Jones | Distress Risk and Corporate Failure Modelling | Buch | 978-1-138-65250-7 | sack.de

Buch, Englisch, 242 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 377 g

Reihe: Routledge Advances in Management and Business Studies

Jones

Distress Risk and Corporate Failure Modelling

The State of the Art
1. Auflage 2022
ISBN: 978-1-138-65250-7
Verlag: Routledge

The State of the Art

Buch, Englisch, 242 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 377 g

Reihe: Routledge Advances in Management and Business Studies

ISBN: 978-1-138-65250-7
Verlag: Routledge


This book is an introduction text to distress risk and corporate failure modelling techniques. It illustrates how to apply a wide range of corporate bankruptcy prediction models and, in turn, highlights their strengths and limitations under different circumstances. It also conceptualises the role and function of different classifiers in terms of a trade-off between model flexibility and interpretability.

Jones's illustrations and applications are based on actual company failure data and samples. Its practical and lucid presentation of basic concepts covers various statistical learning approaches, including machine learning, which has come into prominence in recent years. The material covered will help readers better understand a broad range of statistical learning models, ranging from relatively simple techniques, such as linear discriminant analysis, to state-of-the-art machine learning methods, such as gradient boosting machines, adaptive boosting, random forests, and deep learning.

The book’s comprehensive review and use of real-life data will make this a valuable, easy-to-read text for researchers, academics, institutions, and professionals who make use of distress risk and corporate failure forecasts.

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Zielgruppe


Postgraduate


Autoren/Hrsg.


Weitere Infos & Material


1. The Relevance and Utility of Distress Risk and Corporate Failure Forecasts 2. Searching for the Holy Grail: Alternative Statistical Modelling Approaches 3. The Rise of the Machines 4. An Empirical Application of Modern Machine Learning Methods 5. Corporate Failure Models for Private Companies, Not-for Profits, and Public Sector Entities 6. Whither Corporate Failure Research?


Stewart Jones is Professor of Accounting at the University of Sydney Business School. He specializes in corporate financial reporting and has published extensively in the distress risk and corporate failure modelling field. His publications appear in many leading international journals, including the Accounting Review, the Review of Accounting Studies, Accounting Horizons, Journal of Business Finance and Accounting, the Journal of the Royal Statistical Society, Journal of Banking and Finance and many other leading journals. He has published over 150 scholarly research pieces, including 70 refereed articles, 10 books, and numerous book chapters, working papers, and short monographs. Stewart is currently Senior Editor of the prestigious international quarterly, Abacus.



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