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Author: Stewart Jones
Publisher: Taylor & Francis
ISBN: 1317225376
Category : Business & Economics
Languages : en
Pages : 243
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Book Description
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.
Author: Stewart Jones
Publisher: Taylor & Francis
ISBN: 1317225376
Category : Business & Economics
Languages : en
Pages : 243
Get Book Here
Book Description
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.
Author: Edward I. Altman
Publisher: John Wiley & Sons
ISBN: 1118046048
Category : Business & Economics
Languages : en
Pages : 314
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Book Description
A comprehensive look at the enormous growth and evolution of distressed debt, corporate bankruptcy, and credit risk default This Third Edition of the most authoritative finance book on the topic updates and expands its discussion of corporate distress and bankruptcy, as well as the related markets dealing with high-yield and distressed debt, and offers state-of-the-art analysis and research on the costs of bankruptcy, credit default prediction, the post-emergence period performance of bankrupt firms, and more.
Author: Edward I. Altman
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 408
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Book Description
"A Wiley-Interscience publication."Includes index. Bibliography: p. 355-361.
Author: Edward I. Altman
Publisher: John Wiley & Sons
ISBN: 1119481805
Category : Business & Economics
Languages : en
Pages : 374
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Book Description
A comprehensive look at the enormous growth and evolution of distressed debt markets, corporate bankruptcy, and credit risk models This Fourth Edition of the most authoritative finance book on the topic updates and expands its discussion of financial distress and bankruptcy, as well as the related topics dealing with leveraged finance, high-yield, and distressed debt markets. It offers state-of-the-art analysis and research on U.S. and international restructurings, applications of distress prediction models in financial and managerial markets, bankruptcy costs, restructuring outcomes, and more.
Author: John Y. Campbell
Publisher:
ISBN:
Category :
Languages : en
Pages : 47
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Book Description
This paper explores the determinants of corporate failure and the pricing of financially distressed stocks using US data over the period 1963 to 2003. Firms with higher leverage, lower profitability, lower market capitalization, lower past stock returns, more volatile past stock returns, lower cash holdings, higher market-book ratios, and lower prices per share are more likely to file for bankruptcy, be delisted, or receive a D rating. When predicting failure at longer horizons, the most persistent firm characteristics, market capitalization, the market-book ratio, and equity volatility become relatively more significant. Our model captures much of the time variation in the aggregate failure rate. Since 1981, financially distressed stocks have delivered anomalously low returns. They have lower returns but much higher standard deviations, market betas, and loadings on value and small-cap risk factors than stocks with a low risk of failure. These patterns hold in all size quintiles but are particularly strong in smaller stocks. They are inconsistent with the conjecture that the value and size effects are compensation for the risk of financial distress.
Author: John Y. Campbell
Publisher:
ISBN: 9783865580818
Category : Business failures
Languages : de
Pages : 36
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Book Description
"This paper explores the determinants of corporate failure and the pricing of financially distressed stocks using US data over the period 1963 to 2003. Firms with higher leverage, lower profitability, lower market capitalization, lower past stock returns, more volatile past stock returns, lower cash holdings, higher market-book ratios, and lower prices per share are more likely to file for bankruptcy, be delisted, or receive a D rating. When predicting failure at longer horizons, the most persistentfirm characteristics, market capitalization, the market-book ratio, and equity volatility become relatively more significant. Our model captures much of the time variation in the aggregate failure rate. Since 1981, financially distressed stocks have delivered anomalously low returns. They have lower returns but much higher standard deviations, market betas, and loadings on value and small-cap risk factors than stocks with a low risk of failure. These patterns hold in all size quintiles but are particularly strong in smaller stocks. They are inconsistent with the conjecture that the value and size effects are compensation for the risk of financial distress"--National Bureau of Economic Research web site.
Author: John Argenti
Publisher:
ISBN: 9780852915790
Category : Business failures
Languages : en
Pages : 16
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Book Description
Author: Natalia Outecheva
Publisher:
ISBN:
Category :
Languages : en
Pages : 191
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Book Description
Author: Konstantin A. Danilov
Publisher:
ISBN:
Category :
Languages : en
Pages : 90
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Book Description
This paper is divided into three sections that address the various elements of understanding, predicting and analyzing corporate failure and bankruptcy. Part I covers the definitions of corporate failure, explains the bankruptcy process and then classifies various potential causes of failure into broad categories. The causes are bifurcated into company-specific versus external factors. The company-specific factors include an in depth discussion and analysis of business causes versus financial causes, as well as the interrelation between the two. The most important factors, such as financial and operating leverage, are explored in great detail to gain a better understanding of their implications and impact on corporate failure. Part II covers various approaches for analyzing corporate risk and predicting corporate failure. It first details the credit analysis process from the perspective of lenders and credit agencies as a method for credit evaluation and prediction of default. Then, it provides an in depth explanation of financial ratio analysis as a prediction method and provides an overview of the main statistical prediction models. It concludes with a discussion of the implications of the model findings with respect to the causes detailed in Part I. Lastly, Part III describes the outcome of the study performed to analyze the causes of failure as described in Part I by using a combination of the methods highlighted in Part II. The purpose of the study is to identify the sequence and magnitude of relative ratio deterioration in failed firms in order to establish the relative frequency of the various categories of causes of failure. Various ratios and metrics were used as proxies for relative liquidity complications, profitability issues, business problems, and leverage concerns. The impact of macroeconomic events is also evaluated by isolating the impact of the 2008-2009 recession on the relative ratio measures.
Author: CFA Danilov (Konstantin A.)
Publisher:
ISBN:
Category :
Languages : en
Pages : 90
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Book Description
This paper is divided into three sections that address the various elements of understanding, predicting and analyzing corporate failure and bankruptcy. Part I covers the definitions of corporate failure, explains the bankruptcy process and then classifies various potential causes of failure into broad categories. The causes are bifurcated into company-specific versus external factors. The company-specific factors include an in depth discussion and analysis of business causes versus financial causes, as well as the interrelation between the two. The most important factors, such as financial and operating leverage, are explored in great detail to gain a better understanding of their implications and impact on corporate failure. Part II covers various approaches for analyzing corporate risk and predicting corporate failure. It first details the credit analysis process from the perspective of lenders and credit agencies as a method for credit evaluation and prediction of default. Then, it provides an in depth explanation of financial ratio analysis as a prediction method and provides an overview of the main statistical prediction models. It concludes with a discussion of the implications of the model findings with respect to the causes detailed in Part I. Lastly, Part III describes the outcome of the study performed to analyze the causes of failure as described in Part I by using a combination of the methods highlighted in Part II. The purpose of the study is to identify the sequence and magnitude of relative ratio deterioration in failed firms in order to establish the relative frequency of the various categories of causes of failure. Various ratios and metrics were used as proxies for relative liquidity complications, profitability issues, business problems, and leverage concerns. The impact of macroeconomic events is also evaluated by isolating the impact of the 2008-2009 recession on the relative ratio measures.
