Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction
What it is.
Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction assembles leading researchers to set out the methods used to estimate a company's odds of failure. Edited by Professor Stewart Jones and David A. Hensher, it moves credit-risk modelling beyond the simple classifiers that dominated earlier work.
The book covers the advanced statistical techniques, from mixed logit and survival models to early machine-learning approaches, that let a model handle the messy, high-dimensional reality of company data. It is foundational to how credit risk is quantified today.
It is a technical book with a practical purpose: building models of failure that hold up out of sample and across cycles, the discipline that underpins the scoring at Financial Trends Australia.
Written to be used.
- Quantitative analysts building credit and default models.
- Risk professionals who want the methods, not just the headline.
- Academics and graduate students in credit-risk modelling.
- Readers tracing the research lineage behind modern distress scores.
From the publisherCredit risk and corporate bankruptcy prediction gained considerable momentum after the collapse of many large corporations around the world, and again through the sub-prime crisis 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: probit models, advanced logistic regression models such as mixed logit, nested logit and latent class models, survival analysis, non-parametric techniques including neural networks and recursive partitioning, and structural and reduced-form modelling.
Get the book.
The methods behind credit-risk and bankruptcy modelling, assembled with leading researchers.
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