Statistical Failure Prediction Models for Brittle Materials.

AIAA Journal ◽  
1984 ◽  
Vol 22 (1) ◽  
pp. 135-140 ◽  
Author(s):  
Antonio C. Rufin ◽  
Dean R. Samos ◽  
R. J. H. Bollard
Keyword(s):  
Prediction Models ◽  
Brittle Materials ◽  
Failure Prediction

scholarly journals Evaluating Financial Performance of Saudi Listed Firms: Using Statistical Failure Prediction Models

2019 ◽  
Vol 2 (1) ◽  
pp. 1-18
Author(s):  
Deena Saleh Merza Radhi ◽  
Adel Sarea
Keyword(s):  
Financial Performance ◽  
Prediction Models ◽  
Stock Exchange ◽  
Failure Prediction ◽  
Financial Decisions ◽  
Listed Firms ◽  
Industrial Companies ◽  
Statistical Relationships ◽  
The Given ◽  
Altman Model

The study aims to compare the classification power of three statistical failure prediction models for evaluating financial performance of Saudi Listed Firms. The study sample consisted of 122 listed industrial companies in the Saudi Stock Exchange for the period from 2014 to 2016. Altman model 1968, Kida model and Zmijewski are used as examples of statistical failure prediction models to evaluate the classification power of the given models to assess the financial performance of firms listed on Saudi Stock Exchange. The results showed that Zmijewski model was more powerful in predicting the financial performance of Saudi listed firms than Altman model (1986) and Kida model. The results showed that there are a statistical relationships between some ratios included in the three models and the financal performance of industrial companies, which was measured by EPS. The study recommended users of financial statements of Saudi listed companies to use Zmijewski ?model, which performs well in evaluating their finacial position to be used when making the ?financial decisions.

Corporate Failure: Definitions, Methods, and Failure Prediction Models

2012 ◽  
pp. 357-366
Author(s):  
Jenifer Piesse ◽  
Cheng-Few Lee ◽  
Hsien-Chang Kuo ◽  
Lin Lin
Keyword(s):  
Prediction Models ◽  
Failure Prediction ◽  
Corporate Failure

Corporate failure prediction models in the twenty-first century: a review

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
David Veganzones ◽  
Eric Severin
Keyword(s):  
Prediction Models ◽  
Failure Prediction ◽  
First Century ◽  
Evaluation Metrics ◽  
Prediction Methods ◽  
Content Type ◽  
Corporate Failure ◽  
Twenty First Century ◽  
Definition Of ◽  
Corporate Failure Prediction

Purpose Corporate failure remains a critical financial concern, with implications for both firms and financial institutions; this paper aims to review the literature that proposes corporate failure prediction models for the twenty-first century. Design/methodology/approach This paper gathers information from 106 published articles that contain corporate failure prediction models. The focus of the analysis is on the elements needed to design corporate failure prediction models (definition of failure, sample approach, prediction methods, variables and evaluation metrics and performance). The in-depth review creates a synthesis of current trends, from the view of those elements. Findings Both consensus and divergences emerge regarding the design of corporate failure prediction models. On the one hand, authors agree about the use of bankruptcy as a definition of failure and that at least two evaluation metrics are needed to examine model performance for each class, individually and in general. On the other hand, they disagree about data collection procedures. Although several explanatory variables have been considered, all of them serve as complements for the primarily used financial information. Finally, the selection of prediction methods depends entirely on the research objective. These discrepancies suggest fundamental advances in discovery and establish valuable ideas for further research. Originality/value This paper reveals some caveats and provides extensive, comprehensible guidelines for corporate failure prediction, which researchers can leverage as they continue to investigate this critical financial subject. It also suggests fruitful directions to develop further experiments.

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