Empirical investigations regarding ratio-based modelling of corporate collapse have been ongoing for decades. With any study of an empirical nature, a data sample is a necessary pre-requisite. It allows testing the performance of the prediction model, thereby establishing its practical relevance. However, it is necessary to first ensure that the data sample used satisfies certain conditions, and these have led to some choice controversies. This paper considers the controversial issues that arise in data sampling, provides a critical evaluation of these issues, and makes choice recommendations on the controversial aspects, by empirically examining the literature
An investigation into the use of mathematical models in the prediction of corporate failure, and the...
This paper utilizes a methodological approach called Multi-Level Modeling (MLM) that addresses two m...
Much has been written about the use of multiple discriminant analysis in corporate distress classifi...
Empirical investigations regarding ratio-based modelling of corporate collapse have been ongoing for...
Empirical investigations regarding ratio-based modelling of corporate collapse have been on going fo...
Up until 1979, Multiple Discriminant Analysis (MDA) was the primary multivariate methodological appr...
The year 1968 saw a major shift from univariate to multivariate methodological approaches to ratio-b...
This paper investigates problems associated with interpretations of corporate collapse, and argues f...
This paper provides a fonnal ranking of the popularity of financial ratios in modeling corporate col...
The models developed in the literature with respect to the prediction of a company s failure are bas...
Regardless of the technical procedure used in signalling corporate collapse, the bottom line rests o...
This paper investigates the predictive accuracies of corporate failure models. We find, through the ...
The recognition of behavioural elements in finance has caused major shifts in the analytic framework...
This paper highlights the prevalence and extent of financial fraud amongst collapsed corporations. I...
This paper draws on empirical evidence to demonstrate that a heuristic framework signals collapse wi...
An investigation into the use of mathematical models in the prediction of corporate failure, and the...
This paper utilizes a methodological approach called Multi-Level Modeling (MLM) that addresses two m...
Much has been written about the use of multiple discriminant analysis in corporate distress classifi...
Empirical investigations regarding ratio-based modelling of corporate collapse have been ongoing for...
Empirical investigations regarding ratio-based modelling of corporate collapse have been on going fo...
Up until 1979, Multiple Discriminant Analysis (MDA) was the primary multivariate methodological appr...
The year 1968 saw a major shift from univariate to multivariate methodological approaches to ratio-b...
This paper investigates problems associated with interpretations of corporate collapse, and argues f...
This paper provides a fonnal ranking of the popularity of financial ratios in modeling corporate col...
The models developed in the literature with respect to the prediction of a company s failure are bas...
Regardless of the technical procedure used in signalling corporate collapse, the bottom line rests o...
This paper investigates the predictive accuracies of corporate failure models. We find, through the ...
The recognition of behavioural elements in finance has caused major shifts in the analytic framework...
This paper highlights the prevalence and extent of financial fraud amongst collapsed corporations. I...
This paper draws on empirical evidence to demonstrate that a heuristic framework signals collapse wi...
An investigation into the use of mathematical models in the prediction of corporate failure, and the...
This paper utilizes a methodological approach called Multi-Level Modeling (MLM) that addresses two m...
Much has been written about the use of multiple discriminant analysis in corporate distress classifi...