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Einband grossAdvances in Credit Risk Modelling and Corporate Bankruptcy Prediction
ISBN/GTIN

Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction

E-BookPDFDRM AdobeE-Book
Englisch
Cambridge University Presserschienen am25.09.2008
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.mehr
Verfügbare Formate
BuchGebunden
EUR114,50
TaschenbuchKartoniert, Paperback
EUR58,50
E-BookPDFDRM AdobeE-Book
EUR45,49

Produkt

KlappentextThe 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.
Details
Weitere ISBN/GTIN9780511426827
ProduktartE-Book
EinbandartE-Book
FormatPDF
Format HinweisDRM Adobe
Erscheinungsjahr2008
Erscheinungsdatum25.09.2008
SpracheEnglisch
Dateigrösse1923 Kbytes
Artikel-Nr.2797214
Rubriken
Genre9200