Predicting Corporate Failure - Causes, Predictions and Prevention PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Predicting Corporate Failure - Causes, Predictions and Prevention PDF full book. Access full book title Predicting Corporate Failure - Causes, Predictions and Prevention by Pui Ying Sum. Download full books in PDF and EPUB format.
Author: Pui Ying Sum
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: Pui Ying Sum
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: R.A.I. van Frederikslust
Publisher: Springer Science & Business Media
ISBN: 1468471910
Category : Social Science
Languages : en
Pages : 126
Get Book Here
Book Description
1. 0 INTRODUCTION. In this chapter we define first in Section I. I the concept of failure used in this study. Thereafter, we discuss briefly the causes and possible consequ ences of failure. Finally, we explain in Section 1. 2 the aim of this study. 1. 1 THE CONCEPT OF FAILURE. In this monograph we investigate the predictability of corporate failure. By 'failure' we understand the inability of a firm to pay its obligations when these fall due (i. e. technical cash insolvency). (Walter 1957 and Donaldson 1962 and 1969). Failure mostly appears in a critical situation as a consequ ence of a sharp decline in sales. Such a decline can be caused by a recession, the loss of an important customer, shortage of a raw material, deficiencies of management, etc. The ability to predict corporate failure is important for all parties involved in the corporation, in particular for management and investors. An early warning signal of probable failure will enable them to take preventive measures: changes in operating policy or reorganization of financial structure, but also voluntary liquidation will usually shorten the period over which losses are incurred. The possibility to predict failure is important also from a social point of view, because such an event is an indication of misallocation of resources; prediction provides opportunities to take corrective measures. (See also Lev 1974, p. 134). 1. 2 AIM AND OUTLINE OF THE STUDY.
Author: Om Prakash Kharbanda
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 252
Get Book Here
Book Description
Analyse a wide range of companies that have been close to failure and evaluate the methods adopted to achieve a turnaround. Show the case studies of Rools Royce, Laker and Dunlop.
Author: Constantin Zopounidis
Publisher: Springer Science & Business Media
ISBN: 3642574785
Category : Business & Economics
Languages : en
Pages : 309
Get Book Here
Book Description
During the last decades the globalization, the intensified competition and the rapid changes in the socio-economic and technological environment had a major impact on the global economic, financial and business environments. Within this environment, it is clear that banking institutions worldwide face new challenges and increasing risks, as well as increasing business potentials. The recent experience shows that achieving a sustainable development of the banking system is not only of interest to the banking institutions themselves, but it is also directly related to the development of the whole business and economic environment, both at regional and international level. The variety of new banking products that is constantly being developed to accommodate the increased customer needs (firms, organizations, individuals, etc.) provides a clear indication of the changes that the banking industry has undergone during the last two decades. The establishment of new products of innovative processes and instruments for their requires the implementation efficient management. The implementation of such processes and instruments is closely related to a variety of disciplines, advanced quantitative analysis for risk management, information technology, quality management, etc. The implementation ofthese approaches in banking management is in accordance with the finding that empirical procedures are no longer adequate to address the increasing complexity of the banking industry.
Author: John Argenti
Publisher:
ISBN:
Category : Business failure
Languages : en
Pages :
Get Book Here
Book Description
Author: Błażej Prusak
Publisher: MDPI
ISBN: 303928911X
Category : Business & Economics
Languages : en
Pages : 202
Get Book Here
Book Description
Bankruptcy prediction is one of the most important research areas in corporate finance. Bankruptcies are an indispensable element of the functioning of the market economy, and at the same time generate significant losses for stakeholders. Hence, this book was established to collect the results of research on the latest trends in predicting the bankruptcy of enterprises. It suggests models developed for different countries using both traditional and more advanced methods. Problems connected with predicting bankruptcy during periods of prosperity and recession, the selection of appropriate explanatory variables, as well as the dynamization of models are presented. The reliability of financial data and the validity of the audit are also referenced. Thus, I hope that this book will inspire you to undertake new research in the field of forecasting the risk of bankruptcy.
Author: Sverre Edvard Gunnersen
Publisher:
ISBN:
Category :
Languages : en
Pages : 271
Get Book Here
Book Description
Corporate failure is one of the most popular prediction problems because early identification of at-risk companies presents such a clear economic benefit to creditors, investors and society as a whole. Throughout the years statistically based classification systems, intelligent systems such as Neural Networks with its many variants, and newer techniques such as Genetic Programming have been applied to this problem. Indeed when a new variation or technique is proposed, the prediction of corporate failure is often one of the first test domains for the new methodology. Likewise, the cause of corporate failure is a topic that has received much academic and literary attention, including case studies investigating the trajectories that failing companies take or post hoc qualitative analysis as to whether certain fundamental causes such as one-man-rule can be attributed to the subsequent collapse of a company. However, throughout the history of this topic a number of challenges emerge that remain unaddressed within the literature.The first challenge is that while many papers outlining new classification techniques compare results with another popular classification system as a baseline, little research exists that comprehensively compares many classification techniques across multiple datasets. This thesis finds that intelligent techniques such as Neural Networks, Genetic Programming and Support Vector Machines outperform statistical techniques such as Discriminant Analysis and Logistic Regression.The second challenge is that the desire of researchers to compare results has resulted in the use of the same cross-section of factors, with little analysis as to whether or not the factors being used are impacting on the classification accuracy of the method. This thesis finds that an objective factor selection methodology leads to performance gains.The third is that far less research exists that considers whether share market or macroeconomic data can have a positive impact on classification accuracy. While this research did find some performance gains when including share market information, the difficulty of linking financial information with share market information leads to data loss that outweighs the small performance improvement.The fourth is that while most classificatory research on this problem focuses on the accuracy of the technique, less attention is given to whether the subjective clustering methods used (e.g. by "industry") are effective, and this research finds that an objective clustering technique improves classification accuracy. Furthermore, this research builds on the existing cluster visualisation methods by developing a new and more effective cluster visualisation algorithm.Finally this research attempts to contribute to the theoretical understanding of corporate failure by analysing the classificatory surface of the resulting predictive models and performing a case study analysis of failed companies. In doing so, the model's strengths and limitations are discussed and some of the causes of failure from the literature are identified.In summary, this research makes the following contributions to the field of bankruptcy prediction: a literature review of notable bankruptcy prediction research, a comparison of popular classification techniques, the development and testing of a new objective factor selection methodology, an examination of the effect of share market and macroeconomic data on classification accuracy, the development and testing of a new cluster visualisation method that overcomes limitations in existing methods, an examination of the effect of objective clustering on classification accuracy utilising the new visualisation method, and a case-study analysis on selected failed companies that relates the reasons for failure outlined in secondary sources to the company's failure prediction trajectory.
Author: John Argenti
Publisher:
ISBN: 9780852915790
Category : Business failures
Languages : en
Pages : 16
Get Book Here
Book Description
Author: Andrew Wong
Publisher:
ISBN:
Category :
Languages : en
Pages : 10
Get Book Here
Book Description
The application of bankruptcy prediction models in litigation to evaluate whether a company was in default, or about to default, at a particular time can be helpful in a wide range of contexts when used appropriately, according to a recent AIRA Journal article authored by Managing Principal Andrew Wong and Manager Konstantin Danilov. In "Forecasting Corporate Failure: Understanding Statistical and Theoretical Approaches to Bankruptcy Prediction" (Vol. 29, No. 1, 2015), the authors describe two categories of bankruptcy prediction models -- statistical and theoretical -- and examine their use in litigation. "Statistical models attempt to identify the most common symptoms exhibited by bankrupt companies, and then use this information to estimate the likelihood that a particular firm will go bankrupt in the future," the authors explain. "Conversely, theoretical models predict bankruptcy by attempting to identify and gauge the factors responsible for the causes of bankruptcy."Noting that understanding "the strengths and weaknesses of these approaches is helpful when deciding which particular prediction model to apply in a bankruptcy setting," the authors describe the history of each model, explore their predictive performance and limitations, and examine several case examples. The authors conclude that, because of "differences in rationale, effectiveness, and applicability, each model is uniquely suited" to determine the likelihood that a company will go bankrupt. "As such, the applicability and validity of any approach will always depend on the context and the details of the particular case."
Author: R. A. I. Van Frederikslust
Publisher:
ISBN: 9789020707373
Category : Business failures
Languages : en
Pages : 127
Get Book Here
Book Description
Samenvatting.
