporate Bankruptcy Prediction Cambridge Cambridge University Press 2008 1 Online-Ressource (x, 298 Seiten) txt c cr Quantitative methods for applied economics and business research The field of credit risk and corporate bankruptcy prediction has gained considerable momentum following the collapse of many large corporations around the world, and more recently through the sub-prime scandal in the United States. This book provides a thorough compendium of the different modelling approaches available in the field, including several new techniques that extend the horizons of future research and practice. Topics covered include probit models (in particular bivariate probit modelling), advanced logistic regression models (in particular mixed logit, nested logit and latent class models), survival analysis models, non-parametric techniques (particularly neural networks and recursive partitioning models), structural models and reduced form (intensity) modelling. Models and techniques are illustrated with empirical examples and are accompanied by a careful explanation of model derivation issues. This practical and empirically-based approach makes the book an ideal resource for all those concerned with credit risk and corporate bankruptcy, including academics, practitioners and regulators. Hensher, David A. 1947- Jones, Stewart 1964- Erscheint auch als Druck-Ausgabe 9780521689540 Erscheint auch als Druck-Ausgabe 9780521869287 |
| spellingShingle | Advances in credit risk modelling and corporate bankruptcy prediction |
| title | Advances in credit risk modelling and corporate bankruptcy prediction |
| title_alt | Advances in Credit Risk Modelling & Corporate Bankruptcy Prediction |
| title_auth | Advances in credit risk modelling and corporate bankruptcy prediction |
| title_exact_search | Advances in credit risk modelling and corporate bankruptcy prediction |
| title_full | Advances in credit risk modelling and corporate bankruptcy prediction edited by Stewart Jones and David A. Hensher |
| title_fullStr | Advances in credit risk modelling and corporate bankruptcy prediction edited by Stewart Jones and David A. Hensher |
| title_full_unstemmed | Advances in credit risk modelling and corporate bankruptcy prediction edited by Stewart Jones and David A. Hensher |
| title_short | Advances in credit risk modelling and corporate bankruptcy prediction |
| title_sort | advances in credit risk modelling and corporate bankruptcy prediction |
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