000 02249nam a22002177a 4500
999 _c5048
_d5048
005 20230315115800.0
008 230315b ||||| |||| 00| 0 eng d
020 _a9781138652507
082 _a332.63228
_bJON
100 _aJones, Stewart
_911859
245 _aDistress risk and corporate failure modelling:
_bthe state of the art
260 _bRoutledge
_aNew York
_c2023
300 _axi, 230 p.
365 _aGBP
_b48.99
504 _aTable of Contents 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?
520 _aThis 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.
650 _aStocks--Prices--Mathematical models
_911360
650 _aBusiness failures
_911729
650 _aCorporations--Finance
_9182
942 _2ddc
_cBK